Top-down and bottom-up algorithms
        for nonparametric function estimation in Gaussian noise using
        Unbalanced Haar wavelets.
If a procedure consists of several stages and there are several models that can be selected for each stage,
	uncertainty of the procedure can be decomposed by stages or models.
	This package includes the ANOVA-based method, the cumulative uncertainty-based method, and the balanced decomposition method.
	Yongdai Kim et al. (2019) <doi:10.1016/j.hydroa.2019.100024> is a related paper which is accessible via the URL below.
Implements the Gaussian method of first and second order, the Kragten numerical method and the Monte Carlo simulation method for uncertainty estimation and analysis.
Provides functions for estimating uncertainty in the number of fatalities in the Uppsala Conflict Data Program (UCDP) data. The package implements a parametric reported-value Gumbel mixture distribution that accounts for the uncertainty in the number of fatalities in the UCDP data. The model is based on information from a survey on UCDP coders and how they view the uncertainty of the number of fatalities from UCDP events. The package provides functions for making random draws of fatalities from the mixture distribution, as well as to estimate percentiles, quantiles, means, and other statistics of the distribution. Full details on the survey and estimation procedure can be found in Vesco et al (2024).
Dataset contains select attributes for each match result since 1949-1950 season for UNC men's basketball team.
Implements Minimum Torsion for portfolio diversification as
    described in Meucci, Attilio (2013) <doi:10.2139/ssrn.2276632>.
Model data with a suspected clustering structure (either in 
    co-variate space, regression space or both) using a Bayesian product model 
    with a logistic regression likelihood. Observations are represented 
    graphically and clusters are formed through various edge removals or 
    additions. Cluster quality is assessed through the log Bayesian evidence of 
    the overall model, which is estimated using either a Sequential Monte Carlo 
    sampler or a suitable transformation of the Bayesian Information Criterion 
    as a fast approximation of the former. The internal Iterated Batch 
    Importance Sampling scheme (Chopin (2002 <doi:10.1093/biomet/89.3.539>)) is 
    made available as a free standing function.
A framework for estimating difference-in-differences with
 unpoolable data, based on Karim, Webb, Austin, and Strumpf (2025)
 <doi:10.48550/arXiv.2403.15910>. Supports common or staggered adoption, multiple
 groups, and the inclusion of covariates. Also computes p-values for the
 aggregate average treatment effect on the treated via the
 randomization inference procedure described in MacKinnon and Webb (2020)
 <doi:10.1016/j.jeconom.2020.04.024>.
Detects values imported from spreadsheets that were auto-converted 
    to Excel date serials and reconstructs the originally intended day.month
    decimals (for example, '30.3' that Excel displayed as '30/03/2025').
    The functions work in a vectorized manner, preserve non-serial values, and 
    support both the 1900 and 1904 date systems.
A variational mapping approach that reveals and expands future temporal dynamics from folded high-dimensional geometric distance spaces, unfold turns a set of time series into a 4D block of pairwise distances between reframed windows, learns a variational mapper that maps those distances to the next reframed window, and produces horizon-wise predictive functions for each input series. In short: it unfolds the future path of each series from a folded geometric distance representation.
Use syntax inspired by the package 'glue' to extract matched substrings in a more intuitive and compact way than by using standard regular expressions.
Versatile method for ungrouping histograms (binned count data) 
 assuming that counts are Poisson distributed and that the underlying sequence 
 on a fine grid to be estimated is smooth. The method is based on the composite 
 link model and estimation is achieved by maximizing a penalized likelihood. 
 Smooth detailed sequences of counts and rates are so estimated from the binned 
 counts. Ungrouping binned data can be desirable for many reasons: Bins can be 
 too coarse to allow for accurate analysis; comparisons can be hindered when 
 different grouping approaches are used in different histograms; and the last 
 interval is often wide and open-ended and, thus, covers a lot of information 
 in the tail area. Age-at-death distributions grouped in age classes and 
 abridged life tables are examples of binned data. Because of modest assumptions, 
 the approach is suitable for many demographic and epidemiological applications. 
 For a detailed description of the method and applications see 
 Rizzi et al. (2015) <doi:10.1093/aje/kwv020>.
Create United Nations High Commissioner for Refugees (UNHCR)
    branded documents, presentations, and reports using R Markdown templates.
    This package provides customized formats that align with UNHCR's official
    brand guidelines for creating professional PDF reports, Word documents,
    PowerPoint presentations, and HTML outputs.
A 'ggplot2' theme and color palettes following
    the United Nations High Commissioner for Refugees (UNHCR) Data Visualization Guidelines recommendations.
Verb-like functions to work with messy data, often derived from 
             spreadsheets or parsed PDF tables. Includes functions for unwrapping 
             values broken up across rows, relocating embedded grouping values, 
             and to annotate meaningful formatting in spreadsheet files.
Implement a shrinkage estimation for the univariate normal mean based on a preliminary test (pretest) estimator. This package also provides the confidence interval based on pivoting the cumulative density function. The methodologies are published in Taketomi et al.(2024) <doi:10.1007/s42081-023-00221-2> and Taketomi et al.(2024-)(under review).
A classification (decision) tree is constructed from survival data with high-dimensional covariates.
 The method is a robust version of the logrank tree, where the variance is stabilized.
 The main function "uni.tree" returns a classification tree for a given survival dataset.
 The inner nodes (splitting criterion) are selected by minimizing the P-value of the two-sample the score tests.
 The decision of declaring terminal nodes (stopping criterion) is the P-value threshold given by an argument (specified by user).
 This tree construction algorithm is proposed by Emura et al. (2021, in review).
Nonparametric estimation of a unimodal or U-shape covariate effect under additive hazards model.
An R client to fetch SDMX (Statistical Data and Metadata eXchange)
    CSV series from the UNICEF Data Warehouse <https://data.unicef.org/>.
    Part of a trilingual suite also available for 'Python' and 'Stata'.
    Features include automatic pagination, caching with memoisation, country
    name lookups, metadata versioning (vintages), and comprehensive indicator
    support for SDG (Sustainable Development Goals) monitoring.
UNIfied Cross-Omics deconvolution (Unico) deconvolves
    standard 2-dimensional bulk matrices of samples by features into a
    3-dimensional tensors representing samples by features by cell types.
    Unico stands out as the first principled model-based deconvolution
    method that is theoretically justified for any heterogeneous genomic
    data. For more details see Chen and Rahmani et al. (2024)
    <doi:10.1101/2024.01.27.577588>.
Data from Unicode 17.0.0 and related utilities.
Most universities use specific color combinations to express their unique brand identity. The 'unicol' package provides the colors and color palettes of various universities for easy plotting and printing in R. We collect and provide a diverse range of color palettes for creating scientific visualizations.
Testing whether two discrete variables have a functional
  relationship under null distributions where the two variables are
  statistically independent with fixed marginal counts.
  The fast enumeration algorithm was based on (Nguyen et al. 2020) <doi:10.24963/ijcai.2020/372>.
Uniform sampling of Directed Acyclic Graphs (DAG) using exact
 enumeration by relating each DAG to a sequence of outpoints (nodes with no
 incoming edges) and then to a composition of integers as suggested by
 Kuipers, J. and Moffa, G. (2015) <doi:10.1007/s11222-013-9428-y>.
Probability functions, family for glm() and Stan code for working with the unifed distribution (Quijano Xacur, 2019; <doi:10.1186/s40488-019-0102-6>).
In many phase I trials, the design goal is to find the dose associated with a certain target toxicity rate. In some trials, the goal can be to find the dose with a certain weighted sum of rates of various toxicity grades. For others, the goal is to find the dose with a certain mean value of a continuous response. This package provides the setup and calculations needed to run a dose-finding trial with non-binary endpoints and performs simulations to assess design’s operating characteristics under various scenarios. Three dose finding designs are included in this package: unified phase I design (Ivanova et al. (2009) <doi:10.1111/j.1541-0420.2008.01045.x>), Quasi-CRM/Robust-Quasi-CRM (Yuan et al. (2007) <doi:10.1111/j.1541-0420.2006.00666.x>, Pan et al. (2014) <doi:10.1371/journal.pone.0098147>) and generalized BOIN design (Mu et al. (2018) <doi:10.1111/rssc.12263>). The toxicity endpoints can be handled with these functions including equivalent toxicity score (ETS), total toxicity burden (TTB), general continuous toxicity endpoints, with incorporating ordinal grade toxicity information into dose-finding procedure. These functions allow customization of design characteristics to vary sample size, cohort sizes, target dose-limiting toxicity (DLT) rates, discrete or continuous toxicity score, and incorporate safety and/or stopping rules.
Provides a unified R6-based interface for various machine learning models with automatic interface detection, consistent cross-validation, model interpretations via numerical derivatives, and visualization. Supports both regression and classification tasks with any model function that follows R's standard modeling conventions (formula or matrix interface).
Functions for the creation and manipulation of scenes and objects
    within the 'Unity' '3D' video game engine (<https://unity.com/>). Specific
    focuses include the creation and import of terrain data and 'GameObjects' as
    well as scene management.
Uniform sampling on various geometric shapes, such as
    spheres, ellipsoids, simplices.
In diagnostic contexts, individuals are often assessed using multiple
 tests that measure the same latent variable (e.g., intelligence). These test scores
 are typically not exactly identical. Simple averaging neglects the correlation
 between tests and the reduced variance of their combination. The 'unifyR' package
 provides functions to compute statistically accurate unified scores, reliabilities
 and validities of multiple tests. The underlying algorithms build on and extend the
 method proposed by Evans (1996, <DOI:10.3758/BF03204767>) and have been validated
 through simulations.
A unified R graphics backend. Render R graphics fast and easy to many common file formats.
    Provides a thread safe 'C' interface for asynchronous rendering of R graphics.
Define and use graphical elements of corporate design manuals in R. The 'unikn' package provides color functions (by defining dedicated colors and color palettes, and commands for finding, changing, viewing, and using them) and styled text elements (e.g., for marking, underlining, or plotting colored titles). The pre-defined range of colors and text decoration functions is based on the corporate design of the University of Konstanz <https://www.uni-konstanz.de/>, but can be adapted and extended for other purposes or institutions.
Fit a univariate-guided sparse regression (lasso), by a two-stage procedure. The first stage fits p separate univariate models to the response. The second stage gives more weight to the more important univariate features, and preserves their signs. Conveniently, it returns an objects that inherits from class 'glmnet', so that all of the methods for 'glmnet' are available. See Chatterjee, Hastie and Tibshirani (2025) <doi:10.1162/99608f92.c79ff6db> for details.
Connect to Uniprot <https://www.uniprot.org/> to retrieve information about proteins using their accession number such information could be name or taxonomy information, For detailed information kindly read the publication <doi:10.1016/j.jprot.2019.103613>.
For each string in a set of strings, determine a unique tag that is a substring of fixed size k unique to that string, if it has one. If no such unique substring exists, the least frequent substring is used. If multiple unique substrings exist, the lexicographically smallest substring is used. This lexicographically smallest substring of size k is called the "UniqTag" of that string.
Univariate spline regression. It is possible to add the shape constraint of unimodality and predefined or
	self-defined penalties on the B-spline coefficients.
Provides the ability to read 'Unisens' data into R. 'Unisens' is a universal data format for multi sensor data.
The uc.check() function checks whether the roots of a given polynomial lie outside the Unit circle. You can also easily draw an unit circle.
United is a software tool which can be downloaded at the following
    website <http://www.schroepl.net/pbm/software/united/>. In general, it is
    a virtual manager game for football teams. This package contains helpful
    functions for determining an optimal formation for a virtual match in
    United. E.g. knowing that the opponent has a strong defensive it is
    advisable to beat him in the midfield. Furthermore, this package contains
    functions for computing the optimal usage of hardness in a game.
Simplifies regression tests by comparing objects produced by test
    code with earlier versions of those same objects.  If objects are unchanged
    the tests pass, otherwise execution stops with error details.  If in
    interactive mode, tests can be reviewed through the provided interactive
    environment.
Tools to detect and correct measurement-unit errors in multivariate numeric data using model-based clustering. Gaussian mixture models with user-defined translation vectors identify clusters of records that differ in scale or unit. Core functionality includes cluster assignment via the EM algorithm, error correction based on posterior probabilities and pairwise scatterplot visualizations. For more details see Di Zio, Guarnera and Luzi (2005) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2005001/article/8087-eng.pdf>.
A collection of parametric quantile regression models for bounded data. At present, the package provides 13 parametric quantile regression models. It can specify regression structure for any quantile and shape parameters. It also provides several S3 methods to extract information from fitted model, such as residual analysis, prediction, plotting, and model comparison. For more computation efficient the [dpqr]'s, likelihood, score and hessian functions are written in C++. For further details see Mazucheli et. al (2022) <doi:10.1016/j.cmpb.2022.106816>.
A unified framework for unit root and stationarity testing
    including quantile ADF tests (Koenker and Xiao, 2004)
    <doi:10.1198/016214504000001114>, GARCH-based unit root tests with
    endogenous structural breaks (Narayan and Liu, 2015)
    <doi:10.1016/j.eneco.2014.11.021>, and comprehensive Dickey-Fuller,
    Phillips-Perron, KPSS, ERS/DF-GLS, Zivot-Andrews, and
    Kobayashi-McAleer tests with an Elder-Kennedy decision strategy
    (Elder and Kennedy, 2001) <doi:10.1080/00220480109595179>.
Support for measurement units in R vectors, matrices
    and arrays: automatic propagation, conversion, derivation
    and simplification of units; raising errors in case of unit
    incompatibility. Compatible with the POSIXct, Date and difftime 
    classes. Uses the UNIDATA udunits library and unit database for 
    unit compatibility checking and conversion.
    Documentation about 'units' is provided in the paper by Pebesma, Mailund &
    Hiebert (2016, <doi:10.32614/RJ-2016-061>), included in this package as a
    vignette; see 'citation("units")' for details.
A test to understand the stability of the underlying 
    stochastic data. Helps the user’s understand whether the random variable under 
    consideration is stationary or non-stationary without any manual interpretation 
    of the results. It further ensures to check all the prerequisites and assumptions which 
    are underlying the unit root test statistics and if the underlying data is found to be non-stationary in all
    the 4 lags the function diagnoses the input data and returns with an optimised solution on the same.
Concise TAP <http://testanything.org/> compliant unit testing package. Authored tests can be run using CMD check with minimal implementation overhead.
Implementation of the unity forest (UFO) framework (Hornung & Hapfelmeier, 2026,
  <doi:10.48550/arXiv.2601.07003>).
  UFOs are a random forest variant designed to better take covariates with purely
  interaction-based effects into account, including interactions for which none of the involved
  covariates exhibits a marginal effect.
  While this framework tends to improve discrimination and predictive accuracy compared
  to standard random forests, it also facilitates the identification and interpretation of
  (marginal or interactive) effects: In addition to the UFO algorithm for tree construction,
  the package includes the unity variable importance measure (unity VIM), which quantifies
  covariate effects under the conditions in which they are strongest - either marginally 
  or within subgroups defined by interactions - as well as covariate-representative tree
  roots (CRTRs) that provide interpretable visualizations of these conditions.
  Categorical and continuous outcomes are supported.
  This package is a fork of the R package 'ranger' (main author: Marvin N. Wright), which
  implements random forests using an efficient C++ backend.
Assess essential unidimensionality using external validity
    information  using the procedure proposed by Ferrando & Lorenzo-Seva
    (2019) <doi:10.1177/0013164418824755>. Provides two indices for assessing
    differential  and incremental validity, both based on a second-order 
    modelling schema for the general factor.
User-friendly maximum likelihood estimation (Fisher (1921) 
    <doi:10.1098/rsta.1922.0009>) of univariate densities.
Algorithms for checking the accuracy of a clustering result with known classes, computing cluster validity indices, and generating plots for comparing them.
    The package is compatible with K-means, fuzzy C means, EM clustering, and hierarchical clustering (single, average, and complete linkage).
    The details of the indices in this package can be found in:
    J. C. Bezdek, M. Moshtaghi, T. Runkler, C. Leckie (2016) <doi:10.1109/TFUZZ.2016.2540063>,
    T. Calinski, J. Harabasz (1974) <doi:10.1080/03610927408827101>,
    C. H. Chou, M. C. Su, E. Lai (2004) <doi:10.1007/s10044-004-0218-1>,
    D. L. Davies, D. W. Bouldin (1979) <doi:10.1109/TPAMI.1979.4766909>,
    J. C. Dunn (1973) <doi:10.1080/01969727308546046>,
    F. Haouas, Z. Ben Dhiaf, A. Hammouda, B. Solaiman (2017) <doi:10.1109/FUZZ-IEEE.2017.8015651>,
    M. Kim, R. S. Ramakrishna (2005) <doi:10.1016/j.patrec.2005.04.007>,
    S. H. Kwon (1998) <doi:10.1049/EL:19981523>,
    S. H. Kwon, J. Kim, S. H. Son (2021) <doi:10.1049/ell2.12249>,
    G. W. Miligan (1980) <doi:10.1007/BF02293907>,
    M. K. Pakhira, S. Bandyopadhyay, U. Maulik (2004) <doi:10.1016/j.patcog.2003.06.005>,
    M. Popescu, J. C. Bezdek, T. C. Havens, J. M. Keller (2013) <doi:10.1109/TSMCB.2012.2205679>,
    S. Saitta, B. Raphael, I. Smith (2007) <doi:10.1007/978-3-540-73499-4_14>,
    A. Starczewski (2017) <doi:10.1007/s10044-015-0525-8>,
    Y. Tang, F. Sun, Z. Sun (2005) <doi:10.1109/ACC.2005.1470111>,
    N. Wiroonsri (2024) <doi:10.1016/j.patcog.2023.109910>,
    N. Wiroonsri, O. Preedasawakul (2023) <doi:10.48550/arXiv.2308.14785>,
    C. H. Wu, C. S. Ouyang, L. W. Chen, L. W. Lu (2015) <doi:10.1109/TFUZZ.2014.2322495>, 
    X. Xie, G. Beni (1991) <doi:10.1109/34.85677> and
    P.J. Rousseeuw (1987) and L. Kaufman and P.J. Rousseeuw(2009) <doi:10.1016/0377-0427(87)90125-7> and 
    <doi:10.1002/9780470316801>
    C. Alok. (2010).
Provides S3 generic methods and some default implementations
    for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC)
    samples.  The purpose of 'universals' is to reduce package
    dependencies and conflicts.  The 'nlist' package implements many of
    the methods for its 'nlist' class.
Provides well-known techniques for detecting univariate
    outliers. Methods for handling skewed distributions are included.
    The Hidiroglou-Berthelot (1986) method for detecting outliers in
    ratios of historical data is also implemented. When available,
    survey weights can be incorporated in the detection process.
Pseudo-random number generation of 17 univariate distributions proposed by Demirtas. (2005) <DOI:10.22237/jmasm/1114907220>.
Bindings to system utilities found in most Unix systems such as
    POSIX functions which are not part of the Standard C Library.
Separate a data frame in two based on key columns. The function
 unjoin() provides an inside-out version of a nested data frame. This is used
 to identify duplication and normalize it (in the database sense) by linking
 two tables with the redundancy removed. This is a basic requirement for
 detecting topology within spatial structures that has motivated the need for
 this package as a building block for workflows within more applied projects.
Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) <doi:10.1111/2041-210X.14123>, Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.
Tools for fitting and assessing Bayesian multilevel regression 
  models that account for unmeasured confounders.
Fast flattening of hierarchical data structures (e.g. JSON, XML)
             into data.frames with a flexible spec language.
Assess the significance of identified clusters and estimates the true number of clusters by comparing the explained variation due to the clustering from the original data to that produced by clustering a unimodal reference distribution which preserves the covariance structure in the data. The reference distribution is generated using kernel density estimation and a Gaussian copula framework. A dimension reduction strategy and sparse covariance estimation optimize this method for the high-dimensional, low-sample size setting. This method is described in Helgeson, Vock, and Bair (2021) <doi:10.1111/biom.13376>.
Tools for converting data from complex or irregular layouts to a
    columnar structure.  For example, tables with multilevel column or row
    headers, or spreadsheets.  Header and data cells are selected by their
    contents and position, as well as formatting and comments where available,
    and are associated with one other by their proximity in given directions.
    Functions for data frames and HTML tables are provided.
Methods for managing under- and over-enrollment in Simon's Two-Stage Design are offered by providing adaptive threshold adjustments and sample size recalibration. It also includes post-inference analysis tools to support clinical trial design and evaluation. The package is designed to enhance flexibility and accuracy in trial design, ensuring better outcomes in oncology and other clinical studies. Yunhe Liu, Haitao Pan (2024). Submitted.
Provides half-normal plots, reference plots, and Pareto plots
    of effects from an unreplicated experiment, along with various 
    pseudo-standard-error measures, simulated reference distributions, 
    and other tools. Many of these methods are described in 
    Daniel C. (1959) <doi:10.1080/00401706.1959.10489866> and/or
    Lenth R.V. (1989) <doi:10.1080/00401706.1989.10488595>, but some new
    approaches are added and integrated in one package.
Wraps the 'unrtf' utility <https://www.gnu.org/software/unrtf/> to 
    extract text from RTF files. Supports document conversion to HTML, LaTeX or
    plain text. Output in HTML is recommended because 'unrtf' has limited 
    support for converting between character encodings.
Automatically converts language-specific verbal information, e.g., "1st half of the 19th century," to its standardized numerical counterparts, e.g., "1801-01-01/1850-12-31." It follows the recommendations of the 'MIDAS' ('Marburger Informations-, Dokumentations- und Administrations-System'), see <doi:10.11588/artdok.00003770>.
Reconstructs all possible raw data that could have led to reported
    summary statistics. Provides a wrapper for the 'Rust' implementation of the
    'CLOSURE' algorithm.
Tools for clustering individualized survival curves using the
    Partitioning Around Medoids (PAM) algorithm, with monotonic enforcement,
    optional smoothing, weighted distances (L1/L2), automatic K selection via
    silhouette width, prediction for new curves, basic stability checks, and
    plotting helpers. The clustering strategy follows Kaufman and Rousseeuw
    (1990, ISBN:0471878766).
Performs a test for second-order stationarity of time series based
    on unsystematic sub-samples.
Hubbell's Unified Neutral Theory of Biodiversity.
Calculates a Mahalanobis distance for every row of a set of
    outcome variables (Mahalanobis, 1936
    <doi:10.1007/s13171-019-00164-5>). The conditional Mahalanobis
    distance is calculated using a conditional covariance matrix (i.e., a
    covariance matrix of the outcome variables after controlling for a set
    of predictors). Plotting the output of the cond_maha() function can
    help identify which elements of a profile are unusual after
    controlling for the predictors.
Historical voting data of the United Nations General Assembly. This
    includes votes for each country in each roll call, as well as descriptions and
    topic classifications for each vote.
This program realizes a universal estimation approach that accommodates
    multi-category variables and effect scales, making up for the deficiencies
    of the existing approaches when dealing with non-binary exposures and
    complex models. The estimation via bootstrapping can simultaneously provide results of
    causal mediation on risk difference (RD), odds ratio (OR) and risk ratio (RR) scales with tests of the effects' difference.
    The estimation is also applicable to many other settings, e.g., moderated mediation, inconsistent covariates,
    panel data, etc. The high flexibility and compatibility
    make it possible to apply for any type of model, greatly meeting the needs of
    current empirical researches.
We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance not pay attention to the accuracy of prediction, but focus on model selection uncertainty and providing more information of the model selection results. And to estimate the model measures, we propose an simplify and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance focuses on model selection uncertainty and providing more information of the model selection results. To estimate the model uncertainty variance, we propose an simplified and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. Please see Li,Y., Luo,Y., Ferrari,D., Hu,X. and Qin,Y. (2019) Model Confidence Bounds for Variable Selection. Biometrics, 75:392-403.<DOI:10.1111/biom.13024> for more information.
Displays percentage changes by height and absolute changes by area for up to three nested or non-nested levels. The plots visualise changes in indices and markets, showing how the changes for sectors or for individual components contribute to the overall change. Data can be classified by up to three levels of grouping variables in a layered, hierarchical plot. Each level can be ordered in several ways including by baseline, by percentage change, and by absolute change. The vignettes give examples.
Provides an extension to the Partial Credit Model and Generalized Partial Credit Models which allows for an additional person parameter that characterizes the uncertainty of the person. The method was originally proposed by Tutz and Schauberger (2020) <doi:10.1177/0146621620920932>.
When a package is loaded, the source repository is checked for
    new versions and a message is shown in the console indicating whether the
    package is out of date.
When updating major or minor R versions all packages should
    be re-installed. The utilities in this package assist in getting a
    user up-and-running again by installing all previously installed R
    packages. The package uses 'renv' to install; immediately replenishing
    your 'renv' package cache.
Implements empirical Bayes approaches to genotype
       polyploids from next generation sequencing data while
       accounting for allele bias, overdispersion, and sequencing
       error. The main functions are flexdog() and multidog(), 
       which allow the specification
       of many different genotype distributions. Also provided are functions to
       simulate genotypes, rgeno(), and read-counts, rflexdog(), as well as
       functions to calculate oracle genotyping error rates, oracle_mis(), and
       correlation with the true genotypes, oracle_cor(). These latter two
       functions are useful for read depth calculations. Run
       browseVignettes(package = "updog") in R for example usage. See
       Gerard et al. (2018) <doi:10.1534/genetics.118.301468> and
       Gerard and Ferrao (2020) <doi:10.1093/bioinformatics/btz852> for details 
       on the implemented methods.
Provides an algorithm to detect and characterize disturbances (start, end dates, intensity) that can occur at different hierarchical levels by studying the dynamics of longitudinal observations at the unit level and group level based on Nadaraya-Watson's smoothing curves, but also a shiny app which allows to visualize the observations and the detected disturbances. Finally the package provides a dataframe mimicking a pig farming system subsected to disturbances simulated according to Le et al.(2022) <doi:10.1016/j.animal.2022.100496>.
Efficient Bayesian implementations of probit, logit, multinomial logit and binomial logit models. Functions for plotting and tabulating the estimation output are available as well. Estimation is based on Gibbs sampling where the Markov chain Monte Carlo algorithms are based on the latent variable representations and marginal data augmentation algorithms described in "Gregor Zens, Sylvia Frühwirth-Schnatter & Helga Wagner (2023). Ultimate Pólya Gamma Samplers – Efficient MCMC for possibly imbalanced binary and categorical data, Journal of the American Statistical Association <doi:10.1080/01621459.2023.2259030>".
Up-and-Down (UD) is the most popular design approach for dose-finding, but it has been severely under-served by the statistical and computing communities. This is the first package that comprehensively addresses UD's needs. Recent applied UD tutorial: Oron et al., 2022 <doi:10.1097/ALN.0000000000004282>. Recent methodological overview: Oron and Flournoy, 2024 <doi:10.51387/24-NEJSDS74>.
Using matrix layout to visualize the unique, common, or individual contribution of each predictor (or matrix of predictors) towards explained variation on different models. These contributions were derived from variation partitioning (VP) and hierarchical partitioning (HP), applying the algorithm of "Lai et al. (2022) Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.Methods in Ecology and Evolution, 13: 782-788 <doi:10.1111/2041-210X.13800>".
'UpSet.js' is a re-implementation of 'UpSetR' to create interactive set visualizations for more than three sets.
  This is a 'htmlwidget' wrapper around the 'JavaScript' library 'UpSet.js'.
Creates visualizations of intersecting sets using a novel matrix
    design, along with visualizations of several common set, element and attribute
    related tasks (Conway 2017) <doi:10.1093/bioinformatics/btx364>.
The Upsilon test assesses association among
 categorical variables against the null hypothesis of
 independence (Luo 2021 MS thesis; ProQuest Publication
 No. 28649813). While promoting dominant function patterns,
 it demotes non-dominant function patterns. It is robust
 to low expected count---continuity correction
 like Yates's seems unnecessary. Using a common null
 population following a uniform distribution, contingency
 tables are comparable by statistical significance---not
 the case for most association tests defining a varying
 null population by tensor product of observed marginals.
 Although Pearson's chi-squared test, Fisher's exact test,
 and Woolf's G-test (related to mutual information) are
 useful in some contexts, the Upsilon test appeals to
 ranking association patterns not necessarily following
 same marginal distributions, such as in count data
 from DNA and RNA sequencing---a rapidly expanding frontier
 in modern science.
Core functions necessary for using The Globe and Mail's R data journalism template, 'startr', along with utilities for day-to-day data journalism tasks, such as reading and writing files, producing graphics and cleaning up datasets.
Variance approximations for the 
    Horvitz-Thompson total estimator in Unequal Probability Sampling
    using only first-order inclusion probabilities. 
    See Matei and Tillé (2005) and Haziza, Mecatti and Rao (2008) for details.
'Elasticsearch' is an open-source, distributed, document-based datastore
    (<https://www.elastic.co/products/elasticsearch>).
    It provides an 'HTTP' 'API' for querying the database and extracting datasets, but that
    'API' was not designed for common data science workflows like pulling large batches of
    records and normalizing those documents into a data frame that can be used as a training
    dataset for statistical models. 'uptasticsearch' provides an interface for 'Elasticsearch'
    that is explicitly designed to make these data science workflows easy and fun.
Provide a set of wrappers to call all the endpoints of UptimeRobot API
  which includes various kind of ping, keep-alive and speed tests.
  See <https://uptimerobot.com/> for more information.
Provides researchers with a simple set of diagnostic tools for monitoring the progress and reliability of raters conducting content coding tasks. Goehring (2024) <https://bengoehring.github.io/improving-content-analysis-tools-for-working-with-undergraduate-research-assistants.pdf> argues that supervisors---especially supervisors of small teams---should utilize computational tools to monitor reliability in real time. As such, this package provides easy-to-use functions for calculating inter-rater reliability statistics and measuring the reliability of one coder compared to the rest of the team.
Calculate unified measures
  that quantify the effect of a covariate on a binary dependent variable
  (e.g., for meta-analyses).
  This can be particularly important
  if the estimation results are obtained
  with different models/estimators
  (e.g., linear probability model, logit, probit, ...)
  and/or with different transformations of the explanatory variable of interest
  (e.g., linear, quadratic, interval-coded, ...).
  The calculated unified measures are:
  (a) semi-elasticities of linear, quadratic, or interval-coded covariates and
  (b) effects of linear, quadratic, interval-coded, or categorical covariates
  when a linear or quadratic covariate changes between distinct intervals,
  the reference category of a categorical variable
  or the reference interval of an interval-coded variable needs to be changed,
  or some categories of a categorical covariate
  or some intervals of an interval-coded covariate need to be grouped together.
  Approximate standard errors of the unified measures are also calculated.
  All methods that are implemented in this package 
  are described in the 'vignette'  
  "Extracting and Unifying Semi-Elasticities and Effect Sizes
  from Studies with Binary Dependent Variables"
  that is included in this package.
Unit root and cointegration tests encountered in applied 
 econometric analysis are implemented.
Provide the URL checking tools available in R 4.1+ as a
    package for earlier versions of R. Also uses concurrent requests so
    can be much faster than the serial versions.
Offers tools for parsing and analyzing URL datasets,
    extracting key components and identifying common patterns. It aids in 
    examining website architecture and identifying SEO issues, helping users
    optimize web presence and content strategy.
A fast and simple 'URL' parser package for 'R'. This package provides
    functions to parse 'URLs' into their components, such as scheme, user, password, host, port,
    path, query, and fragment.
Allows using two URL shortening services, which also provide
    expanding and analytic functions. Specifically developed for 'Bit.ly' (which requires OAuth 2.0) and 'is.gd' (no API key).
A toolkit for all URL-handling needs, including encoding and decoding,
    parsing, parameter extraction and modification. All functions are
    designed to be both fast and entirely vectorised. It is intended to be
    useful for people dealing with web-related datasets, such as server-side
    logs, although may be useful for other situations involving large sets of
    URLs.
Seasonal unit roots and seasonal stability tests.
    P-values based on response surface regressions are available for both tests.
    P-values based on bootstrap are available for seasonal unit root tests.
Conduct unit root tests based on 'EViews' (<https://eviews.com>) routines and report them in tables. 'EViews' (Econometric Views) is a commercial software for econometrics.
S3 classes and methods for manipulation with georeferenced raster data: reading/writing, processing, multi-panel visualization.
A simple interface to the Geographic Header information
  from the "2010 US Census Summary File 2".  The entire Summary File 2
  is described at
  <https://catalog.data.gov/dataset/census-2000-summary-file-2-sf2>,
  but note that this package only provides access to parts of the
  geographic header ('geoheader') of the file.  In particular, only
  the first 101 columns of the geoheader are included and, more
  importantly, only rows with summary levels (SUMLEVs) 010 through 050
  (nation down through county level) are included.  In addition to
  access to (part of) the geoheader, the package also provides a
  decode function that takes a column name and value and, for certain
  columns, returns "the meaning" of that column (i.e., a "SUMLEV"
  value of 40 means "State"); without a value, the decode function
  attempts to describe the column itself.
Updated versions of the 1970s "US State Facts and Figures"
    objects from the 'datasets' package included with R. The new data is
    compiled from a number of sources, primarily from the United States
    Census Bureau or the relevant federal agency. Modern tidy tibbles
    provide richer state-level data including identifiers, geography,
    capitals, demographics, and socioeconomic statistics. Convenience
    vectors parallel the base 'datasets' state objects but extend coverage
    to all 51 jurisdictions: the 50 states and the District of Columbia.
Contains a WGS84 datum map of the USA, which includes all
    Commonwealth and State boundaries & also includes Puerto Rico and the U.S.
    Virgin Islands. This map is a reprojection of the NAD83 datum map from the
    USGS National Map. This package contains a subset of the data included in
    the 'USA.state.boundaries.data' package, which is available in a 'drat'
    repository. To install that data package, please follow the instructions at
    <https://gitlab.com/iembry/usa.state.boundaries.data>.
The boundaries for geographical units in the United States of
    America contained in this package include state, county, congressional
    district, and zip code tabulation area. Contemporary boundaries are provided
    by the U.S. Census Bureau (public domain). Historical boundaries for the
    years from 1629 to 2000 are provided form the Newberry Library's Atlas of
    Historical County Boundaries (licensed CC BY-NC-SA). Additional  data is
    provided in the USAboundariesData package; this package provides an
    interface to access that data.
Intended to be used by the United States Copyright Office Product Management Division Business Analysts. Include algorithms for the United States Copyright Office Product Management Division SR Audit Data dataset. The algorithm takes in the SR Audit Data excel file and reformat the spreadsheet such that the values and variables fit the format of the online database. Support functions in this package include clean_str(), which cleans instances of variable AUDIT_LOG; clean_data_to_excel(), which cleans and output the reorganized SR Audit Data dataset in excel format; clean_data_to_dataframe(), which cleans and stores the reorganized SR Audit Data data set to a data frame; format_from_excel(), which reads in the outputted excel file from the clean_data_to_excel() function and formats and returns the data as a dictionary that uses FIELD types as keys and NON-FIELD types as the values of those keys. format_from_dataframe(), which reads in the outputted data frame from the clean_data_to_dataframe() function and formats and returns the data as a dictionary that uses FIELD types as keys and NON-FIELD types as the values of those keys; support_function(), which takes in the dictionary outputted either from the format_from_dataframe() or format_from_excel() function and returns the data as a formatted data frame according to the original U.S. Copyright Office SR Audit Data online database. The main function of this package is clean_format_all(), which takes in an excel file and returns the formatted data into a new excel and text file according to the format from the U.S. Copyright Office SR Audit Data online database.
Fetch United States Congressional Records from their API <https://api.govinfo.gov/docs/> such as congressional 
    speeches, speaker names, and metadata about congressional sessions, and detailed granule records. 
    Optional parameters allow users to specify congressional sessions, 
    and the maximum number of speeches to retrieve. Data is parsed, cleaned, and 
    returned in a structured dataframe for analysis.
Interface to easily access data via the United States Department of Agriculture (USDA)'s Livestock Mandatory Reporting ('LMR')
  Data API at <https://mpr.datamart.ams.usda.gov/>. The downloaded data can be saved for later off-line use. 
  Also provide relevant information and metadata for each of the input variables needed for sending the data inquiry.
An alternative for downloading various United States Department of
    Agriculture (USDA) data from <https://quickstats.nass.usda.gov/> through R. 
    You must sign up for an API token from the mentioned website in order for 
    this package to work.
Demographic data on the United States at the county and state levels spanning multiple years.
Provides a diverse collection of U.S. datasets 
    encompassing various fields such as crime, economics, education, finance, energy, healthcare, and more.
    It serves as a valuable resource for researchers and analysts seeking to perform in-depth analyses and derive insights from U.S.-specific data.
This is a framework that aims to provide methods and tools for assessing the impact of different sources of uncertainties (e.g.positional uncertainty) on performance of species distribution models (SDMs).)
Fetch data from the <https://www.justice.gov/developer/api-documentation/api_v1> API such as press releases, blog entries, and speeches. Optional parameters allow users to specify the number of results starting from the earliest or latest entries, and whether these results contain keywords. Data is cleaned for analysis and returned in a dataframe.
Provides functions for uniform sampling of the environmental space, designed to assist species distribution modellers in gathering ecologically relevant pseudo-absence data. The method ensures balanced representation of environmental conditions and helps reduce sampling bias in model calibration. Based on the framework described by Da Re et al. (2023) <doi:10.1111/2041-210X.14209>.
Functions to re-arrange, extract, and work with distances.
Consistent with 'knitr' syntax highlighting, 'usedthese' adds
    a summary table of package & function usage to a Quarto document and
    enables aggregation of usage across a website.
A set of little functions that have been found useful to do little
    odds and ends such as plotting the results of K-means clustering, substituting
    special text characters, viewing parts of a data.frame, constructing formulas
    from text and building design and response matrices.
A set of general functions that I have used in various
    projects and other R packages. Miscellaneous operations on data
    frames, matrices and vectors, ROC and PR statistics.
Code snippets to fit models using the tidymodels framework
    can be easily created for a given data set.
Automate package and project setup tasks that are otherwise
    performed manually. This includes setting up unit testing, test
    coverage, continuous integration, Git, 'GitHub', licenses, 'Rcpp',
    'RStudio' projects, and more.
Provides an overview of the demand for natural gas in the US by state and country level. Data source: US Energy Information Administration <https://www.eia.gov/>.
Provides a set of regular time-series datasets, describing the US electricity grid. That includes the total demand and supply, and as well as the demand by energy source (coal, solar, wind, etc.). Source: US Energy Information Administration (Dec 2019) <https://www.eia.gov/>.
Calculates federal and state income taxes in the United States. It acts as a wrapper 
    to the NBER's TAXSIM 35 (<http://taxsim.nber.org/taxsim35/>) tax simulator. TAXSIM 35 conducts 
    the calculations, while 'usincometaxes' prepares the data for TAXSIM 35, sends the data to 
    TAXSIM 35's server or communicates with the Web Assembly file, retrieves the data, and places it 
    into a data frame. All without the user worrying about this process.
A collection of data sets to accompany the
    textbook "Using R for Introductory Statistics," second
    edition.
Implements mixtures of unrestricted skew-t factor analyzer models via the EM algorithm.
The Universal Scalability Law (Gunther 2007)
    <doi:10.1007/978-3-540-31010-5> is a model to predict hardware and
    software scalability. It uses system capacity as a function of load to
    forecast the scalability for the system.
Obtain United States map data frames of varying region types (e.g. county,
    state). The map data frames include Alaska and Hawaii conveniently placed to the
    bottom left, as they appear in most maps of the US. Convenience functions for plotting
    choropleths, visualizing spatial data, and working with FIPS codes are also provided.
Provides a container for data used by the 'usmap' package.
    The data used by 'usmap' has been extracted into this package so that the
    file size of the 'usmap' package can be reduced greatly. The data in this
    package will be updated roughly once per year as new map data files are
    provided by the US Census Bureau.
Implements various independence tests for discrete, continuous, and infinite-dimensional data. The tests are based on a U-statistic permutation test, the USP of Berrett, Kontoyiannis and Samworth (2020) <arXiv:2001.05513>, and shown to be minimax rate optimal in a wide range of settings. As the permutation principle is used, all tests have exact, non-asymptotic Type I error control at the nominal level.
Centers of population (centroid) data for census areas in the
    United States.
Tools package to extract and analyze data from U SPORTS, the governing body of university sport in Canada.
The "ussher" data set is drawn from original chronological textual historic events. Commonly known as James Ussher's Annals of the World, the source text was originally written in Latin in 1650, and published in English translation in 1658.The data are classified by index, year, epoch (or one of the 7 ancient "Ages of the World"), Biblical source book if referenced (rarely), as well as alternate dating mechanisms, such as "Anno Mundi" (age of the world) or "Julian Period" (dates based upon the Julian calendar). Additional file "usshfull" includes variables that may be of further interest to historians, such as Southern Kingdom and Northern Kingdom discrepant dates, and the original amalgamated dating mechanic used by Ussher in the original text. The raw data can also be called using "usshraw", as described in: Ussher, J. (1658) <https://archive.org/stream/AnnalsOfTheWorld/Annals_djvu.txt>.
A set of functions leading to multivariate response L1 regression. 
    This includes functions on computing Euclidean inner products and norms, 
    weighted least squares estimates on multivariate responses, function to compute 
    fitted values and residuals. This package is a companion to the book "U-Statistics,
    M-estimation and Resampling", by Arup Bose and Snigdhansu Chatterjee, to appear 
    in 2017 as part of the "Texts and Readings in Mathematics" (TRIM) series of 
    Hindustan Book Agency and Springer-Verlag.
Make requests from the US Treasury Fiscal Data API endpoints.
Forms a query to submit for US Treasury yield curve data, posting
    this query to the US Treasury web site's data feed service.  By default the
    download includes data yield data for 12 products from January 1, 1990,
    some of which are NA during this span.  The caller can pass parameters to
    limit the query to a certain year or year and month, but the full download
    is not especially large.  The download data from the service is in XML
    format.  The package's main function transforms that XML data into a numeric 
    data frame with treasury product items (constant maturity yields for 12 kinds 
    of bills, notes, and bonds) as columns and dates as row names. The function 
    returns a list which includes an item for this data frame as well as query-related
    values for reference and the update date from the service.
Three functions are provided: first function changes time from local to UTC, other changes from UTC to local and third returns difference between local and UTC. %h+% operator is also provided it adds hours to a time.
Provides decorators, transformators, and utility functions
    to extend the 'teal' framework for interactive data analysis
    applications. Implements methods for data visualization enhancement,
    statistical data transformations, and workflow integration tools.
    Designed to support clinical and pharmaceutical research workflows
    within the 'teal' ecosystem through modular and reusable components.
An implementation of Lind and Mehlum's (2010) <doi:10.1111/j.1468-0084.2009.00569.x> Utest to test for the presence of a U shaped or inverted U shaped relationship between 
              variables in (generalized) linear models. It also implements a test of upward/downward sloping relationships at the lower and upper 
              boundary of the data range.
Process and print 'UTF-8' encoded international
    text (Unicode). Input, validate, normalize, encode, format, and
    display.
Format text (bold, italic, ...) and numbers using UTF-8. 
    Offers functions to search for emojis and include them in your text.
Functions for building customized ready-to-export tables for publication.
Tools for formatting and summarizing data for outcomes research.
A set of functions to aid in the production of visuals in ggplot2.
Construct and plot objective hierarchies and associated value and utility functions. 
  Evaluate the values and utilities and visualize the results as colored objective hierarchies or tables. 
  Visualize uncertainty by plotting median and quantile intervals within the nodes of objective hierarchies.
  Get numerical results of the evaluations in standard R data types for further processing.
Predicts a smooth and continuous (individual) utility function from utility points, and computes measures of intensity for risk and higher-order risk measures (or any other measure computed with user-written function) based on this utility function and its derivatives according to the method introduced in Schneider (2017) <http://hdl.handle.net/21.11130/00-1735-0000-002E-E306-0>.
The most used functions on IPEA (Instituto de Pesquisa Economica Aplicada). 
             Most of functions deal with brazilian names. 
             It can guess the women single's name, extract prepositions or extract the first name.
An engine for univariate time series forecasting using
    different regression models in an autoregressive way. The engine
    provides an uniform interface for applying the different models. 
    Furthermore, it is extensible so that users can easily apply their
    own regression models to univariate time series forecasting and 
    benefit from all the features of the engine, such as preprocessings
    or estimation of forecast accuracy.
Tools for generating and handling of UUIDs (Universally Unique Identifiers).
Generate, parse, and validate RFC 9562 UUIDs from R using the
    Rust 'uuid' crate via 'extendr'. Developed by Thomas Bryce Kelly at Icy
    Seas Co-Laboratory LLC. Version 7 UUIDs are the default for new
    identifiers, while versions 4, 5, 6, and legacy version 1 are also
    supported. Functions return character vectors by default and can also
    expose 16-byte raw representations for low-level workflows.
Estimate ambient vitamin D-effective or erythemal dose using ultraviolet radiation (UV) data from the 'TEMIS' database, based on date and geographical location.
A tool for checking how much information is disclosed when
    reporting summary statistics.
A method for estimating log-normalizing constants (or free
        energies) and expectations from multiple distributions (such as
        multiple generalized ensembles).
An implementation of the Uniform Manifold Approximation and
    Projection dimensionality reduction by McInnes et al. (2018)
    <doi:10.48550/arXiv.1802.03426>. It also provides means to transform new data and
    to carry out supervised dimensionality reduction. An implementation of
    the related LargeVis method of Tang et al. (2016) <doi:10.48550/arXiv.1602.00370>
    is also provided. This is a complete re-implementation in R (and C++,
    via the 'Rcpp' package): no Python installation is required. See the
    uwot website (<https://github.com/jlmelville/uwot>) for more
    documentation and examples.
Provides convenience functions for user experience research
    with an emphasis on quantitative user experience testing and reporting.
    The functions are designed to translate statistical approaches to 
    applied user experience research.
An R interface to V8 <https://v8.dev>: Google's open source JavaScript
    and WebAssembly engine. This package can be compiled either with V8 or NodeJS 
    when built as a shared library.
Calibrates population-level cause-specific mortality fractions (CSMFs) that are derived using computer-coded verbal autopsy (CCVA) algorithms. Leveraging the data collected in the Child Health and Mortality Prevention Surveillance (CHAMPS;<https://champshealth.org/>) project, the package stores misclassification matrix estimates of three CCVA algorithms (EAVA, InSilicoVA, and InterVA) and two age groups (neonates aged 0-27 days, and children aged 1-59 months) across countries (specific estimates for Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa, and a combined estimate for all other countries), enabling global calibration. These estimates are obtained using the framework proposed in Pramanik et al. (2025;<doi:10.1214/24-AOAS2006>) and are analyzed in Pramanik et al. (2026;<doi:10.1136/bmjgh-2025-021747>). Given VA-only data for an age group, CCVA algorithm, and country, the package utilizes the corresponding misclassification matrix estimate in the modular VA-Calibration framework (Pramanik et al.,2025;<doi:10.1214/24-AOAS2006>) and produces calibrated estimates of CSMFs. The package also supports ensemble calibration to accommodate multiple algorithms. More generally, this allows calibration of population-level prevalence derived from single-class predictions of discrete classifiers. For this, users need to provide fixed or uncertainty-quantified misclassification matrices. This work is supported by the Eunice Kennedy Shriver National Institute of Child Health K99 NIH Pathway to Independence Award (1K99HD114884-01A1), the Bill and Melinda Gates Foundation (INV-034842), and the Johns Hopkins Data Science and AI Institute.
Tools to estimate the impact of vaccination campaigns at population level (number of events averted, number of avertable events, number needed to vaccinate). Inspired by the methodology proposed by Foppa et al. (2015) <doi:10.1016/j.vaccine.2015.02.042> and Machado et al. (2019) <doi:10.2807/1560-7917.ES.2019.24.45.1900268> for influenza vaccination impact.
Various semiparametric and nonparametric statistical tools for
    immune correlates analysis of vaccine clinical trial data. This includes
    calculation of summary statistics and estimation of risk, vaccine efficacy,
    controlled effects (controlled risk and controlled vaccine efficacy), and
    mediation effects (natural direct effect, natural indirect effect,
    proportion mediated). See Gilbert P, Fong Y, Kenny A, and Carone, M (2022)
    <doi:10.1093/biostatistics/kxac024> and Fay MP and Follmann DA (2023)
    <doi:10.48550/arXiv.2208.06465>.
Provides tools for estimating vaccine effectiveness and
    related metrics. The 'vaccineff_data' class manages key features for
    preparing, visualizing, and organizing cohort data, as well as
    estimating vaccine effectiveness. The results and model performance
    are assessed using the 'vaccineff' class.
A method to visualize pharmacometric analyses which are impacted by
    covariate effects. Variability-aligned covariate harmonized-effects
    and time-transformation equivalent ('vachette') facilitates intuitive
    overlays of data and model predictions, allowing for comprehensive
    comparison without dilution effects. 'vachette' improves upon previous
    methods Lommerse et al. (2021) <doi:10.1002/psp4.12679>, enabling its
    application to all pharmacometric models and enhancing Visual Predictive
    Checks (VPC) by integrating data into cohesive plots that can highlight
    model misspecification.
An implementation of three procedures developed by 
    John Tukey: FUNOP (FUll NOrmal Plot), FUNOR-FUNOM 
    (FUll NOrmal Rejection-FUll NOrmal Modification), and vacuum cleaner. 
    Combined, they provide a way to identify, treat, and analyze outliers 
    in two-way (i.e., contingency) tables, as described in his 
    landmark paper "The Future of Data Analysis", Tukey, John W. (1962) 
    <https://www.jstor.org/stable/2237638>.
Non-Domestic VAERS vaccine data for 01/01/2016 - 06/14/2016. If
    you want to explore the full VAERS data for 1990 - Present (data, symptoms,
    and vaccines), then check out the 'vaersND' package from the URL below. The
    URL and BugReports below correspond to the 'vaersND' package, of which
    'vaersNDvax' is a small subset (2016 only). 'vaersND' is not hosted on CRAN
    due to the large size of the data set. To install the Suggested 'vaers' and
    'vaersND' packages, use the following R code:
    'devtools::install_git("https://gitlab.com/iembry/vaers.git",
    build_vignettes = TRUE)' and
    'devtools::install_git("https://gitlab.com/iembry/vaersND.git",
    build_vignettes = TRUE)'. "VAERS is a national vaccine safety
    surveillance program co-sponsored by the US Centers for Disease Control and
    Prevention (CDC) and the US Food and Drug Administration (FDA). VAERS is a
    post-marketing safety surveillance program, collecting information about
    adverse events (possible side effects) that occur after the administration
    of vaccines licensed for use in the United States." For more information
    about the data, visit <https://vaers.hhs.gov/index>. For information about
    vaccination/immunization hazards, visit
    <http://www.questionuniverse.com/rethink.html/#vaccine>.
US VAERS vaccine data for 01/01/2018 - 06/14/2018. If you want to
    explore the full VAERS data for 1990 - Present (data, symptoms, and
    vaccines), then check out the 'vaers' package from the URL below. The URL
    and BugReports below correspond to the 'vaers' package, of which 'vaersvax'
    is a small subset (2018 only). 'vaers' is not hosted on CRAN due to the
    large size of the data set. To install the Suggested 'vaers' and 'vaersND'
    packages, use the following R code:
    'devtools::install_git("<https://gitlab.com/iembry/vaers.git>",
    build_vignettes = TRUE)' and
    'devtools::install_git("<https://gitlab.com/iembry/vaersND.git>",
    build_vignettes = TRUE)'. "The Vaccine Adverse Event Reporting System (VAERS)
    is a national early warning system to detect possible safety problems in
    U.S.-licensed vaccines. VAERS is co-managed by the Centers for Disease Control
    and Prevention (CDC) and the U.S. Food and Drug Administration (FDA)." For
    more information about the data, visit <https://vaers.hhs.gov/>. For
    information about
    vaccination/immunization hazards, visit
    <http://www.questionuniverse.com/rethink.html#vaccine>.
Provides access to the 'Vagalume' API <https://api.vagalume.com.br>. 
    The data extracted is basically lyrics of songs and information about
    artists/bands.
A set of basic tools to transform functions into functions with
    input validation checks, in a manner suitable for both programmatic and
    interactive use.
Provides a robust and reproducible pipeline for extracting,
    cleaning, and analyzing athlete performance data generated by 'VALD'
    'ForceDecks' systems. The package supports batch-oriented data processing
    for large datasets, standardized data transformation workflows, and
    visualization utilities for sports science research and performance
    monitoring. It is designed to facilitate reproducible analysis across
    multiple sports with comprehensive documentation and error handling.
Provides helper functions and wrappers to simplify authentication, 
    data retrieval, and result processing from the 'VALD' 'APIs'. 
    Designed to streamline integration for analysts and researchers working 
    with 'VALD's external 'APIs'.
    For further documentation on integrating with 'VALD' 'APIs', see:
    <https://support.vald.com/hc/en-au/articles/23415335574553-How-to-integrate-with-VALD-APIs>.
    For a step-by-step guide to using this package, see:
    <https://support.vald.com/hc/en-au/articles/48730811824281-A-guide-to-using-the-valdr-R-package>.
Provides a 'shiny' dashboard and plotting utilities to explore and
    report 'VALD ForceDecks' testing data. Includes interactive modules for
    metric exploration, radar charts, longitudinal comparisons, quadrant plots,
    and athlete reports.
Uses large language models to create poems about R packages.
   Currently contains the roses() function to make "roses are red, ..." style 
   poems and the prompt() function to only assemble the prompt without submitting 
   it to the model.
Alternative splicing produces a variety of different protein products from a given gene. 'VALERIE' enables visualisation of alternative splicing events from high-throughput single-cell RNA-sequencing experiments. 'VALERIE' computes percent spliced-in (PSI) values for user-specified genomic coordinates corresponding to alternative splicing events. PSI is the proportion of sequencing reads supporting the included exon/intron as defined by Shiozawa (2018) <doi:10.1038/s41467-018-06063-x>. PSI are inferred from sequencing reads data based on specialised infrastructures for representing and computing annotated genomic ranges by Lawrence (2013) <doi:10.1371/journal.pcbi.1003118>. Computed PSI for each single cell are subsequently presented in the form of a heatmap implemented using the 'pheatmap' package by Kolde (2010) <https://CRAN.R-project.org/package=pheatmap>. Board overview of the mean PSI difference and associated p-values across different user-defined groups of single cells are presented in the form of a line graph using the 'ggplot2' package by Wickham (2007) <https://CRAN.R-project.org/package=ggplot2>.
The Bank of Canada updated their Valet API
             <https://www.bankofcanada.ca/valet/docs>, and no R client
             currently exists. This provides access to all of Valet's endpoints
             and serves responses in wide format easy for researchers to
             handle but also provides tools to access API responses as a list.
An interface between R and the 'Valhalla' API. 'Valhalla' is a
    routing service based on 'OpenStreetMap' data.
    See <https://valhalla.github.io/valhalla/> for more information.
    This package enables the computation of routes, trips, isochrones and
    travel distances matrices (travel time and kilometer distance).
An interface to the 'Valhalla' routing engine’s
    application programming interfaces (APIs) for turn-by-turn routing,
    isochrones, and origin-destination analyses. Also includes several
    user-friendly functions for plotting outputs, and strives to follow
    "tidy" design principles. Please note that this package requires
    access to a running instance of 'Valhalla', which is open source and
    can be downloaded from <https://github.com/valhalla/valhalla>.
Functions for validating the structure and properties of data frames. Answers essential questions about a data set after initial import or modification. What are the unique or missing values? What columns form a primary key? What are the properties of the numeric or categorical columns? What kind of overlap or mapping exists between 2 columns?
Declare data validation rules and data quality indicators;
        confront data with them and analyze or visualize the results.
        The package supports rules that are per-field, in-record,
        cross-record or cross-dataset. Rules can be automatically
        analyzed for rule type and connectivity. Supports checks implied
        by an SDMX DSD file as well. See also Van der Loo
        and De Jonge (2018) <doi:10.1002/9781118897126>, Chapter 6
        and the JSS paper (2021) <doi:10.18637/jss.v097.i10>.
By creating crowd-sourcing tasks that can be easily posted and results retrieved using Amazon's Mechanical Turk (MTurk) API, researchers can use this solution to validate the quality of topics obtained from unsupervised or semi-supervised learning methods, and the relevance of topic labels assigned. This helps ensure that the topic modeling results are accurate and useful for research purposes. See Ying and others (2022) <doi:10.1101/2023.05.02.538599>. For more information, please visit <https://github.com/Triads-Developer/Topic_Model_Validation>.
Generate suggestions for validation rules 
  from a reference data set, which can be used as a starting point for domain specific 
   rules to be checked with package 'validate'.
Rule sets with validation rules may contain redundancies or contradictions. 
  Functions for finding redundancies and problematic rules are provided, 
  given a set a rules formulated with 'validate'.
Given a partition resulting from any clustering algorithm, the implemented tests allow valid post-clustering inference by testing if a given variable significantly separates two of the estimated clusters. 
             Methods are detailed in: Hivert B, Agniel D, Thiebaut R & Hejblum BP (2022). 
             "Post-clustering difference testing: valid inference and practical considerations", <arXiv:2210.13172>.
Deploy, execute, and analyze the results of models hosted on the
  'ValidMind' Platform <https://validmind.ai>. This package interfaces with the
  'Python' Library API in order to allow advanced diagnostics and insight
  into trained models all from an 'R' environment.
Functions for metrics and plots for model evaluation. Based on vectors of observed and predicted values. Method: Kristin Piikki, Johanna Wetterlind, Mats Soderstrom and Bo Stenberg (2021). <doi:10.1111/SUM.12694>.
The algorithm implemented in this package was
    designed to quickly estimates the distribution of the 
    log-rank especially for heavy unbalanced groups. VALORATE 
    estimates the null distribution and the p-value of the 
    log-rank test based on a recent formulation. For a given 
    number of alterations that define the size of survival 
    groups, the estimation involves a weighted sum of 
    distributions that are conditional on a co-occurrence term 
    where mutations and events are both present. The estimation 
    of conditional distributions is quite fast allowing the 
    analysis of large datasets in few minutes 
    <https://bioinformatics.mx/index.php/bioinfo-tools/>.
Historical results for the state of Virginia lottery draw games. Data were downloaded from https://www.valottery.com/.
Read and manipulate genome intervals and signals. Provides
    functionality similar to command-line tool suites within R, enabling
    interactive analysis and visualization of genome-scale data.  Riemondy
    et al. (2017) <doi:10.12688/f1000research.11997.1>.
EQ-5D is a standard instrument (<https://euroqol.org/eq-5d-instruments/>) that measures the quality of life 
    often used in clinical and economic evaluations of health care technologies. Both adult versions of EQ-5D (EQ-5D-3L and EQ-5D-5L)
    contain a descriptive system and visual analog scale. The descriptive system measures the patient's health in 5 dimensions: 
    the 5L versions has 5 levels and 3L version has 3 levels. The descriptive system scores are usually converted to index values 
    using country specific values sets (that incorporates the country preferences). This package allows the calculation of both descriptive system
    scores to the index value scores. The value sets for EQ-5D-3L are from the references mentioned in the website <https://euroqol.org/eq-5d-instruments/eq-5d-3l-about/valuation/>
    The value sets for EQ-5D-3L for a total of 31 countries are used for the valuation (see the user guide for a complete list of references).
    The value sets for EQ-5D-5L are obtained from references mentioned in the <https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/valuation-standard-value-sets/> and other sources.
    The value sets for EQ-5D-5L for a total of 17 countries are used for the valuation (see the user guide for a complete list of references).
    The package can also be used to map 5L scores to 3L index values for 10 countries: Denmark, France, Germany, Japan, Netherlands, Spain, Thailand, UK, USA, and Zimbabwe. 
    The value set and method for mapping are obtained from Van Hout et al (2012) <doi: 10.1016/j.jval.2012.02.008>.
You can easily visualize your 'sf' polygons or data.frame with h3 address.
    While 'leaflet' package is too raw for data analysis, 
    this package can save data analysts' efforts & time with pre-set visualize options.
Provides tools for analyzing the relationship between direct
    prices (based on labor values) and prices of production using Bayesian
    generalized linear models, panel data methods, partial least squares
    regression, canonical correlation analysis, and panel vector
    autoregression. Includes functions for model comparison, out-of-sample
    validation, and structural break detection. Here, methods use raw accounting data with explicit temporal structure, following Gomez Julian (2023) <doi:10.17605/OSF.IO/7J8KF>
    and standard econometric techniques for panel data analysis.
Provides statistical methods for analytical method comparison and 
    validation studies. Implements Bland-Altman analysis for assessing agreement 
    between measurement methods (Bland & Altman (1986) <doi:10.1016/S0140-6736(86)90837-8>), 
    Passing-Bablok regression for non-parametric method comparison 
    (Passing & Bablok (1983) <doi:10.1515/cclm.1983.21.11.709>), and Deming 
    regression accounting for measurement error in both variables 
    (Linnet (1993) <doi:10.1093/clinchem/39.3.424>). Also includes tools for 
    setting quality goals based on biological variation (Fraser & Petersen (1993) 
    <doi:10.1093/clinchem/39.7.1447>) and calculating Six Sigma metrics, 
    precision experiments with variance component analysis, precision
    profiles for functional sensitivity estimation (Kroll & Emancipator (1993) 
    <https://pubmed.ncbi.nlm.nih.gov/8448849/>). Commonly used in clinical 
    laboratory method validation. Provides publication-ready plots and 
    comprehensive statistical summaries.
Contains logic for cell-specific gene set scoring of single cell RNA sequencing data.
Implementation of a Monte Carlo simulation engine for valuing synthetic portfolios of 
    variable annuities, which reflect realistic features of common annuity contracts in practice. 
    It aims to facilitate the development and dissemination of research related to the efficient 
    valuation of a portfolio of large variable annuities. The main valuation methodology was 
    proposed by Gan (2017) <doi:10.1515/demo-2017-0021>.
Wrapper around the 'City of Vancouver' Open Data API <https://opendata.vancouver.ca/api/v2/console> to simplify and standardize access to 'City of Vancouver' open data. 
  Functionality to list the data catalogue and access data and geographic records.
Collection of functions to evaluate presence-absence models. It 
    comprises functions to adjust discrimination statistics for the 
    representativeness effect through case-weighting, along with functions for 
    visualizing the outcomes. Originally outlined in: 
    Jiménez-Valverde (2022) The uniform AUC: dealing with the 
    representativeness effect in presence-absence models. Methods Ecol. Evol, 
    13, 1224-1236.
Provides 'ggplot2'-compatible colour palettes inspired by Vincent van Gogh's paintings. Each palette contains five colours, manually selected by hexadecimal values. Includes tools for assessing colour vision deficiency (CVD) accessibility.
Simplifies functions to conduct univariate, bivariate, and multivariate statistical techniques. Includes functions designed to replicate plots and tables that would result from similar calls in 'SPSS', including hst(), box(), qq(), tab(), cormat(), and residplot(). Also includes simplified formulae, such as mode(), scatter(), p.corr(), ow.anova(), and rm.anova().
Provides low-level access to 'GDAL' functionality.  
  'GDAL' is the 'Geospatial Data Abstraction Library' a translator for raster and vector geospatial data formats 
  that presents a single raster abstract data model and single vector abstract data model to the calling application 
  for all supported formats <https://gdal.org/>. This package is focussed on providing exactly and only what GDAL does, to enable
  developing further tools.
A collection of the functions for estimation, hypothesis testing, prediction for stationary vector autoregressive models.
The spectral characteristics of a bivariate series (Marginal Spectra, Coherency- and Phase-Spectrum) determine whether there is a strong presence of short-, medium-, or long-term fluctuations (components of certain frequencies in the spectral representation of the series) in each one of them.  These are induced by strong peaks of the marginal spectra of each series at the corresponding frequencies. The spectral characteristics also determine how strongly these short-, medium-, or long-term fluctuations of the two series are correlated between the two series. Information on this is provided by the Coherency spectrum at the corresponding frequencies. Finally, certain fluctuations of the two series may be lagged to each other. Information on this is provided by the Phase spectrum at the corresponding frequencies. The idea in this package is to define a VAR (Vector autoregression) model with desired spectral characteristics by specifying a number of polynomials, required to define the VAR. See Ioannidis(2007) <doi:10.1016/j.jspi.2005.12.013>. These are specified via their roots, instead of via their coefficients. This is an idea borrowed from the Time Series Library of R. Dahlhaus, where it is used for defining ARMA models for univariate time series. This way, one may e.g. specify a VAR inducing a strong presence of long-term fluctuations in series 1 and in series 2, which are weakly correlated, but lagged by a number of time units to each other, while short-term fluctuations in series 1 and in series 2, are strongly present only in one of the two series, while they are strongly correlated to each other between the two series. Simulation from such models allows studying the behavior of data-analysis tools, such as estimation of the spectra, under different circumstances, as e.g. peaks in the spectra, generating bias, induced by leakage.
Implementation of the variable banding procedure for modeling local dependence and estimating precision matrices that is introduced in Yu & Bien (2016) and is available at <https://arxiv.org/abs/1604.07451>.
Tool for easy and efficient discretization of continuous and categorical data. 
    The package calculates the most optimal binning of a given explanatory variable with respect to a 
    user-specified target variable. The purpose is to assign a unique Weight-of-Evidence value 
    to each of the calculated binpoints in order to recode the original variable. 
    The package allows users to impose certain restrictions on the functional form on the resulting 
    binning while maximizing the overall information value in the original data. 
    The package is well suited for logistic scoring models where input variables may be subject to 
    restrictions such as linearity by e.g. regulatory authorities. An excellent source describing in 
    detail the development of scorecards, and the role of Weight-of-Evidence coding in credit scoring 
    is (Siddiqi 2006, ISBN: 978–0-471–75451–0). The package utilizes the discrete nature of decision trees and 
    Isotonic Regression to accommodate the trade-off between flexible functional forms and maximum 
    information value.
Fast algorithms for fitting Bayesian variable selection
    models and computing Bayes factors, in which the outcome (or
    response variable) is modeled using a linear regression or a
    logistic regression. The algorithms are based on the variational
    approximations described in "Scalable variational inference for
    Bayesian variable selection in regression, and its accuracy in
    genetic association studies" (P. Carbonetto & M. Stephens, 2012,
    <DOI:10.1214/12-BA703>). This software has been applied to large
    data sets with over a million variables and thousands of samples.
Performs clustering of quantitative variables,
    assuming that clusters lie in low-dimensional subspaces. Segmentation of
    variables, number of clusters and their dimensions are selected based on
    BIC. Candidate models are identified based on many runs of K-means
    algorithm with different random initializations of cluster centers.
Implements the algorithm introduced in Tian, Y., and Safikhani, A. (2024)
    <doi:10.5705/ss.202024.0182>, "Sequential Change Point Detection in High-dimensional 
    Vector Auto-regressive Models". This package provides tools for detecting change points 
    in the transition matrices of VAR models, effectively identifying shifts in temporal 
    and cross-correlations within high-dimensional time series data.
Generation of domain variables, linearization of several non-linear population statistics (the ratio of two totals, weighted income percentile, relative median income ratio, at-risk-of-poverty rate, at-risk-of-poverty threshold, Gini coefficient, gender pay gap, the aggregate replacement ratio, the relative median income ratio, median income below at-risk-of-poverty gap, income quintile share ratio, relative median at-risk-of-poverty gap), computation of regression residuals in case of weight calibration, variance estimation of sample surveys by the ultimate cluster method (Hansen, Hurwitz and Madow, Sample Survey Methods And Theory, vol. I: Methods and Applications; vol. II: Theory. 1953, New York: John Wiley and Sons), variance estimation for longitudinal, cross-sectional measures and measures of change for single and multistage stage cluster sampling designs (Berger, Y. G., 2015, <doi:10.1111/rssa.12116>). Several other precision measures are derived - standard error, the coefficient of variation, the margin of error, confidence interval, design effect.
Generating functions for both optimal and ordinary difference sequences, and the difference-based estimation functions.
Computes Value at risk and expected shortfall, two most popular measures of financial risk, for over one hundred parametric distributions, including all commonly known distributions.  Also computed are the corresponding probability density function and cumulative distribution function. See Chan, Nadarajah and Afuecheta (2015) <doi:10.1080/03610918.2014.944658> for more details.
Error variance estimation in ultrahigh dimensional datasets with four different methods, viz. Refitted cross validation, k-fold refitted cross validation, Bootstrap-refitted cross validation, Ensemble method.
Variables are the fundamental parts of each programming language but handling them efficiently might be frustrating for programmers. This package contains some functions to help user (especially data explorers) to make more sense of their variables and take the most out of variables and hardware resources. These functions are written and crafted since 2014 with years of experience in statistical data analysis on high-dimensional data, and for each of them there was a need. Functions in this package are supposed to be efficient and easy to use, hence they will be frequently updated to make them more convenient.
Performs analysis of various genetic parameters like genotypic and phenotypic coefficient of variance, heritability, genetic advance, genetic advance as a percentage of mean. The package also has functions for genotypic and phenotypic covariance, correlation and path analysis. Dataset has been added to facilitate example. For more information refer Singh, R.K. and Chaudhary, B.D. (1977, ISBN:81766330709788176633079).
Abstract descriptions of (yet) unobserved variables.
Implements variable screening techniques for ultra-high
    dimensional regression settings.  Techniques for independent (iid) data,
    varying-coefficient models, and longitudinal data are implemented. The package
     currently contains three screen functions: screenIID(), screenLD() and screenVCM(),
     and six methods for simulating dataset: simulateDCSIS(), simulateLD, simulateMVSIS(),
     simulateMVSISNY(), simulateSIRS() and simulateVCM(). The package is based on the work of
    Li-Ping ZHU, Lexin LI, Runze LI, and Li-Xing ZHU (2011) <DOI:10.1198/jasa.2011.tm10563>,
    Runze LI, Wei ZHONG, & Liping ZHU (2012) <DOI:10.1080/01621459.2012.695654>,
    Jingyuan LIU, Runze LI, & Rongling WU (2014) <DOI:10.1080/01621459.2013.850086>
    Hengjian CUI, Runze LI, & Wei ZHONG (2015) <DOI:10.1080/01621459.2014.920256>, and
    Wanghuan CHU, Runze LI and Matthew REIMHERR (2016) <DOI:10.1214/16-AOAS912>.
Provides variable selection for linear models and generalized linear models using Bayesian information criterion (BIC) and model posterior probability (MPP). 
             Given a set of candidate predictors, it evaluates candidate models and returns model-level summaries (BIC and MPP) and predictor-level posterior inclusion probabilities (PIP).
             For more details see Xu, S., Ferreira, M. A., & Tegge, A. N. (2025) <doi:10.48550/arXiv.2510.02628>.
Provides functions for the variance gamma
        distribution. Density, distribution and quantile functions.
        Functions for random number generation and fitting of the
        variance gamma to data. Also, functions for computing moments
        of the variance gamma distribution of any order about any
        location. In addition, there are functions for checking the
        validity of parameters and to interchange different sets of
        parameterizations for the variance gamma distribution.
This is a 'sparklyr' extension integrating 'VariantSpark' and R. 'VariantSpark' is 
  a framework based on 'scala' and 'spark' to analyze genome datasets, 
  see <https://bioinformatics.csiro.au/>. It was tested on datasets with 3000 samples 
  each one containing 80 million features in either unsupervised clustering approaches 
  and supervised applications, like classification and regression. The genome datasets
  are usually writing in VCF, a specific text file format used 
  in bioinformatics for storing gene sequence variations. So, 'VariantSpark' is a great 
  tool for genome research, because it is able to read VCF files, run analyses and return 
  the output in a 'spark' data frame.
Enables computationally efficient parameters-estimation by variational Bayesian methods for various diagnostic classification models (DCMs). DCMs are a class of discrete latent variable models for classifying respondents into latent classes that typically represent distinct combinations of skills they possess. Recently, to meet the growing need of large-scale diagnostic measurement in the field of educational, psychological, and psychiatric measurements, variational Bayesian inference has been developed as a computationally efficient alternative to the Markov chain Monte Carlo methods, e.g., Yamaguchi and Okada (2020a) <doi:10.1007/s11336-020-09739-w>, Yamaguchi and Okada (2020b) <doi:10.3102/1076998620911934>, Yamaguchi (2020) <doi:10.1007/s41237-020-00104-w>, Oka and Okada (2023) <doi:10.1007/s11336-022-09884-4>, and Yamaguchi and Martinez (2023) <doi:10.1111/bmsp.12308>. To facilitate their applications, 'variationalDCM' is developed to provide a collection of recently-proposed variational Bayesian estimation methods for various DCMs.
Computes the random forest variable importance (VIMP) for the conditional inference random forest (cforest) of the 'party' package. Includes a function (varImp) that computes the VIMP for arbitrary measures from the 'measures' package. For calculating the VIMP regarding the measures accuracy and AUC two extra functions exist (varImpACC and varImpAUC).
Estimates the predicted 10-year cardiovascular (CVD) risk score (in probability) for civilian women, women military service 
    members and veterans by inputting patient profiles. The proposed women CVD risk score improves the accuracy of the 
    existing American College of Cardiology/American Heart Association CVD risk assessment
    tool in predicting long‐term CVD risk for VA women, particularly in young and racial/ethnic 
    minority women. See the reference: Jeon‐Slaughter, H., Chen, X., Tsai, S., Ramanan, B., & Ebrahimi, R. 
    (2021) <doi:10.1161/JAHA.120.019217>.
Multi-caller variant analysis pipeline for targeted analysis sequencing (TAS) data. Features a modular, automated workflow that can start with raw reads and produces a user-friendly PDF summary and a spreadsheet containing consensus variant information.
A continuous version of the receiver operating characteristics (ROC) curve to assess both classification and continuity performances of biomarkers, diagnostic tests, or risk prediction models.
A new framework of variable selection, which instead of generating artificial covariates such as permutation importance and knockoffs, creates release rules to examine the affect on the response for each covariate where the conditional distribution of the response variable can be arbitrary and unknown.
In order to make it easy to use variance reduction algorithms for any simulation, this framework can help you.
    We propose user friendly and easy to extend framework. Antithetic Variates, Inner Control Variates,
    Outer Control Variates and Importance Sampling algorithms are available in the framework. User can
    write its own simulation function and use the Variance Reduction techniques in this package to
    obtain more efficient simulations. An implementation of Asian Option simulation is already 
    available within the package. See Kemal Dinçer Dingeç & Wolfgang Hörmann (2012) <doi:10.1016/j.ejor.2012.03.046>.
Methods for fitting semi-parametric mean and variance models, with normal or censored data. Extended to allow a regression in the location, scale and shape parameters, and further for multiple regression in each.
Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance decomposition and impulse response functions of VAR models and estimation of SVAR and SVEC models.
Feature selection using Sequential Forward Floating feature Selection and Jeffries-Matusita distance. It returns a suboptimal set of features to use for image classification. Reference: Dalponte, M., Oerka, H.O., Gobakken, T., Gianelle, D. & Naesset, E. (2013). Tree Species Classification in Boreal Forests With Hyperspectral Data. IEEE Transactions on Geoscience and Remote Sensing, 51, 2632-2645, <DOI:10.1109/TGRS.2012.2216272>.
Utilizes multiple variable selection methods to estimate Average Treatment Effect.
Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here <doi:10.1007/s11222-016-9670-1>). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.
Variable selection from random forests using both
        backwards variable elimination (for the selection of small sets
        of non-redundant variables) and selection based on the
        importance spectrum (somewhat similar to scree plots; for the
        selection of large, potentially highly-correlated variables).
        Main applications in high-dimensional data (e.g., microarray
        data, and other genomics and proteomics applications).
Vector autoregressive (VAR) model is a fundamental and effective approach
    for multivariate time series analysis. Shrinkage estimation methods can be
    applied to high-dimensional VAR models with dimensionality greater than
    the number of observations, contrary to the standard ordinary least squares
    method. This package is an integrative package delivering nonparametric,
    parametric, and semiparametric methods in a unified and consistent manner,
    such as the multivariate ridge regression in Golub, Heath, and Wahba (1979)
    <doi:10.2307/1268518>, a James-Stein type nonparametric shrinkage method in
    Opgen-Rhein and Strimmer (2007) <doi:10.1186/1471-2105-8-S2-S3>, and
    Bayesian estimation methods using noninformative and informative priors
    in Lee, Choi, and S.-H. Kim (2016) <doi:10.1016/j.csda.2016.03.007> and
    Ni and Sun (2005) <doi:10.1198/073500104000000622>.
Performs 18 omnibus tests yielding a total of 28 distinct methodological variations for testing the composite hypothesis of variance homogeneity.
An implementation of the Likelihood ratio Test (LRT) for testing that,
    in a (non)linear mixed effects model, the variances of a subset of the random
    effects are equal to zero. There is no restriction on the subset of variances
    that can be tested: for example, it is possible to test that all the variances
    are equal to zero. Note that the implemented test is asymptotic.
    This package should be used on model fits from packages 'nlme', 'lmer', and 'saemix'.
    Charlotte Baey and Estelle Kuhn (2019) <doi:10.18637/jss.v107.i06>.
Implements wild bootstrap tests for autocorrelation in Vector
    Autoregressive (VAR) models based on Ahlgren and Catani (2016)
    <doi:10.1007/s00362-016-0744-0>, a combined Lagrange Multiplier (LM)
    test for Autoregressive Conditional Heteroskedasticity (ARCH) in VAR
    models from Catani and Ahlgren (2016) <doi:10.1016/j.ecosta.2016.10.006>,
    and bootstrap-based methods for determining the cointegration rank from
    Cavaliere, Rahbek, and Taylor (2012) <doi:10.3982/ECTA9099> and
    Cavaliere, Rahbek, and Taylor (2014) <doi:10.1080/07474938.2013.825175>.
Implements a maximum likelihood estimation (MLE) method for
    estimation and prediction of Gaussian process-based spatially varying
    coefficient (SVC) models (Dambon et al. (2021a)
    <doi:10.1016/j.spasta.2020.100470>).  Covariance tapering (Furrer et
    al. (2006) <doi:10.1198/106186006X132178>) can be applied such that
    the method scales to large data. Further, it implements a joint
    variable selection of the fixed and random effects (Dambon et al.
    (2021b) <doi:10.1080/13658816.2022.2097684>). The package and its 
    capabilities are described in (Dambon et al. (2021c)
    <doi:10.48550/arXiv.2106.02364>).
Provide a collection of miscellaneous R functions
    related to the Vasicek distribution with the intent to make
    the lives of risk modelers easier.
Fits the extended Vasicek single-factor credit loss model where
    the probability of default depends on macroeconomic covariates. Maximum
    likelihood estimates of all parameters, including asset value correlation,
    are obtained via closed-form probit-transformed OLS regression; see
    Mayorov (2026) <doi:10.2139/ssrn.6506378> for derivation.
Provides probability density, cumulative distribution,
    quantile, and random number generation functions for the Vasicek
    distribution. In addition, two functions are available for fitting
    Generalized Additive Models for Location, Scale and Shape introduced
    by Rigby and Stasinopoulos (2005,
    <doi:10.1111/j.1467-9876.2005.00510.x>). Some functions are written in
    'C++' using 'Rcpp', developed by Eddelbuettel and Francois (2011,
    <doi:10.18637/jss.v040.i08>).
Provides raster grid logic, operations that describe a discretized
 rectangular domain and do not require access to materialized data. Grids are
 arrays with dimension and extent, and many operations are functions of dimension
 only: number of columns, number of rows, or they are a combination of the
 dimension and the extent the range in x and the range in y in that order. Here
 we provide direct access to this logic without need for connection to any
 materialized data or formats. Grid logic includes functions that relate the cell
 index to row and column, or row and column to cell index, row, column or cell
 index to position. These methods are described in Loudon, TV, Wheeler, JF,
 Andrew, KP (1980)  <doi:10.1016/0098-3004(80)90015-1>, and implementations were
 in part derived from Hijmans R (2024) <doi:10.32614/CRAN.package.terra>.
An R client for the 'vatcheckapi.com' VAT number validation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://vatcheckapi.com/docs> .
Provides an interface to a 'HashiCorp' vault server over
  its http API (typically these are self-hosted; see
  <https://www.vaultproject.io>).  This allows for secure storage and
  retrieval of secrets over a network, such as tokens, passwords and
  certificates.  Authentication with vault is supported through
  several backends including user name/password and authentication via
  'GitHub'.
Provides tools to analyze vaccine coverage data and simulate potential disease outbreak scenarios. It allows users to calculate key epidemiological metrics such as the effective reproduction number (Re), outbreak probabilities, and expected infection counts based on county-level vaccination rates, disease characteristics, and vaccine effectiveness. The package includes historical kindergarten vaccination data for Florida counties and offers functions for generating summary tables, visualizations, and exporting the underlying plot data.
Estimate vaccine efficacy (VE) using immunogenicity data.
    The inclusion of immunogenicity data in regression models can increase precision in VE. 
    The methods are described in the publications "Elucidating vaccine efficacy using a correlate of protection, demographics, and logistic regression" and "Improving precision of vaccine efficacy evaluation using immune correlate data in time-to-event models" by Julie Dudasova, Zdenek Valenta, and Jeffrey R. Sachs (2024).
Position adjustments for 'ggplot2' to implement "visualize as
    you randomize" principles, which can be especially useful when
    plotting experimental data.
Provides tools for analysis blinding in confirmatory research contexts
  by masking and scrambling test-relevant aspects of data. Vector-, data frame-, and
  row-wise operations support blinding for hierarchical and repeated-measures designs.
  For more details see MacCoun and Perlmutter (2015) <doi:10.1038/526187a> and
  Dutilh, Sarafoglou, and Wagenmakers (2019) <doi:10.1007/s11229-019-02456-7>.
Computes the Gaussian variational approximation of the Bayesian 
    empirical likelihood posterior. This is an implementation of the function 
    found in Yu, W., & Bondell, H. D. (2023) <doi:10.1080/01621459.2023.2169701>.
Fit and simulate latent position and cluster models for network data, using a fast Variational Bayes approximation developed in Salter-Townshend and Murphy (2013) <doi:10.1016/j.csda.2012.08.004>.
A Variational Bayesian algorithm for high-dimensional multi-source 
    heterogeneous linear models. More details have been written up in a paper 
    submitted to the journal Statistics in Medicine, and the details of variational
    Bayesian methods can be found in Ray and Szabo (2021) <doi:10.1080/01621459.2020.1847121>.
    It simultaneously performs parameter estimation and variable selection. The 
    algorithm supports two model settings: (1) local models, where variable selection
    is only applied to homogeneous coefficients, and (2) global models, where variable
    selection is also performed on heterogeneous coefficients. Two forms of 
    Spike-and-Slab priors are available: the Laplace distribution and the Gaussian 
    distribution as the Slab component.
Identification of Latent Patient Phenotype from Electronic Health Records (EHR) Data using Variational Bayes Gaussian Mixture Model for Latent Class Analysis and Variational Bayes regression for Biomarker level shifts, both implemented by Coordinate Ascent Variational Inference algorithms.  Variational methods are used to enable Bayesian analysis of very large Electronic Health Records data. For VB GMM details see Bishop (2006,ISBN:9780-387-31073-2). For Logistic VB see Jaakkola and Jordan (2000) <doi:10.1023/A:1008932416310>. Please see preprint of JSS-submitted paper <doi:10.48550/arXiv.2512.14272>.
Add publication-quality custom legends with vertical brackets. Designed for displaying statistical comparisons between groups,
    commonly used in scientific publications for showing significance levels.
    Features include adaptive positioning, automatic bracket spacing for overlapping
    comparisons, font family inheritance, and support for asterisks, p-values,
    or custom labels. Compatible with 'ggplot2' graphics.
Contains functions for a variational Bayesian method for sparse PCA proposed by Ning (2020) <arXiv:2102.00305>. There are two algorithms: the PX-CAVI algorithm (if assuming the loadings matrix is jointly row-sparse) and the batch PX-CAVI algorithm (if without this assumption). The outputs of the main function, VBsparsePCA(), include the mean and covariance of the loadings matrix, the score functions, the variable selection results, and the estimated variance of the random noise.
Time series decomposition for univariate time series using the
    "Verallgemeinerte Berliner Verfahren" (Generalized Berlin Method) as
    described in 'Kontinuierliche Messgrößen und Stichprobenstrategien in
    Raum und Zeit mit Anwendungen in den Natur-, Umwelt-, Wirtschafts-
    und Finanzwissenschaften', by
    Hebbel and Steuer, Springer Berlin Heidelberg, 2022
    <doi:10.1007/978-3-662-65638-9>, or
    'Decomposition of Time Series using the Generalised Berlin 
    Method (VBV)' by Hebbel and Steuer, in Jan Beran, Yuanhua Feng, Hartmut
    Hebbel (Eds.): Empirical Economic and Financial Research - Theory,
    Methods and Practice, Festschrift in Honour of Prof. Siegfried Heiler.
    Series: Advanced Studies in Theoretical and Applied Econometrics.
    Springer 2014, p. 9-40.
Provides new classes for (rotated) BB1, BB6, BB7, BB8, and 
  Tawn copulas, extends the existing Gumbel and Clayton families with 
  rotations, and allows to set up a vine copula model using the 'copula' API.
  Corresponding objects from the 'VineCopula' API can easily be converted.
ANOVA and REML estimation of linear mixed models is implemented, once following
 Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package.
 The primary objective of this package is to perform a variance component analysis (VCA)
 according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement
 Procedures" (2014). There are plotting methods for visualization of an experimental design,
 plotting random effects and residuals. For ANOVA type estimation two methods for computing
 ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of 
 variance components can be derived, which is used in estimating confidence intervals. Linear
 hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific
 values of covariables and with custom weighting schemes for factor variables. See ?VCA for a
 more comprehensive description of the features.
Fits linear varying coefficient (VC) models, which assert a linear relationship between an outcome and several covariates but allow that relationship (i.e., the coefficients or slopes in the linear regression) to change as functions of additional variables known as effect modifiers, by approximating the coefficient functions with Bayesian Additive Regression Trees. Implements a Metropolis-within-Gibbs sampler to simulate draws from the posterior over coefficient function evaluations. VC models with independent observations or repeated observations can be fit. For more details see Deshpande et al. (2026) <doi:10.1214/24-BA1470>.
Implements the Vine Copula Change Point (VCCP) methodology for the estimation of the number and location of multiple change points in the vine copula structure of multivariate time series. The method uses vine copulas, various state-of-the-art segmentation methods to identify multiple change points, and a likelihood ratio test or the stationary bootstrap for inference. The vine copulas allow for various forms of dependence between time series including tail, symmetric and asymmetric dependence. The functions have been extensively tested on simulated multivariate time series data and fMRI data. For details on the VCCP methodology, please see Xiong & Cribben (2021).
Visualization techniques, data sets, summary and inference
        procedures aimed particularly at categorical data. Special
        emphasis is given to highly extensible grid graphics. The
        package was package was originally inspired by the book 
	"Visualizing Categorical Data" by Michael Friendly and is 
	now the main support package for a new book, 
	"Discrete Data Analysis with R" by Michael Friendly and 
	David Meyer (2015).
Provides the 'vcd2df' function, which loads a IEEE 1364-1995/2001
    VCD (.vcd) file, specified as a parameter of type string containing exactly
    a file path, and returns an R dataframe containing values over time.  
    A VCD file captures the register values at discrete timepoints from a 
    simulated trace of execution of a hardware design in Verilog or VHDL.
    The returned dataframe contains a row for each register, by name, and a
    column for each time point, specified VCD-style using octothorpe-prefixed 
    multiples of the timescale as strings. 
    The only non-trivial implementation details are that (1) VCD 'x' and 'z' 
    non-numerical values are encoded as negative value -1 (as otherwise all bit
    values are positive) and (2) registers with repeated names in distinct 
    modules are ignored, rather than duplicated, as we anticipate these 
    registers to have the same values.
    Read more in arXiv preprint: 'vcd2df' -- Leveraging Data Science Insights 
    for Hardware Security Research <doi:10.48550/arXiv.2505.06470>.
Provides additional data sets, methods and documentation to complement the 'vcd' package for Visualizing Categorical Data
    and the 'gnm' package for Generalized Nonlinear Models.
	In particular, 'vcdExtra' extends mosaic, assoc and sieve plots from 'vcd' to handle 'glm()' and 'gnm()' models and
	adds a 3D version in 'mosaic3d'.  Additionally, methods are provided for comparing and visualizing lists of
	'glm' and 'loglm' objects. This package is now a support package for the book, "Discrete Data Analysis with R" by
  Michael Friendly and David Meyer.
Streams and parses variant call format file headers without reading full files. Provides structured metadata, validation, inference, and HTML reporting. For details on the specifications used see Danecek et al. (2021) <doi:10.1093/gigascience/giab008>.
The 'vcfpp.h' (<https://github.com/Zilong-Li/vcfpp>) provides an easy-to-use 'C++' 'API' of 'htslib', offering full functionality for manipulating Variant Call Format (VCF) files. The 'vcfppR' package serves as the R bindings of the 'vcfpp.h' library, enabling rapid processing of both compressed and uncompressed VCF files. Explore a range of powerful features for efficient VCF data manipulation.
Facilitates easy manipulation of variant call format (VCF) data.
    Functions are provided to rapidly read from and write to VCF files. Once
    VCF data is read into R a parser function extracts matrices of data. This
    information can then be used for quality control or other purposes. Additional
    functions provide visualization of genomic data. Once processing is complete
    data may be written to a VCF file (*.vcf.gz). It also may be converted into
    other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between
    VCF data and familiar R software.
Provides an 'htmlwidgets' interface to 'VChart.js'. 
      'VChart', more than just a cross-platform charting library, but also an expressive data storyteller.
      'VChart' examples and documentation are available here: <https://www.visactor.io/vchart>.
Implements functions for varying coefficient meta-analysis methods. 
  These methods do not assume effect size homogeneity. Subgroup effect size 
  comparisons, general linear effect size contrasts, and linear models of 
  effect sizes based on varying coefficient methods can be used to describe 
  effect size heterogeneity. Varying coefficient meta-analysis methods do not 
  require the unrealistic assumptions of the traditional fixed-effect and 
  random-effects meta-analysis methods. For details see: 
  Statistical Methods for Psychologists, Volume 5, <https://dgbonett.sites.ucsc.edu/>.
Methods for faster extraction (about 5x faster in a few test cases) of variance-covariance matrices and standard errors from models. Methods in the 'stats' package tend to rely on the summary method, which may waste time computing other summary statistics which are summarily ignored.
Estimating the disparity between two groups based on the extended model of the Peters-Belson (PB) method. Our model is the first work on the longitudinal data, and also can set a varying variable to find the complicated association between other variables and the varying variable. Our work is an extension of the Peters-Belson method which was originally published in Peters (1941)<doi:10.1080/00220671.1941.10881036> and Belson (1956)<doi:10.2307/2985420>.
Method to perform penalized variance component analysis.
Record test suite 'HTTP' requests and replays them during
    future runs. A port of the Ruby gem of the same name
    (<https://github.com/vcr/vcr/>). Works by recording real 'HTTP'
    requests/responses on disk in 'cassettes', and then replaying
    matching responses on subsequent requests.
Recursive partitioning for varying coefficient generalized linear models and ordinal linear mixed models. Special features are coefficient-wise partitioning, non-varying coefficients and partitioning of time-varying variables in longitudinal regression. A description of a part of this package was published by Burgin and Ritschard (2017) <doi:10.18637/jss.v080.i06>.
Defines new notions of prototype and size that are used to
    provide tools for consistent and well-founded type-coercion and
    size-recycling, and are in turn connected to ideas of type- and
    size-stability useful for analysing function interfaces.
A way of visualizing collections of time series and, optionally
    their future values, forecasts for their future values and prediction
    intervals for the forecasts. A web-based GUI can be used to display the
    information in a collection of time series.
Comparison of variance - covariance patterns using relative principal component analysis (relative eigenanalysis), as described in Le Maitre and Mitteroecker (2019) <doi:10.1111/2041-210X.13253>. Also provides functions to compute group covariance matrices, distance matrices, and perform proportionality tests. A worked sample on the body shape of cichlid fishes is included, based on the dataset from Kerschbaumer et al. (2013) <doi:10.5061/dryad.fc02f>.
Analyze Peptide Array Data and characterize peptide
    sequence space. Allows for high level visualization of global signal, Quality control based
    on replicate correlation and/or relative Kd, calculation of peptide Length/Charge/Kd parameters,
    Hits selection based on RFU Signal, and amino acid composition/basic motif recognition with RFU
    signal weighting. Basic signal trends can be used to generate peptides that follow the observed
    compositional trends.
The qda() function from package 'MASS' is extended to calculate a weighted linear (LDA) and quadratic discriminant analysis (QDA) by changing the group variances and group means based on cell-wise uncertainties.
    The uncertainties can be derived e.g. through relative errors for each individual measurement (cell), not only row-wise or column-wise uncertainties.
    The method can be applied compositional data (e.g. portions of substances, concentrations) and non-compositional data.
An extension to the 'testthat' package that makes it easy to
    add graphical unit tests. It provides a Shiny application to manage
    the test cases.
To ease the visualization of outputs from Diversity Motif Analyser ('DiMA';
    <https://github.com/BVU-BILSAB/DiMA>). 'vDiveR' allows visualization of the diversity 
    motifs (index and its variants – major, minor and unique) for elucidation of 
    the underlying inherent dynamics. Please refer <https://vdiver-manual.readthedocs.io/en/latest/>
    for more information.
Contains variable, diversity, and joining sequences and accompanying functions that enable both the extraction of and comparison between immune V-D-J genomic segments from a variety of species. Sources include IMGT from MP Lefranc (2009) <doi:10.1093/nar/gkn838> and Vgenerepertoire from publication DN Olivieri (2014) <doi:10.1007/s00251-014-0784-3>.
Comprehensive set of tools for analyzing and manipulating functional
 data with non-uniform lengths. This package addresses two common scenarios in
 functional data analysis: Variable Domain Data, where the observation domain
 differs across samples, and Partially Observed Data, where observations are
 incomplete over the domain of interest. 'VDPO' enhances the flexibility and
 applicability of functional data analysis in 'R'.
 See Amaro et al. (2024) <doi:10.48550/arXiv.2401.05839>.
Although model selection is ubiquitous in scientific discovery, the stability and uncertainty of the selected model is often hard to evaluate. How to characterize the random behavior of the model selection procedure is the key to understand and quantify the model selection uncertainty. This R package offers several graphical tools to visualize the distribution of the selected model. For example, Gplot(), Hplot(), VDSM_scatterplot() and VDSM_heatmap(). To the best of our knowledge, this is the first attempt to visualize such a distribution. About what distribution of selected model is and how it work please see Qin,Y.and Wang,L. (2021) "Visualization of Model Selection Uncertainty" <https://homepages.uc.edu/~qinyn/VDSM/VDSM.html>.
Provides statistical methods for the design and analysis of a calibration study, which aims for calibrating measurements using two different methods. The package includes sample size calculation, sample selection,  regression analysis with error-in measurements and change-point regression. The method is described in Tian, Durazo-Arvizu, Myers, et al. (2014) <DOI:10.1002/sim.6235>.
Applies affine and similarity transformations on vector spatial data (sp objects). Transformations can be defined from control points or directly from parameters. If redundant control points are provided Least Squares is applied allowing to obtain residuals and RMSE.
Under a different representation of the multivariate normal (MVN) probability, we can use the Vecchia approximation to sample the integrand at a linear complexity with respect to n. Additionally, both the SOV algorithm from Genz (92) and the exponential-tilting method from Botev (2017) can be adapted to linear complexity. The reference for the method implemented in this package is Jian Cao and Matthias Katzfuss (2024) "Linear-Cost Vecchia Approximation of Multivariate Normal Probabilities" <doi:10.48550/arXiv.2311.09426>. Two major references for the development of our method are Alan Genz (1992) "Numerical Computation of Multivariate Normal Probabilities" <doi:10.1080/10618600.1992.10477010> and Z. I. Botev (2017) "The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting" <doi:10.48550/arXiv.1603.04166>.
Provides functions for estimation (parametric, semi-parametric and non-parametric)
             of copula-based dependence coefficients between a finite collection of random vectors,
             including phi-dependence measures and Bures-Wasserstein dependence measures. 
             An algorithm for agglomerative hierarchical variable clustering is also implemented.
             Following the articles De Keyser & Gijbels (2024) <doi:10.1016/j.jmva.2024.105336>,
             De Keyser & Gijbels (2024) <doi:10.1016/j.ijar.2023.109090>, and De Keyser & Gijbels (2024)
             <doi:10.48550/arXiv.2404.07141>.
Implements the Vector Matching algorithm to match multiple
    treatment groups based on previously estimated generalized propensity
    scores. The package includes tools for visualizing initial confounder
    imbalances, estimating treatment assignment probabilities using various
    methods, defining the common support region, performing matching across
    multiple groups, and evaluating matching quality. For more details, see 
    Lopez and Gutman (2017) <doi:10.1214/17-STS612>.
The 'base'  tools  union() intersect(), etc.,  follow the algebraic definition
 that each element of a set must be unique. 
 Since it's often helpful to compare all elements of two vectors,
 this toolset treats every element as unique for counting purposes.
 For ease of use, all functions in vecsets have an argument
 'multiple' which, when set to FALSE,
 reverts them to the base::sets (alias for all the items) tools functionality.
A tool for fast, efficient bitwise operations along the
    elements within a vector. Provides such functionality for AND, OR and
    XOR, as well as infix operators for all of the binary bitwise
    operations.
Facilitate the analysis of inter-limb and intra-limb coordination in human movement. 
  It provides functions for calculating the phase angle between two segments, enabling researchers and practitioners to quantify the coordination patterns within and between limbs during various motor tasks.
  Needham, R., Naemi, R., & Chockalingam, N. (2014) <doi:10.1016/j.jbiomech.2013.12.032>.
  Needham, R., Naemi, R., & Chockalingam, N. (2015) <doi:10.1016/j.jbiomech.2015.07.023>.
  Tepavac, D., & Field-Fote, E. C. (2001) <doi:10.1123/jab.17.3.259>.
  Park, J.H., Lee, H., Cho, Js. et al. (2021) <doi:10.1038/s41598-020-80237-w>.
Machine learning utilities for fast vectorized model training.
    Methods are based on standard statistical learning references such as
    Hastie et al. (2009) <doi:10.1007/978-0-387-84858-7>.
Provides pedagogical tools for visualization and numerical computation in vector calculus. Includes functions for parametric curves, scalar and vector fields, gradients, divergences, curls, line and surface integrals, and dynamic 2D/3D graphical analysis to support teaching and learning. The implemented methods follow standard treatments in vector calculus and multivariable analysis as presented in Marsden and Tromba (2011) <ISBN:9781429215084>, Stewart (2015) <ISBN:9781285741550>, Thomas, Weir and Hass (2018) <ISBN:9780134438986>, Larson and Edwards (2016) <ISBN:9781285255869>, Apostol (1969) <ISBN:9780471000051>, Spivak (1971) <ISBN:9780805390216>, Schey (2005) <ISBN:9780071369080>, Colley (2019) <ISBN:9780321982384>, Lizarazo Osorio (2020) <ISBN:9789585450103>, Sievert (2020) <ISBN:9780367180165>, and Borowko (2013) <ISBN:9781439870791>.
Allows registered 'VectorSurv' <https://vectorsurv.org/> users access to data through the 'VectorSurv API' <https://api.vectorsurv.org/>. Additionally provides functions for analysis and visualization.
New wavelet methodology (vector wavelet coherence) (Oygur, T., Unal, G, 2020 <doi:10.1007/s40435-020-00706-y>) 
  to handle dynamic co-movements of multivariate time series via extending multiple and quadruple wavelet coherence methodologies. 
  This package can be used to perform multiple wavelet coherence, quadruple wavelet coherence, and n-dimensional vector wavelet coherence analyses.
A minimal columnar query engine with lazy execution on datasets
    larger than RAM. Provides 'dplyr'-like verbs (filter(), select(), mutate(),
    group_by(), summarise(), joins, window functions) and common aggregations
    (n(), sum(), mean(), min(), max(), sd(), first(), last()) backed by a
    pure C11 pull-based execution engine and a custom on-disk format ('.vtr').
    Reads and writes 'GeoTIFF' (including tiled and 'BigTIFF' layouts) and a
    tiled raster format ('.vec') with overview pyramids and time cubes for
    larger-than-RAM raster data.
A lightweight vector database for text retrieval in R with embedded
    machine learning models and no external API (Application Programming
    Interface) keys. Supports dense and hybrid search, optional HNSW
    (Hierarchical Navigable Small World) approximate nearest-neighbor indexing,
    faceted filters with ACL (Access Control List) metadata, command-line
    tools, and a local dashboard built with 'shiny'. The HNSW method is
    described by Malkov and Yashunin (2018) <doi:10.1109/TPAMI.2018.2889473>.
Mixed type vectors are useful for combining semantically similar 
  classes. Some examples of semantically related classes include time across 
  different granularities (e.g. daily, monthly, annual) and probability 
  distributions (e.g. Normal, Uniform, Poisson). These groups of vector types 
  typically share common statistical operations which vary in results with the 
  attributes of each vector. The 'vecvec' data structure facilitates efficient 
  storage and computation across multiple vectors within the same object.
Provides platform for Vedic calendar system having several
    functionalities to facilitate conversion between Gregorian and Vedic
    calendar systems, and helpful in examining its impact in the
    time series analysis domain.
Implements the Variable importance Explainable Elastic Shape Analysis pipeline for explainable machine learning with functional data inputs. Converts training and testing data functional inputs to elastic shape analysis principal components that account for vertical and/or horizontal variability. Computes feature importance to identify important principal components and visualizes variability captured by functional principal components. See Goode et al. (2025) <doi:10.48550/arXiv.2501.07602> for technical details about the methodology.
The 'Vega-Lite' 'JavaScript' framework provides a higher-level grammar
    for visual analysis, akin to 'ggplot' or 'Tableau', that generates complete 'Vega'
    specifications. Functions exist which enable building a valid 'spec' from scratch
    or importing a previously created 'spec' file. Functions also exist to export 'spec'
    files and to generate code which will enable plots to be embedded in properly
    configured web pages. The default behavior is to generate an 'htmlwidget'.
Ordination methods, diversity analysis and other
  functions for community and vegetation ecologists.
Static and dynamic 3D plots to be used with ordination
    results and in diversity analysis, especially with the vegan package.
'Vega' and 'Vega-Lite' parse text in 'JSON' notation to render 
  chart-specifications into 'HTML'. This package is used to facilitate the 
  rendering. It also provides a means to interact with signals, events,
  and datasets in a 'Vega' chart using 'JavaScript' or 'Shiny'.
A set of functions to: (1) perform fuzzy clustering of vegetation data (De Caceres et al, 2010) <doi:10.1111/j.1654-1103.2010.01211.x>; (2) to assess ecological community similarity on the basis of structure and composition (De Caceres et al, 2013) <doi:10.1111/2041-210X.12116>.
Provides retail and wholesale vegetable price data from two major market hubs in Sri Lanka, Dambulla and Pettah. Includes tools for analyzing, visualizing, and comparing vegetable prices across markets.
It provides a comprehensive toolkit for calculating a suite of common vegetation indices (VIs) derived from remote sensing imagery. VIs are essential tools used to quantify vegetation characteristics, such as biomass, leaf area index (LAI) and photosynthetic activity, which are essential parameters in various ecological, agricultural, and environmental studies. Applications of this package include biomass estimation, crop monitoring, forest management, land use and land cover change analysis and climate change studies. For method details see, Deb,D.,Deb,S.,Chakraborty,D.,Singh,J.P.,Singh,A.K.,Dutta,P.and Choudhury,A.(2020)<doi:10.1080/10106049.2020.1756461>. Utilizing this R package, users can effectively extract and analyze critical information from remote sensing imagery, enhancing their comprehension of vegetation dynamics and their importance in global ecosystems. The package includes the function vegetation_indices().
Collection of common methods to determine growing season length in
  a simple manner. Start and end dates of the vegetation periods are calculated
  solely based on daily mean temperatures and the day of the year.
Earth system dynamics, such as plant dynamics, water bodies, and fire regimes, are widely monitored using spectral indicators obtained from multispectral remote sensing products. There is a great need for spectral index catalogues and computing tools as a result of the quick rise of suggested spectral indices. Unfortunately, the majority of these resources lack a standard Application Programming Interface, are out-of-date, closed-source, or are not linked to a catalogue. We now introduce 'VegSpecIndex', a standardised list of spectral indices for studies of the earth system. A thorough inventory of spectral indices is offered by 'VegSpecIndex' and is connected to an R library. For every spectral index, 'VegSpecIndex' provides a comprehensive collection of information, such as names, formulae, and source references. The user community may add more items to the catalogue, which will keep 'VegSpecIndex' up to date and allow for further scientific uses. Additionally, the R library makes it possible to apply the catalogue to actual data, which makes it easier to employ remote sensing resources effectively across a variety of Earth system domains.
Elaboration of vehicular emissions inventories,
    consisting in four stages, pre-processing activity data, preparing 
    emissions factors, estimating the emissions and post-processing of emissions 
    in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>.
    Before using VEIN you need to know the vehicular composition of your study area, in other words,
    the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to
    start with the project to download a template to create a structure of directories and scripts.
Predicate helper functions for testing atomic vectors in R. All functions take
  a single argument 'x' and check whether it's of the target type of base-R
  atomic vector (i.e. no class extensions nor attributes other than 'names'),
  returning TRUE or FALSE. Some additionally check for value (e.g. absence of
  missing values, infinities, blank characters, or 'names' attribute; or having
  length 1).
Functions for downloading, reshaping, culling, cleaning, and analyzing fossil data from the Paleobiology Database <https://paleobiodb.org>.
A set of functions for generating HTML to
    embed hosted video in your R Markdown documents or Shiny applications.
A close to zero dependency package to draw and display Venn
    diagrams up to 7 sets, and any Boolean union of set intersections.
A set of functions to generate high-resolution Venn and Euler plots. Includes handling for several special cases, including two-case scaling, and extensive customization of plot shape and structure.
Calculates and displays Venn and Euler Diagrams.
Generate Venn diagrams from two or three sets, displaying the 
    overlapping items as lists in the appropriate sections. The lists can be
    split into columns or shortened for large sets and the plot is generated
    using 'ggplot2' allowing further customisations.
Calculate and plot Venn diagrams in 2D and 3D.
Turn R analysis outputs into full sentences, by writing vectors into in-sentence lists, pluralising words conditionally, spelling out numbers if they are at the start of sentences, writing out dates in full following US or UK style, and managing capitalisations in tidy data.
Describe in words the genealogical relationship between two
    members of a given pedigree, using the algorithm in Vigeland (2022)
    <doi:10.1186/s12859-022-04759-y>. 'verbalisr' is part of the
    'pedsuite' collection of packages for pedigree analysis. For a
    demonstration of 'verbalisr', see the online app 'QuickPed' at
    <https://magnusdv.shinyapps.io/quickped>.
Provides access to data collected by the Ecuadorian Truth Commission.
    Allows users to extract and analyze systematized information for human rights 
    research in Ecuador. The package contains datasets documenting human rights 
    violations from 1984-2008, including victim information, violation types, 
    perpetrators, and geographic distribution.
Facilitates use and analysis of data about the armed conflict
    in Colombia resulting from the joint project between La Jurisdicción
    Especial para la Paz (JEP), La Comisión para el Esclarecimiento de la
    Verdad, la Convivencia y la No repetición (CEV), and the Human Rights Data
    Analysis Group (HRDAG). The data are 100 replicates from a multiple
    imputation through chained equations as described in Van Buuren and
    Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. With the replicates
    the user can examine four human rights violations that occurred in the
    Colombian conflict accounting for the impact of missing fields and fully
    missing observations.
An implementation of the 'Verhoeff' algorithm for calculating 
    check digits (Verhoeff, J. (1969) <doi:10.1002/zamm.19710510323>). 
    Functions are provided to calculate a check digit given an input number, 
    calculate and append a check digit to an input number, and validate that a 
    check digit is correct given an input number.
Utilities for verifying discrete, continuous and probabilistic forecasts, and forecasts expressed as parametric distributions are included.
Extendable 'R6' file comparison classes, including a 'shiny' app for combining the comparison functionality into a file comparison application. The package idea originates from pharma companies' drug development processes, where statisticians and statistical programmers need to review and compare different versions of the same outputs and datasets. The package implementation itself is not tied to any specific industry and can be used in any context for easy file comparisons between different file version sets.
The biomarker data set by Vermeulen et al. (2009)
    <doi:10.1016/S1470-2045(09)70154-8> is provided. The data
    source, however, is by Ruijter et al. (2013)
    <doi:10.1016/j.ymeth.2012.08.011>. The original data set may
    be downloaded from
    <https://medischebiologie.nl/wp-content/uploads/2019/02/qpcrdatamethods.zip>.
    This data set is for a real-time quantitative polymerase chain reaction
    (PCR) experiment that comprises the raw fluorescence data of 24,576
    amplification curves. This data set comprises 59 genes of interest and 5
    reference genes. Each gene was assessed on 366 neuroblastoma complementary
    DNA (cDNA) samples and on 18 standard dilution series samples (10-fold
    5-point dilution series x 3 replicates + no template controls (NTC) x 3
    replicates).
R data pipelines commonly require reading and writing data to versioned
    directories. Each directory might correspond to one step of a multi-step process,
    where that version corresponds to particular settings for that step and a chain of
    previous steps that each have their own versions. This package creates a configuration
    object that makes it easy to read and write versioned data, based on YAML
    configuration files loaded and saved to each versioned folder.
Installs specified versions of R packages hosted on CRAN and
    provides functions to list available versions and the versions of currently
    installed packages. These tools can be used to help make R projects and
    packages more reproducible. 'versions' fits in the narrow gap between
    the 'devtools' install_version() function and the 'checkpoint' package.
    devtools::install_version() installs a stated package version from source files
    stored on the CRAN archives. However CRAN does not store binary versions of
    packages so Windows users need to have RTools installed and Windows and OSX
    users get longer installation times. 'checkpoint' uses the Revolution Analytics
    MRAN server to install packages (from source or binary) as they were available
    on a given date. It also provides a helpful interface to detect the packages
    in use in a directory and install all of those packages for a given date.
    'checkpoint' doesn't provide install.packages-like functionality however, and
    that's what 'versions' aims to do, by querying MRAN. As MRAN only goes back to
    2014-09-17, 'versions' can't install packages archived before this date.
A lightweight package for sorting version codes in various forms. No strong dependencies guaranteed.
A toolset for interactively exploring the differences between two data frames.
Creates Vertex Similarity matrix of an undirected graph based
  on the method stated by E. A. Leicht, Petter Holme, AND M. E. J. Newman in
  their paper <DOI:10.1103/PhysRevE.73.026120>.
Provides functions to run statistical analyses on
    surface-based neuroimaging data, computing measures including cortical
    thickness and surface area of the whole-brain and of the hippocampi.
    It can make use of 'FreeSurfer', 'fMRIprep', 'XCP-D', 'HCP' and 'CAT12' 
    preprocessed datasets, 'HippUnfold' hippocampal outputs and 
    'SubCortexMesh' subcortical outputs for a given sample by 
    restructuring the data values into a single file. The single file can 
    then be used by the package for analyses independently from its base
    dataset and without need for its access.
Multi-precision library that allows to store and operate with arbitrarily big integers without
    loss of precision. It includes a large list of tools to work with them, like:
      - Arithmetic and logic operators
      - Modular-arithmetic operators
      - Computer Number Theory utilities
      - Probabilistic primality tests
      - Factorization algorithms
      - Random generators of diferent types of integers.
The goal of 'vetiver' is to provide fluent tooling to
    version, share, deploy, and monitor a trained model. Functions handle
    both recording and checking the model's input data prototype, and
    predicting from a remote API endpoint. The 'vetiver' package is
    extensible, with generics that can support many kinds of models.
Declarative template-based framework for verifying that objects
  meet structural requirements, and auto-composing error messages when they do
  not.
R Codes and Datasets for Duchateau, L. and Janssen, P. and Rowlands, G. J. (1998). Linear Mixed Models. An Introduction with applications in Veterinary Research. International Livestock Research Institute.
Implements methods for inference on potential waning of vaccine
    efficacy and for estimation of vaccine efficacy at a user-specified time
    after vaccination based on data from a randomized, double-blind,
    placebo-controlled vaccine trial in which participants may be unblinded
    and placebo subjects may be crossed over to the study vaccine.  The
    methods also allow adjustment for possible confounding via inverse
    probability weighting through specification of models for the trial
    entry process, unblinding mechanisms, and the probability an unblinded
    placebo participant accepts study vaccine:  Tsiatis, A. A. and Davidian,
    M. (2022) <doi:10.1111/biom.13509>.
Implements methods for inference on potential waning of vaccine efficacy and for estimation of vaccine efficacy at a user-specified time after vaccination based on data from a randomized, double-blind, placebo-controlled vaccine trial in which participants may be unblinded and placebo subjects may be crossed over to the study vaccine.  The methods also for variant stratification and allow adjustment for possible confounding via inverse probability weighting through specification of models for the trial entry process, unblinding mechanisms, and the probability an unblinded placebo participant accepts study vaccine.
A set of visual input controls for Shiny apps to facilitate filtering across multiple outputs.
Variance function estimation for models proposed by W. Sadler in his variance function program 
  ('VFP', www.aacb.asn.au/AACB/Resources/Variance-Function-Program). Here, the idea is
  to fit multiple variance functions to a data set and consequently assess which function reflects
  the relationship 'Var ~ Mean' best. For 'in-vitro diagnostic' ('IVD') assays modeling this relationship
  is of great importance when individual test-results are used for defining follow-up treatment of patients.
Realization of published methods to analyze visual field (VF) progression. Introduction to the plotting methods (designed by author TE) for VF output visualization. A sample dataset for two eyes, each with 10 follow-ups is included. The VF analysis methods could be found in -- Musch et al. (1999) <doi:10.1016/S0161-6420(99)90147-1>, Nouri-Mahdavi et at. (2012) <doi:10.1167/iovs.11-9021>, Schell et at. (2014) <doi:10.1016/j.ophtha.2014.02.021>, Aptel et al. (2015) <doi:10.1111/aos.12788>.
Empirical models for runoff, erosion, and phosphorus loss 
    across a vegetated filter strip, given slope, soils, climate, and 
    vegetation (Gall et al., 2018) <doi:10.1007/s00477-017-1505-x>. 
    It also includes functions for deriving climate parameters from 
    measured daily weather data, and for simulating rainfall. Models 
    implemented include MUSLE (Williams, 1975) and APLE (Vadas et al., 
    2009 <doi:10.2134/jeq2008.0337>).
If f <- function(x){x^2} and g <- function(x){x+1} it is
     a constant source of annoyance that "f+g" is not defined.
     Package 'vfunc' allows you to do this, and we have (f+g)(2)
     returning 5.  The other arithmetic operators are similarly
     implemented.  A wide class of coding bugs is eliminated.
An implementation of about 6 major classes of
    statistical regression models. The central algorithm is
    Fisher scoring and iterative reweighted least squares.
    At the heart of this package are the vector generalized linear
    and additive model (VGLM/VGAM) classes. VGLMs can be loosely
    thought of as multivariate GLMs. VGAMs are data-driven
    VGLMs that use smoothing. The book "Vector Generalized
    Linear and Additive Models: With an Implementation in R"
    (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of
    the statistical framework and the package. Currently only
    fixed-effects models are implemented. Many (100+) models and
    distributions are estimated by maximum likelihood estimation
    (MLE) or penalized MLE. The other classes are RR-VGLMs
    (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained
    RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs,
    RCIMs (row-column interaction models)---these classes perform
    constrained and unconstrained quadratic ordination (CQO/UQO)
    models in ecology, as well as constrained additive ordination
    (CAO). Hauck-Donner effect detection is implemented.
    Note that these functions are subject to change;
    see the NEWS and ChangeLog files for latest changes.
Mainly data sets to accompany the VGAM package and
	the book "Vector Generalized Linear and
	Additive Models: With an Implementation in R" (Yee, 2015)
	<DOI:10.1007/978-1-4939-2818-7>.
	These are used to illustrate vector generalized
	linear and additive models (VGLMs/VGAMs), and associated models
	(Reduced-Rank VGLMs, Quadratic RR-VGLMs, Row-Column
	Interaction Models, and constrained and unconstrained ordination
	models in ecology). This package now contains some
	old VGAM family functions which have been replaced by newer
	ones (often because they are now special cases).
Extending the functionalities of the 'VGAM' package with
         additional functions and datasets. At present, 'VGAMextra'
         comprises new family functions (ffs) to estimate several time
         series models by maximum likelihood using Fisher scoring, 
         unlike popular packages in CRAN relying on optim(), including
         ARMA-GARCH-like models, the Order-(p, d, q) ARIMAX model (non-
         seasonal), the Order-(p) VAR model, error correction models
         for cointegrated time series, and ARMA-structures with Student-t 
         errors. For independent data, new ffs to estimate the inverse-
         Weibull, the inverse-gamma, the generalized beta of the second
         kind and the general multivariate normal distributions are
         available. In addition, 'VGAMextra' incorporates new VGLM-links
         for the mean-function, and the quantile-function (as an alternative
         to ordinary quantile modelling) of several 1-parameter distributions,
         that are compatible with the class of VGLM/VGAM family functions.
         Currently, only fixed-effects models are implemented. All functions
         are subject to change; see the NEWS for further details on the
         latest changes.
Estimates hierarchical models using variational inference. 
    At present, it can estimate logistic, linear, and negative binomial models. 
    It can accommodate models with an arbitrary number of random effects and 
    requires no integration to estimate. It also provides the ability to improve 
    the quality of the approximation using marginal augmentation. 
    Goplerud (2022) <doi:10.1214/21-BA1266> and Goplerud (2024) <doi:10.1017/S0003055423000035> 
    provide details on the variational algorithms.
Analyze the co-adaptation of codon usage between a virus and its host, calculate various codon usage bias measurements as: effective number of codons (ENc) Novembre (2002) <doi:10.1093/oxfordjournals.molbev.a004201>, codon adaptation index (CAI) Sharp  and  Li (1987) <doi:10.1093/nar/15.3.1281>, relative  codon deoptimization index (RCDI) Puigbò et al (2010) <doi:10.1186/1756-0500-3-87>, similarity index (SiD) Zhou et al (2013) <doi:10.1371/journal.pone.0077239>,  synonymous codon usage orderliness (SCUO) Wan et al (2004) <doi:10.1186/1471-2148-4-19> and, relative synonymous    codon usage (RSCU) Sharp et al (1986) <doi:10.1093/nar/14.13.5125>. Also, it provides a statistical dinucleotide over- and underrepresentation with three different models. Implement several methods for visualization of codon usage as ENc.GC3plot() and PR2.plot().
The "Vertical and Horizontal Inheritance Consistence Analysis" method is described in the following publication: "VHICA: a new method to discriminate between vertical and horizontal transposon transfer: application to the mariner family within Drosophila" by G. Wallau. et al. (2016) <DOI:10.1093/molbev/msv341>. The purpose of the method is to detect horizontal transfers of transposable elements, by contrasting the divergence of transposable element sequences with that of regular genes.
The base class 'VirtualArray' is defined, which acts as a wrapper around lists allowing users to fold arbitrary sequential data into n-dimensional, R-style virtual arrays. The derived 'XArray' class is defined to be used for homogeneous lists that contain a single class of objects. The 'RasterArray' and 'SfArray' classes enable the use of stacked spatial data instead of lists.
'Via Foundry' API provides streamlined tools for interacting with and extracting data from structured responses, particularly for use cases involving hierarchical data from Foundry's API. It includes functions to fetch and parse process-level and file-level metadata, allowing users to efficiently query and manipulate nested data structures. Key features include the ability to list all unique process names, retrieve file metadata for specific or all processes, and dynamically load or download files based on their type. With built-in support for handling various file formats (e.g., tabular and non-tabular files) and seamless integration with API through authentication, this package is designed to enhance workflows involving large-scale data management and analysis. Robust error handling and flexible configuration ensure reliable performance across diverse data environments. Please consult the documentation for the API endpoint for your installation.
Practicals, data sets, helper functions and interactive 'Shiny' apps
    used in the introductory course on Bayesian inference at the
    Valencia International Bayesian Summer School. Installing 'vibass' installs
    all the other packages used during the course and downloads all necessary
    materials for working off line.
The Variable Infiltration Capacity (VIC) model is a macroscale
    hydrologic model that solves full water and energy balances, originally
    developed by Xu Liang at the University of Washington (UW).
    The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>,
    see Hamman et al. (2018).
    Development and maintenance of the current official version
    of the VIC model at present is led by the UW Hydro (Computational Hydrology
    group) in the Department of Civil and Environmental Engineering at UW. VIC is
    a research model and in its various forms it has been applied to most of the
    major river basins around the world, as well as globally 
    <http://vic.readthedocs.io/en/master/Documentation/References/>. 
    References: "Liang, X., D. P. Lettenmaier, E. F. Wood, and
    S. J. Burges (1994), A simple hydrologically based model of land surface water
    and energy fluxes for general circulation models, J. Geophys. Res., 99(D7),
    14415-14428, <doi:10.1029/94JD00483>"; 
    "Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The
    Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements
    for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, 
    <doi:10.5194/gmd-11-3481-2018>".
A variational Bayesian finite mixture model for the clustering of categorical data, and can implement variable selection and semi-supervised outcome guiding if desired. Incorporates an option to perform model averaging over multiple initialisations to reduce the effects of local optima and improve the automatic estimation of the true number of clusters. For further details, see the paper by Rao and Kirk (2024) <doi:10.48550/arXiv.2406.16227>.
A shiny app for accurate estimation of vaccine induced immunogenicity 
    with bivariate linear modeling. Method is detailed in: Lhomme, Hejblum, Lacabaratz, 
    Wiedemann, Lelievre, Levy, Thiebaut & Richert (2020). Journal of Immunological Methods, 
    477:112711. <doi:10.1016/j.jim.2019.112711>.
Compared with the similar graph embedding method such as Laplacian Eigenmaps, 'Vicus' can exploit more local structures of graph data. For the details of the methods, see the reference section of 'GitHub' README.md <https://github.com/rikenbit/Vicus>.
Video interactivity within 'shiny' applications using 'video.js'. Enables
    the status of the video to be sent from the UI to the server, and allows events
    such as playing and pausing the video to be triggered from the server.
Interface to the 'Video Game Insights' API
    <https://app.sensortower.com/vgi/> for video game market analytics and
    intelligence. Provides functions to retrieve game metadata, developer and
    publisher information, player statistics (concurrent players, daily and monthly
    active users), revenue and sales data, review analytics, wish-list tracking,
    and platform-specific rankings. The package includes data processing utilities
    to analyze player demographics, track pricing history, calculate player overlap
    between games, and monitor market trends. Supports analysis across multiple
    gaming platforms including 'Steam', 'PlayStation', 'Xbox', and 'Nintendo' with
    unified data structures for cross-platform comparison.
Converts Vietnam's provinces' names and ID
    across different formats. Handles diacritics and different spellings.
Conversion of characters from unsupported Vietnamese character encodings to Unicode characters. These Vietnamese encodings (TCVN3, VISCII, VPS) are not natively supported in R and lead to printing of wrong characters and garbled text (mojibake). This package fixes that problem and provides readable output with the correct Unicode characters (with or without diacritics).
Debugging pipe chains often consists of viewing the output after 
  each step. This package adds RStudio addins and two functions that allow 
  outputing each or select steps in a convenient way.
Provides a graphical user interface to integrate, visualize and explore results 
            from linkage and quantitative trait loci analysis, together with genomic information for autopolyploid 
            species. The app is meant for interactive use and allows users to optionally upload different sources 
            of information, including  gene annotation and alignment files, enabling the exploitation and search for 
            candidate genes in a genome browser. In its current version, 'VIEWpoly' supports inputs from 'MAPpoly', 
            'polymapR', 'diaQTL', 'QTLpoly', 'polyqtlR', 'GWASpoly', and 'HIDECAN' packages.
Provides a feature-rich, popup-based interactive interface for
    viewing, exploring, filtering, sorting, editing, analysing, and plotting
    R data frames. Key features include: a searchable, paginated data table
    with drag-and-drop column reordering and variable-label 'tooltips';
    multi-condition filters (AND/OR) with live preview; multi-column sorting;
    column visibility management with search; an Excel-like cell editor powered
    by 'rhandsontable'; find-and-replace across one or all columns (literal or
    regex) with automatic live preview; a Plots tab with auto-detected
    histograms and bar charts for every column; automatic 'dplyr' code
    generation reflecting every operation performed in the 'UI'; one-click CSV
    export; and a Variable Info tab with type, missing values, and summary
    statistics. The entire interface is launched with a single call to ViewR()
    and works as a popup dialog, in the 'RStudio' Viewer pane, or in the
    system browser.
A collection of functions to make R a more effective viewscape analysis 
    tool for calculating viewscape metrics based on computing the viewable area for 
    given a point/multiple viewpoints and a digital elevation model.The method of calculating 
    viewscape metrics implemented in this package are based on the work of 
    Tabrizian et al. (2020) <doi:10.1016/j.landurbplan.2019.103704>. The algorithm of computing 
    viewshed is based on the work of 
    Franklin & Ray. (1994) <https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=555780f6f5d7e537eb1edb28862c86d1519af2be>.
Perform the analysis of the World Health Organization
       (WHO) Pharmacovigilance database 'VigiBase' (Extract Case Level version),
       <https://who-umc.org/>
       e.g., load data, perform data management,
       disproportionality analysis, and descriptive statistics. Intended for
       pharmacovigilance routine use or studies.
       This package is NOT supported nor reflect the opinion of the WHO, or the
       Uppsala Monitoring Centre.
       Disproportionality methods are described by Norén et 
       al (2013) <doi:10.1177/0962280211403604>.
Conducts linear regression using variational Bayesian inference, particularly optimized for genome-wide association mapping and whole-genome prediction which use a number of DNA markers as the explanatory variables. Provides seven regression models which select the important variables (i.e., the variables related to response variables) among the given explanatory variables in different ways (i.e., model structures).
Inference methods for state-space models, relying on the Kalman Filter or on Viking (Variational Bayesian VarIance tracKING). See J. de Vilmarest (2022) <https://theses.hal.science/tel-03716104/>.
This is a package for creating and running Agent Based Models (ABM). It provides a set of base classes with core functionality to allow bootstrapped models. For more intensive modeling, the supplied classes can be extended to fit researcher needs.
Provides methods for imputation and visualization of 
    missing values. It includes graphical tools to explore the amount, structure 
    and patterns of missing and/or imputed values, supporting exploratory 
    data analysis and helping to investigate potential missingness mechanisms
    (details in Alfons, Templ and Filzmoser, <doi:10.1007/s11634-011-0102-y>. 
    The quality of imputations can be assessed visually using a wide range of 
    univariate, bivariate and multivariate plots. 
    The package further provides several imputation methods, 
    including efficient implementations of k-nearest neighbour and hot-deck 
    imputation (Kowarik and Templ 2013, <doi:10.18637/jss.v074.i07>, 
    iterative robust model-based multiple 
    imputation (Templ 2011, <doi:10.1016/j.csda.2011.04.012>; 
    Templ 2023, <doi:10.3390/math11122729>), and machine learning–based 
    approaches such as robust GAM-based multiple imputation 
    (Templ 2024, <doi:10.1007/s11222-024-10429-1>) as well as gradient boosting 
    (XGBoost) and transformer-based methods 
    (Niederhametner et al., <doi:10.1177/18747655251339401>). 
    General background and practical guidance on imputation are provided in the 
    Springer book by 
    Templ (2023) <doi:10.1007/978-3-031-30073-8>.
To computed the variability independent of mean (VIM) or variation
    independent of mean (VIM). The methodology can be found at
    Peter M Rothwell et al. (2010) <doi:10.1016/S1474-4422(10)70067-3>.
Collapsed Variational Inference for a Dirichlet Process (DP) mixture model with unknown covariance matrix structure and DP concentration parameter. It enables efficient clustering of high-dimensional data with significantly improved computational speed than traditional MCMC methods. The package incorporates 8 parameterisations and corresponding prior choices for the unknown covariance matrix, from which the user can choose and apply accordingly.
Calculate point estimates of and valid confidence intervals for
    nonparametric, algorithm-agnostic variable importance measures in high and low dimensions,
    using flexible estimators of the underlying regression functions. For more information
    about the methods, please see Williamson et al. (Biometrics, 2020),  Williamson et al. (JASA, 2021), and Williamson and Feng (ICML, 2020).
An implementation of methods related to sparse clustering and variable importance 
    in clustering. The package currently allows to perform sparse k-means clustering with a group 
    penalty, so that it automatically selects groups of numerical features. It also allows to 
    perform sparse clustering and variable selection on mixed data (categorical and numerical 
    features), by preprocessing each categorical feature as a group of numerical features.
    Several methods for visualizing and exploring the results are also provided. 
    M. Chavent, J. Lacaille, A. Mourer and M. Olteanu (2020)<https://www.esann.org/sites/default/files/proceedings/2020/ES2020-103.pdf>.
The variable importance is calculated using knock off variables. Then output can be provided in numerical and graphical form. Meredith L Wallace (2023) <doi:10.1186/s12874-023-01965-x>.
Provides a programmatic interface in R for the US Department of 
    Transportation (DOT) National Highway Transportation Safety Administration 
    (NHTSA) vehicle identification number (VIN) API, located at 
    <https://vpic.nhtsa.dot.gov/api/>. 
    The API can decode up to 50 vehicle identification numbers in one call, and 
    provides manufacturer information about the vehicles, including make, model, 
    model year, and gross vehicle weight rating (GVWR).
Provides tools for the statistical analysis of regular vine copula 
    models, see Aas et al. (2009) <doi:10.1016/j.insmatheco.2007.02.001> and 
    Dissman et al. (2013) <doi:10.1016/j.csda.2012.08.010>.
    The package includes tools for parameter estimation, model selection,
    simulation, goodness-of-fit tests, and visualization. Tools for estimation,
    selection and exploratory data analysis of bivariate copula models are also
    provided.
Implements D-vine quantile regression models with
  parametric or nonparametric pair-copulas. See 
  Kraus and Czado (2017) <doi:10.1016/j.csda.2016.12.009> and
  Schallhorn et al. (2017) <doi:10.48550/arXiv.1705.08310>.
Produces violin plots with optional nonparametric (Mann-Whitney test) and parametric (Tukey's honest significant difference) mean comparison and linear regression. This package aims to be a simple and quick visualization tool for comparing means and assessing trends of categorical factors.
A violin plot is a combination of a box plot and a kernel density plot. This package allows extensive customisation of violin plots.
A general framework for constructing variable importance plots from 
  various types of machine learning models in R. Aside from some standard model-
  specific variable importance measures, this package also provides model-
  agnostic approaches that can be applied to any supervised learning algorithm.
  These include 1) an efficient permutation-based variable importance measure, 
  2) variable importance based on Shapley values (Strumbelj and Kononenko, 
  2014) <doi:10.1007/s10115-013-0679-x>, and 3) the variance-based 
  approach described in Greenwell et al. (2018) <doi:10.48550/arXiv.1805.04755>. A 
  variance-based method for quantifying the relative strength of interaction 
  effects is also included (see the previous reference for details).
Generate a violin point plot, a combination of a violin/histogram
    plot and a scatter plot by offsetting points within a category based on their
    density using quasirandom noise.
Provides tools for designing virus protein panels through sequence clustering and protein sequence analysis. The package includes functionality for filtering sequences, removing redundancy, identifying outliers, clustering sequences, and calculating entropy to evaluate clustering quality. A publication describing these methods is in preparation and will be added once available.
A dedicated viral-explainer model tool designed to empower researchers in the field of HIV research, particularly in viral load and CD4 (Cluster of Differentiation 4) lymphocytes regression modeling. Drawing inspiration from the 'tidymodels' framework for rigorous model building of Max Kuhn and Hadley Wickham (2020) <https://www.tidymodels.org>, and the 'DALEXtra' tool for explainability by Przemyslaw Biecek (2020) <doi:10.48550/arXiv.2009.13248>. It aims to facilitate interpretable and reproducible research in biostatistics and computational biology for the benefit of understanding HIV dynamics.
Computation of volatility impulse response function for multivariate time series model using algorithm by Jin, Lin and Tamvakis (2012) <doi:10.1016/j.eneco.2012.03.003>.
Color maps designed to improve graph readability for readers with 
    common forms of color blindness and/or color vision deficiency. The color 
    maps are also perceptually-uniform, both in regular form and also when 
    converted to black-and-white for printing. This package also contains 
    'ggplot2' bindings for discrete and continuous color and fill scales. A lean
    version of the package called 'viridisLite' that does not include the 
    'ggplot2' bindings can be found at 
    <https://cran.r-project.org/package=viridisLite>.
Color maps designed to improve graph readability for readers with 
    common forms of color blindness and/or color vision deficiency. The color 
    maps are also perceptually-uniform, both in regular form and also when 
    converted to black-and-white for printing. This is the 'lite' version of the 
    'viridis' package that also contains 'ggplot2' bindings for discrete and 
    continuous color and fill scales and can be found at 
    <https://cran.r-project.org/package=viridis>.
Tools for reporting and forecasting viral respiratory infections,
    using case surveillance data. Report generation tools for short-term forecasts,
    and validation metrics for an arbitrary number of customizable respiratory viruses.
    Estimation of the effective reproduction number is based on the 'EpiEstim' framework 
    described in work by 'Cori' and colleagues. (2013) <doi:10.1093/aje/kwt133>.
Tools to generate virtual environmental drivers with a given temporal autocorrelation, and to simulate pollen curves at annual resolution over millennial time-scales based on these drivers and virtual taxa with different life traits and niche features. It also provides the means to simulate quasi-realistic pollen-data conditions by applying simulated accumulation rates and given depth intervals between consecutive samples.
Constructs a virtual population from fertility and mortality rates for any country,
	calendar year and birth cohort in the Human Mortality Database <https://www.mortality.org> and the Human Fertility Database <https://www.humanfertility.org>.  Fertility histories are simulated for every individual and their offspring, producing a multi-generation virtual population.
Provides a framework for generating virtual species distributions,
    a procedure increasingly used in ecology to improve species distribution
    models. This package integrates the existing methodological approaches 
    with the objective of generating virtual species distributions with 
    increased ecological realism.
Provides users with a simple and convenient
             mechanism to manage and query a 'Virtuoso' database using the 'DBI' (Data-Base Interface)
             compatible 'ODBC' (Open Database Connectivity) interface.
             'Virtuoso' is a high-performance "universal server," which can act
             as both a relational database, supporting standard Structured Query
             Language ('SQL') queries, while also supporting data following the
             Resource Description Framework ('RDF') model for Linked Data.
             'RDF' data can be queried using 'SPARQL' ('SPARQL' Protocol and 'RDF' Query Language)
             queries, a graph-based query that supports semantic reasoning.
             This allows users to leverage the performance of local or remote 'Virtuoso' servers using
             popular 'R' packages such as 'DBI' and 'dplyr', while also providing a 
             high-performance solution for working with large 'RDF' 'triplestores' from 'R.'
             The package also provides helper routines to install, launch, and manage
             a 'Virtuoso' server locally on 'Mac', 'Windows' and 'Linux' platforms using
             the standard interactive installers from the 'R' command-line.  By 
             automatically handling these setup steps, the package can make using 'Virtuoso'
             considerably faster and easier for a most users to deploy in a local
             environment. Managing the bulk import of triples
             from common serializations with a single intuitive command is another key
             feature of this package.  Bulk import performance can be tens to
             hundreds of times faster than the comparable imports using existing 'R' tools,
             including 'rdflib' and 'redland' packages.
A collection of tools for downstream analysis of
    'VirusHunterGatherer' output. Processing of hittables 
    and plotting of results, enabling better interpretation,
    is made easier with the provided functions.
Provides a comprehensive R interface to the 'VirusTotal' API v3.0
    <https://docs.virustotal.com/>, a Google service that analyzes files and
    URLs for viruses, worms, trojans and other malware. Features include
    file/URL scanning, domain categorization, passive DNS information, IP
    reputation analysis, IoC relationships, sandbox analysis, and
    comment/voting systems. Implements rate limiting, error handling, and
    response validation for robust security analysis workflows.
Provides easy-to-use tools for data analysis and visualization for hyperspectral remote sensing (also known as imaging spectroscopy), with 
    a particular focus on vegetation hyperspectral data analysis. It consists of a set of functions, ranging from the organization of hyperspectral data 
    in the proper data structure for spectral feature selection, calculation of vegetation index, multivariate analysis, as well as to the visualization 
    of spectra and results of analysis in the 'ggplot2' style.
Provides a set of wrapper functions for 'Visa Chart Components'.
  'Visa Chart Components' <https://github.com/visa/visa-chart-components> is an accessibility focused,
  framework agnostic set of data experience design systems components for the web.
Implementation of 'shiny' app to visualize adverse events based on the Common Terminology Criteria for Adverse Events (CTCAE) using stacked correspondence analysis as described in Diniz et. al (2021)<doi:10.1186/s12874-021-01368-w>.
Provides methods to calculate diagnostics for multicollinearity among predictors in a linear or
  generalized linear model. It also provides methods to visualize those diagnostics following Friendly & Kwan (2009),
  "Where’s Waldo: Visualizing Collinearity Diagnostics", <doi:10.1198/tast.2009.0012>.
  These include better tabular presentation of collinearity diagnostics that highlight the important numbers,
  a semi-graphic tableplot of the diagnostics to make warning and danger levels more salient,
  and a "collinearity biplot" of the smallest dimensions of predictor space, where collinearity is most apparent.
A set of functions providing several visualization tools for exploring the behavior of the components in a network meta-analysis of multi-component (complex) interventions: 
   - components descriptive analysis
   - heat plot of the two-by-two component combinations 
   - leaving one component combination out scatter plot 
   - violin plot for specific component combinations' effects
   - density plot for components' effects  
   - waterfall plot for the interventions' effects that differ by a certain component combination 
   - network graph of components
   - rank heat plot of components for multiple outcomes.
   The implemented tools are described by Seitidis et al. (2023) <doi:10.1002/jrsm.1617>.
Functionality for creating phase portraits of functions in the
    complex number plane. Works with R base graphics, whose full 
    functionality is available. Parallel processing is used for optimum 
    performance.
Visualizing of distributions of covariance matrices.
    The package implements the methodology described in Tokuda, T., Goodrich, B., Van Mechelen, I., Gelman, A., & Tuerlinckx, F. (2012) <https://sites.stat.columbia.edu/gelman/research/unpublished/Visualization.pdf>.
Create preliminary exploratory data visualisations of an entire 
    dataset to identify problems or unexpected features using 'ggplot2'.
Designed to help the user to determine the sensitivity of an proposed causal effect to unconsidered common causes. Users can create visualizations of sensitivity, effect sizes, and determine which pattern of effects would support a causal claim for between group differences. Number needed to treat formula from Kraemer H.C. & Kupfer D.J. (2006) <doi:10.1016/j.biopsych.2005.09.014>.
Performs modeling and forecasting of park visitor counts
	using social media data and (partial) on-site visitor counts.
	Specifically, the model is built based on an automatic decomposition
	of the trend and seasonal components of the social media-based park visitor counts,
	from which short-term forecasts of the visitor counts and percent changes
	in the visitor counts can be made. A reference for the underlying model that 'VisitorCounts' uses can be found at 
    Russell Goebel, Austin Schmaltz, Beth Ann Brackett, Spencer A. Wood, Kimihiro Noguchi (2023) <doi:10.1002/for.2965> .
Provides a suite of analytical functionalities to process and analyze
    visual meteor observations from the Visual Meteor Database
    of the International Meteor Organization <https://www.imo.net/>.
A comprehensive suite of static and interactive visual diagnostics for assessing the quality of multiply-imputed data obtained from packages such as 'mixgb' and 'mice'. The package supports inspection of distributional characteristics, diagnostics based on masking observed values and comparing them with re-imputed values, and convergence diagnostics.
Provides an R interface to the 'vis.js' JavaScript charting
    library. It allows an interactive visualization of networks.
Provides methods to transform omop_result objects into
    formatted tables and figures, facilitating the visualisation of study
    results working with the Observational Medical Outcomes Partnership
    (OMOP) Common Data Model.
Provides tools for visibility analysis in geospatial data. It
    offers functionality to perform isovist calculations, using arbitrary
    geometries as both viewpoints and occluders.
Provides tools for the analysis and visualization of animal and
    plant pedigrees. Analytical methods include equivalent complete generations,
    generation intervals, effective population size (via inbreeding, coancestry,
    and demographic approaches), founder and ancestor contributions, partial
    inbreeding, genetic diversity indices, and additive (A), dominance (D), and
    epistatic (AA) relationship matrices. Core algorithms — ancestry tracing,
    topological sorting, inbreeding coefficients, and matrix construction — are
    implemented in C++ ('Rcpp', 'RcppArmadillo') and 'data.table', scaling to
    pedigrees with over one million individuals. Pedigree graphs are rendered
    via 'igraph' with support for compact full-sib family display; relationship
    matrices can be visualized as heatmaps. Supports complex mating systems,
    including selfing and pedigrees in which the same individual can appear as
    both sire and dam.
Provides a convenient interface for constructing plots to
    visualize the fit of regression models arising from a wide variety
    of models in R ('lm', 'glm', 'coxph', 'rlm', 'gam', 'locfit', 'lmer',
    'randomForest', etc.)
A library for creating time based charts, like Gantt or timelines. Possible outputs 
  include 'ggplot2' diagrams, 'plotly.js' graphs, 'Highcharts.js' widgets and data.frames. Results can be
  used in the 'RStudio' viewer pane, in 'RMarkdown' documents or in Shiny apps. In the 
  interactive outputs created by vistime() and hc_vistime(), you can interact with the 
  plot using mouse hover or zoom.
Traces information spread through interactions between features, utilising information theory measures and a higher-order generalisation of the concept of widest paths in graphs.
  In particular, 'vistla' can be used to better understand the results of high-throughput biomedical experiments, by organising the effects of the investigated intervention in a tree-like hierarchy from direct to indirect ones, following the plausible information relay circuits.
  Due to its higher-order nature, 'vistla' can handle multi-modality and assign multiple roles to a single feature.
Provides a visualization for characterizing subgroups defined by a decision tree structure. The visualization simplifies the ability to interpret individual pathways to subgroups; each sub-plot describes the distribution of observations within individual terminal nodes and percentile ranges for the associated inner nodes.
Visualize and compute percentiles/probabilities of normal, t, f, chi square 
    and binomial distributions.
Estimates and plots as a heat map the correlation coefficients obtained via the wavelet local multiple correlation 'WLMC' (Fernández-Macho 2018) and the 'dominant' variable/s, i.e., the variable/s that maximizes the multiple correlation through time and scale (Polanco-Martínez et al. 2020, Polanco-Martínez 2022). We improve the graphical outputs of WLMC proposing a didactic and useful way to visualize the 'dominant' variable(s) for a set of time series. The WLMC was designed for financial time series, but other kinds of data (e.g., climatic, ecological, etc.) can be used. The functions contained in 'VisualDom' are highly flexible since these contains several parameters to personalize the time series under analysis and the heat maps. In addition, we have also included two data sets (named 'rdata_climate' and 'rdata_Lorenz') to exemplify the use of the functions contained in 'VisualDom'. Methods derived from Fernández-Macho (2018) <doi:10.1016/j.physa.2017.11.050>, Polanco-Martínez et al. (2020) <doi:10.1038/s41598-020-77767-8> and Polanco-Martínez (2023, in press).
A collection of tools for analyzing the field of vision. It
    provides a framework for development and use of innovative methods for
    visualization, statistical analysis, and clinical interpretation of
    visual-field loss and its change over time. It is intended to be a tool for
    collaborative research. The package is described in Marin-Franch and Swanson
    (2013) <doi:10.1167/13.4.10> and is part of the Open Perimetry Initiative
    (OPI) [Turpin, Artes, and McKendrick (2012) <doi:10.1167/12.11.22>].
Graphs the pdf or pmf and highlights what area or probability is
    present in user defined locations. Visualize is able to provide lower tail,
    bounded, upper tail, and two tail calculations. Supports strict and equal
    to inequalities.  Also provided on the graph is the mean and variance of
    the distribution.
Visualize the trends and historical downloads from packages in the 'CRAN' repository. Data is obtained by using the 'API' to query the database from the 'RStudio' 'CRAN' mirror.
To visualize the probabilities of early termination,
       fail and success of Simon's two-stage design.  To evaluate
       and visualize the operating characteristics of Simon's
       two-stage design.
Visual contour and 2D point and contour plots for binary classification modeling under algorithms such as 'glm', 'rf', 'gbm', 'nnet' and 'svm', presented over two dimensions generated by 'famd' and 'mca' methods. Package 'FactoMineR' for multivariate reduction functions and package 'MBA' for interpolation functions are used. The package can be used to visualize the discriminant power of input variables and algorithmic modeling, explore outliers, compare algorithm behaviour, etc. It has been created initially for teaching purposes, but it has also many practical uses under the 'XAI' paradigm.
Visualize Variance is an intuitive 'shiny' applications tailored for agricultural research data analysis, including one-way and two-way analysis of variance, correlation, and other essential statistical tools. Users can easily upload their datasets, perform analyses, and download the results as a well-formatted document, streamlining the process of data analysis and reporting in agricultural research.The experimental design methods are based on classical work by Fisher (1925) and Scheffe (1959). The correlation visualization approaches follow methods developed by Wei & Simko (2021) and Friendly (2002) <doi:10.1198/000313002533>.
Visualizes vowel variation in f0, F1, F2, F3 and duration.
A Shiny application and functions for visual exploration of hierarchical clustering with numeric datasets. Allows users to iterative set hyperparameters, select features and evaluate results through various plots and computation of evaluation criteria.
Implements the novel testing approach by Janitza et al.(2015)
    <http://nbn-resolving.de/urn/resolver.pl?urn=nbn:de:bvb:19-epub-25587-4>
    for the permutation variable importance measure in a random forest and the
    PIMP-algorithm by Altmann et al.(2010) <doi:10.1093/bioinformatics/btq134>.
    Janitza et al.(2015) <http://nbn-resolving.de/urn/resolver.pl?urn=nbn:de:bvb:19-epub-25587-4>
    do not use the "standard" permutation variable
    importance but the cross-validated permutation variable
    importance for the novel test approach. The cross-validated
    permutation variable importance is not based on the out-of-bag
    observations but uses a similar strategy which is inspired by
    the cross-validation procedure. The novel test approach can be
    applied for classification trees as well as for regression
    trees. However, the use of the novel testing approach has not
    been tested for regression trees so far, so this routine is
    meant for the expert user only and its current state is rather
    experimental.
Provides templates and functions to simplify the production and maintenance of curriculum vitae.
Analysing vital statistics based on tools
    consistent with the tidyverse. Tools are provided for data visualization,
    life table calculations, computing net migration numbers, Lee-Carter
    modelling; functional data modelling and forecasting.
Provides fitting routines for four versions of the
        Vitality family of mortality models.
A port of 'Inspect', a widely adopted 'Python' framework for
    large language model evaluation. Specifically aimed at 'ellmer' users
    who want to measure the effectiveness of their large language model-based
    products, the package supports prompt engineering, tool usage,
    multi-turn dialog, and model graded evaluations.
A collection of utilities that grew out of day-to-day non-life
    actuarial work at Com-PASS Advisory. Provides helpers for building
    chain-ladder triangles (cumulative, decumulative, run-off, development
    factors with optional weighting), constructing exposure columns from
    policy start/end dates, parsing Czech birth numbers ('rodné číslo')
    into dates, generating smooth RGB color palettes for charts, and
    loading multi-sheet 'xlsx'/'xlsb' files into a list of data frames.
    The chain-ladder helpers follow the standard methodology of
    Mack (1993) <doi:10.2143/AST.23.2.2005092>.
Provides functions for importing, validating, and analyzing 'Viva Glint'
    survey data exports, with optional API-based import via the 'Microsoft Graph'
    API. Includes tools for data reshaping, question-level analysis, multi-cycle
    comparisons, organizational hierarchy analysis, factor analysis, and
    correlation analysis. Harman (1960, ISBN: 0226316513); Husser (2017)
    <doi:10.1002/9781118901731.iecrm0048>.
Provides a versatile range of functions, including exploratory data analysis, time-series analysis, organizational network analysis, and data validation, whilst at the same time implements a set of best practices in analyzing and visualizing data specific to 'Microsoft Viva Insights'.
Analysis of minor alleles in Illumina sequencing data of viral
    genomes. Functions in 'vivaldi' primarily operate on vcf files.
A suite of plots for displaying variable importance and two-way variable interaction jointly. Can also display partial dependence plots laid out in a pairs plot or 'zenplots' style.
Provides an easy to calculate local variable importance measure based on Ceteris Paribus profile 
  and global variable importance measure based on Partial Dependence Profiles.
Interactive visualization for Bayesian prior and posterior distributions. 
    This package facilitates an animated transition between prior and posterior distributions. 
    Additionally, it splits the distribution into bars based on the provided 'breaks,' displaying 
    the probability for each region. If no 'breaks' are provided, it defaults to zero.
Offers a core selection of interactivity-first 'shiny' modules for many 
    plot types meant to serve as flexible building blocks for applications and 
    as the base for more complex modules. These modules
    allow for the rapid and convenient construction of 'shiny' apps with very few lines
    of code and decouple plotting from the underlying data. These modules allow 
    for full plot aesthetic customization by the end user through UI inputs. Utility
    functions for simple UI organization, automated UI tooltips, and additional
    plot enhancements are also provided.
Identifies the optimal confidence level to represent the results of a set of pairwise tests as suggested by Armstrong and Poirier (2025) <doi:10.1017/pan.2024.24>.
Provides an interface to the VK API <https://vk.com/dev/methods>.
      VK <https://vk.com/> is the largest European online social networking
      service, based in Russia.
Using frequency matrices, very low frequency variants (VLFs) are assessed for amino acid and nucleotide sequences.  The VLFs are then compared to see if they occur in only one member of a species, singleton VLFs, or if they occur in multiple members of a species, shared VLFs.  The amino acid and nucleotide VLFs are then compared to see if they are concordant with one another.  Amino acid VLFs are also assessed to determine if they lead to a change in amino acid residue type, and potential changes to protein structures. Based on Stoeckle and Kerr (2012) <doi:10.1371/journal.pone.0043992> and Phillips et al. (2023) <doi:10.3897/BDJ.11.e96480>.
Functions, Classes & Methods for estimation, prediction, and
  simulation (bootstrap) of Variable Length Markov Chain ('VLMC') Models.
Models categorical time series through a Markov Chain when a) covariates are predictors for transitioning into the next state/symbol and b) when the dependence in the past states has variable length. The probability of transitioning to the next state in the Markov Chain is defined by a multinomial regression whose parameters depend on the past states of the chain and, moreover, the number of states in the past needed to predict the next state also depends on the observed states themselves. See Zambom, Kim, and Garcia (2022) <doi:10.1111/jtsa.12615>.
A framework to infer causality on a pair of time series of real numbers based on variable-lag Granger causality and transfer entropy. Typically, Granger causality and transfer entropy have an assumption of a fixed and constant time delay between the cause and effect. However, for a non-stationary time series, this assumption is not true. For example, considering two time series of velocity of person A and person B where B follows A. At some time, B stops tying his shoes, then running to catch up A. The fixed-lag assumption is not true in this case. We propose a framework that allows variable-lags between cause and effect in Granger causality and transfer entropy to allow them to deal with variable-lag non-stationary time series. Please see Chainarong Amornbunchornvej, Elena Zheleva, and Tanya Berger-Wolf (2021) <doi:10.1145/3441452> when referring to this package in publications.
'RcppArmadillo' implementation for the Matlab code of the 'Variational Mode Decomposition' and 'Two-Dimensional Variational Mode Decomposition'. For more information, see (i) 'Variational Mode Decomposition' by K. Dragomiretskiy and D. Zosso in IEEE Transactions on Signal Processing, vol. 62, no. 3, pp. 531-544, Feb.1, 2014, <doi:10.1109/TSP.2013.2288675>; (ii) 'Two-Dimensional Variational Mode Decomposition' by Dragomiretskiy, K., Zosso, D. (2015), In: Tai, XC., Bae, E., Chan, T.F., Lysaker, M. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2015. Lecture Notes in Computer Science, vol 8932. Springer, <doi:10.1007/978-3-319-14612-6_15>.
Application of Variational Mode Decomposition based different Machine Learning models for univariate time series forecasting. For method details see (i) K. Dragomiretskiy and D. Zosso (2014) <doi:10.1109/TSP.2013.2288675>; (ii)  Pankaj Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/44138>.
Forecasting univariate time series with Variational Mode Decomposition (VMD) based time delay neural network models.For method details see Konstantin, D.and Dominique, Z. (2014). <doi:10.1109/TSP.2013.2288675>.
A variety of tools to allow the quantification of videos of the 
    lymphatic vasculature taken under an operating microscope. Lymphatic vessels
    that have been injected with a variety of blue dyes can be tracked throughout
    the video to determine their width over time. Code is optimised
    for efficient processing of multiple large video files. Functions to calculate
    physiologically relevant parameters and generate graphs from these values 
    are also included.
Provides fast sampling from von Mises-Fisher distribution using the method proposed by Andrew T.A Wood (1994) <doi:10.1080/03610919408813161>.
Manage, provision and use Virtual Machines pre-configured for R.
             Develop, test and build package in a clean environment.
             'Vagrant' tool and a provider (such as 'Virtualbox') have to be installed.
Variational Autoencoded Multivariate Spatial Fay-Herriot models are designed to efficiently estimate population parameters in small area estimation. This package implements the variational generalized multivariate spatial Fay-Herriot model (VGMSFH) using 'NumPyro' and 'PyTorch' backends, as demonstrated by Wang, Parker, and Holan (2025) <doi:10.48550/arXiv.2503.14710>. The 'vmsae' package provides utility functions to load weights of the pretrained variational autoencoders (VAEs) as well as tools to train custom VAEs tailored to users specific applications.
Data version management on the file system for smaller projects.
    Manage data pipeline outputs with symbolic folder links, structured logging
    and reports, using 'R6' classes for encapsulation and 'data.table' for
    speed. Directory-specific logs used as source of truth to allow portability
    of versioned data folders.
Implements the variable neighborhood trust region search (VNTRS)
    algorithm for nonlinear global optimization, following Bierlaire et al.
    (2009) "A Heuristic for Nonlinear Global Optimization"
    <doi:10.1287/ijoc.1090.0343>. The method combines neighborhood
    exploration with a trust-region framework to search the solution space
    efficiently. It can terminate a local search early when the iterates
    converge toward a previously visited local optimum or when further
    improvement within the current region is unlikely. The algorithm can also
    be used to identify multiple local optima.
Create adjacency matrices of vocalisation graphs from
  dataframes containing sequences of speech and silence intervals,
  transforming these matrices into Markov diagrams, and generating
  datasets for classification of these diagrams by 'flattening' them
  and adding global properties (functionals) etc.  Vocalisation
  diagrams date back to early work in psychiatry (Jaffe and Feldstein,
  1970) and social psychology (Dabbs and Ruback, 1987) but have only
  recently been employed as a data representation method for machine
  learning tasks including meeting segmentation (Luz, 2012)
  <doi:10.1145/2328967.2328970> and classification (Luz,
  2013) <doi:10.1145/2522848.2533788>.
Methods to calculate the expected value of information from a decision-analytic model.  This includes the expected value of perfect information (EVPI), partial perfect information (EVPPI) and sample information (EVSI), and the expected net benefit of sampling (ENBS).  A range of alternative computational methods are provided under the same user interface.  See Heath et al. (2024) <doi:10.1201/9781003156109>, Jackson et al. (2022) <doi:10.1146/annurev-statistics-040120-010730>.
Provides tools for audio data analysis, including feature extraction, pitch detection, and speaker identification. Designed for voice research and signal processing applications.
Simplifies and largely automates practical voice analytics for social science research. This package offers an accessible and easy-to-use interface, including an interactive Shiny app, that simplifies the processing, extraction, analysis, and reporting of voice recording data in the behavioral and social sciences. The package includes batch processing capabilities to read and analyze multiple voice files in parallel, automates the extraction of key vocal features for further analysis, and automatically generates APA formatted reports for typical between-group comparisons in experimental social science research. A more extensive methodological introduction that inspired the development of the 'voiceR' package is provided in Hildebrand et al. 2020 <doi:10.1016/j.jbusres.2020.09.020>.
Random generation, density function and parameter estimation for the Voigt distribution. The main objective of this package is to provide R users with efficient estimation of Voigt parameters using classic iid data in a Bayesian framework. The estimating function allows flexible prior specification, specification of fixed parameters and several options for Markov Chain Monte Carlo posterior simulation. A basic version of the algorithm is described in: Cannas M. and Piras, N. (2025) <doi:10.1007/978-3-031-96303-2_53>.
'R' implementation of the 'vol2bird' software for generating vertical profiles
    of birds and other biological signals in weather radar data. See Dokter et al.
    (2011) <doi:10.1098/rsif.2010.0116> for a paper describing the methodology.
Trading Strategies for high Option Volatility environment are represented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability.
    Guy Cohen (“The Bible of Options Strategies (2nd ed.)”, 2015, ISBN: 9780133964028).
    Zura Kakushadze, Juan A. Serur (“151 Trading Strategies”, 2018, ISBN: 9783030027919).
    John C. Hull (“Options, Futures, and Other Derivatives (11th ed.)”, 2022, ISBN: 9780136939979).
Generates interactive plots for analysing and visualising 
    three-class high dimensional data. It is particularly suited to visualising 
    differences in continuous attributes such as gene/protein/biomarker 
    expression levels between three groups. Differential gene/biomarker 
    expression analysis between two classes is typically shown as a volcano 
    plot. However, with three groups this type of visualisation is particularly 
    difficult to interpret. This package generates 3D volcano plots and 3-way 
    polar plots for easier interpretation of three-class data.
Interactive adverse event (AE) volcano plot for monitoring clinical trial safety. This tool allows users to view the overall distribution of AEs in a clinical trial using standard (e.g. MedDRA preferred term) or custom (e.g. Gender) categories using a volcano plot similar to proposal by Zink et al. (2013) <doi:10.1177/1740774513485311>. This tool provides a stand-along shiny application and flexible shiny modules allowing this tool to be used as a part of more robust safety monitoring framework like the Shiny app from the 'safetyGraphics' R package.
Provides an R interface for 'volesti' C++ package. 'volesti' computes estimations of volume
             of polytopes given by (i) a set of points, (ii) linear inequalities or (iii) Minkowski sum of segments
             (a.k.a. zonotopes). There are three algorithms for volume estimation as well as algorithms
             for sampling, rounding and rotating polytopes. Moreover, 'volesti' provides algorithms for
             estimating copulas useful in computational finance. Methods implemented in 'volesti' are described
             in A. Chalkis and V. Fisikopoulos (2022) <doi:10.32614/RJ-2021-077> and references therein.
Craft polished tables and plots in Markdown reports. 
             Simply choose whether to treat your data as counts or metrics, 
             and the package will automatically generate well-designed default tables and plots for you.
             Boiled down to the basics, with labeling features and simple interactive reports.
             All functions are 'tidyverse' compatible.
Simulates and evaluates stochastic scenarios of death and lapse events in life reinsurance contracts with profit commissions. The methodology builds on materials published by the Institute of Actuaries of Japan <https://www.actuaries.jp/examin/textbook/pdf/modeling.pdf>. A paper describing the detailed algorithms will be published by the author within a few months after the initial release of this package.
Facilitates modeling species' ecological niches and 
  geographic distributions based on occurrences and environments that 
  have a vertical as well as horizontal component, and projecting models 
  into three-dimensional geographic space. Working in three dimensions is 
  useful in an aquatic context when the organisms one wishes to model can 
  be found across a wide range of depths in the water column. The package
  also contains functions to automatically generate marine training
  model training regions using machine learning, and interpolate and smooth
  patchily sampled environmental rasters using thin plate splines.
  Davis Rabosky AR, Cox CL, Rabosky DL, Title PO, Holmes IA, Feldman A, McGuire JA (2016) <doi:10.1038/ncomms11484>.
  Nychka D, Furrer R, Paige J, Sain S (2021) <doi:10.5065/D6W957CT>.
  Pateiro-Lopez B, Rodriguez-Casal A (2022) <https://CRAN.R-project.org/package=alphahull>.
Creates visualization plots for 2D data including ellipse plots, Voronoi tesselation plots, and combined ellipse-Voronoi plots. Designed to visualize class separation in 2D data, raw of from projection techniques like principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) or others. For more details see Lotsch and Kringel (2026) and Lotsch, J., and Kringel, D. (2026) <doi:10.1371/journal.pone.0333653>.
Fortune's (1987, <doi:10.1007/BF01840357>) algorithm is a very efficient method to perform Voronoi tessellation and Delaunay triangulation. This package is a port of the original code published in the early 1990's by Steven Fortune.
The d3.js framework with the plugins d3-voronoi-map, d3-voronoi-treemap and d3-weighted-voronoi
        are used to generate Voronoi treemaps in R and in a shiny application.
        The computation of the Voronoi treemaps are based on Nocaj and Brandes (2012)
        <doi:10.1111/j.1467-8659.2012.03078.x>.
Collects tweets and metadata for threaded conversations and
    generates networks.
A 'Shiny' application for the interactive visualisation and
    analysis of networks that also provides a web interface for collecting
    social media data using 'vosonSML'.
A suite of easy to use functions for collecting social media
    data and generating networks for analysis. Supports Mastodon, YouTube,
    Reddit and Web 1.0 data sources.
Generating realizations of a fractal Brownian function on uniform 1D & 2D grid with classic and generic versions of the Voss algorithm (random sequential additions).
Calculate solar potential for LiDAR point clouds using the 'VOSTOK'
    (Voxel Octree Solar Toolkit) algorithm. This R program provides an interface to
    the original 'VOSTOK' C++ implementation by Bechtold and Hofle (2020), enabling
    efficient ray casting and solar position algorithms to compute solar irradiance
    for each point while accounting for shadowing effects. Integrates seamlessly with
    the 'lidR' package for LiDAR data processing workflows. The original 'VOSTOK'
    toolkit is available at <doi:10.11588/data/QNA02B>.
Counting election votes and determining election results by different methods, including
    the single transferable vote or ranked choice, approval, score, plurality, condorcet and two-round 
    runoff methods (Raftery et al., 2021 <doi:10.32614/RJ-2021-086>).
'ProPublica' <https://projects.propublica.org/represent/> makes United States
    Congress member votes available and has developed their own unique cartogram to visually
    represent this data. Tools are provided to retrieve voting data, prepare voting data 
    for plotting with 'ggplot2', create vote cartograms and theme them.
An R interface to the Project 'VoteSmart'<https://justfacts.votesmart.org/> API.
Various methods to count ballots in voting systems are provided.
	Functions to check validity of ballots are also provided to ensure flexibility.
Calculates voter transitions comparing two elections, using the function solve.QP() in package 'quadprog'.
A R interface to the 'vouch' project
    (<https://github.com/mitchellh/vouch>), which bills itself as "a
    community trust management system based on explicit vouches to
    participate". 'vouch' is a 'Nushell' module, so 'voucher' provides a R
    application programming interface (API) to modify the 'VOUCHED.td'
    database without 'Nushell'. 'voucher' does not depend on 'vouch' or
    'Nushell'.
A wrapper around a CSS library called 'vov.css', intended for use 
  in 'shiny' applications. Simply wrap a UI element in one of the animation 
  functions to see it move.
Procedures for the manipulation, normalization, and plotting of phonetic and sociophonetic vowel formant data.  vowels is the backend for the NORM website.
Tools for 3D point cloud voxelisation, projection, geometrical and morphological description of trees (DBH, height, volume, crown diameter), analyses of temporal changes between different measurement times, distance based clustering and visualisation of 3D voxel clouds and 2D projection. Most analyses and algorithms provided in the package are based on the concept of space exploration and are described in Lecigne et al. (2018, <doi:10.1093/aob/mcx095>).
Visual predictive checks are a commonly used diagnostic plot in pharmacometrics, showing how certain statistics (percentiles) for observed data compare to those same statistics for data simulated from a model. The package can generate VPCs for continuous, categorical, censored, and (repeated) time-to-event data.
Variable Penalty Dynamic Time Warping (VPdtw) for aligning chromatographic signals. With an appropriate penalty this method performs good alignment of chromatographic data without deforming the peaks (Clifford, D., Stone, G., Montoliu, I., Rezzi S., Martin F., Guy P., Bruce S., and Kochhar S.(2009) <doi:10.1021/ac802041e>; Clifford, D. and Stone, G. (2012) <doi:10.18637/jss.v047.i08>).
R functions are not supposed to print text without giving
 the user the option to turn the printing off or on using a Boolean
 'verbose' in a construct like 'if(verbose) print(...)'. But this black/white
 approach is rather rigid, and an approach with shades of gray might be more
 appropriate in many circumstances.
Implements a set of routines to perform structured matrix factorization with minimum volume constraints. The NMF procedure decomposes a matrix X into a product C * D. Given conditions such that the matrix C is non-negative and has sufficiently spread columns, then volume minimization of a matrix D delivers a correct and unique, up to a scale and permutation, solution (C, D). This package provides both an implementation of volume-regularized NMF and "anchor-free" NMF, whereby the standard NMF problem is reformulated in the covariance domain. This algorithm was applied in Vladimir B. Seplyarskiy Ruslan A. Soldatov, et al. "Population sequencing data reveal a compendium of mutational processes in the human germ line". Science, 12 Aug 2021. <doi:10.1126/science.aba7408>. This package interacts with data available through the 'simulatedNMF' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/vrnmf>. The size of the 'simulatedNMF' package is approximately 8 MB.
The goal of 'vroom' is to read and write data (like 'csv',
    'tsv' and 'fwf') quickly. When reading it uses a quick initial
    indexing step, then reads the values lazily , so only the data you
    actually use needs to be read.  The writer formats the data in
    parallel and writes to disk asynchronously from formatting.
A  collection of statistical tests for martingale difference hypothesis, including automatic portmanteau test (Escansiano and Lobato, 2009) <doi:10.1016/j.jeconom.2009.03.001> and automatic variance ratio test (Kim, 2009) <doi:10.1016/j.frl.2009.04.003>.
Performs variable selection/feature reduction under a clustering or 
  classification framework. In particular, it can be used in an automated fashion 
  using mixture model-based methods ('teigen' and 'mclust' are currently supported).
  Can account for mixtures of non-Gaussian distributions via Manly transform (via 'ManlyMix').
  See Andrews and McNicholas (2014) <doi:10.1007/s00357-013-9139-2> and Neal and McNicholas (2023)
  <doi:10.48550/arXiv.2305.16464>.
Methods for calculating the variance scale exponent to
    identify memory patterns in time series data. Includes tests for white
    noise, short memory, and long memory. See Fu, H. et al. (2018)
    <doi:10.1016/j.physa.2018.06.092>.
An implementation of Vasicek and Song goodness-of-fit tests. Several functions are provided to estimate differential Shannon entropy, i.e., estimate Shannon entropy of real random variables with density, and test the goodness-of-fit of some family of distributions, including uniform, Gaussian, log-normal, exponential, gamma, Weibull, Pareto, Fisher, Laplace and beta distributions; see Lequesne and Regnault (2020) <doi:10.18637/jss.v096.c01>.
Penalized weighted least-squares estimate for variable selection on correlated multiply imputed data and penalized estimating equations for generalized linear models with multiple imputation.
  Reference:
  Li, Y., Yang, H., Yu, H., Huang, H., Shen, Y*. (2023) "Penalized estimating equations for generalized linear models with multiple imputation", <doi:10.1214/22-AOAS1721>.
  Li, Y., Yang, H., Yu, H., Huang, H., Shen, Y*. (2023) "Penalized weighted least-squares estimate for variable selection on correlated multiply imputed data", <doi:10.1093/jrsssc/qlad028>.
A wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient, stable, and high confidential variables from omics-based data. Using a bagging strategy in combination of a parametric method or inflection point search method for cut-off threshold determination. This package can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. Luo H, Zhao Q, et al (2020) <doi:10.1126/scitranslmed.aax7533> for more details.
Provides fast spectral estimation of latent factors in random
    dot product graphs using the vsp estimator. Under mild assumptions,
    the vsp estimator is consistent for (degree-corrected) stochastic
    blockmodels, (degree-corrected) mixed-membership stochastic
    blockmodels, and degree-corrected overlapping stochastic blockmodels.
A nonparametric method to estimate Toeplitz covariance matrices from a sample of n independently and identically distributed p-dimensional vectors with mean zero. The data is preprocessed with the discrete cosine matrix and a variance stabilization transformation to obtain an approximate Gaussian regression setting for the log-spectral density function. Estimates of the spectral density function and the inverse of the covariance matrix are provided as well. Functions for simulating data and a protein data example are included. For details see (Klockmann, Krivobokova; 2023), <arXiv:2303.10018>.
Implementation of 'Azure DevOps' <https://azure.microsoft.com/> API calls. 
    It enables the extraction of information about repositories, build and release definitions and individual releases. 
    It also helps create repositories and work items within a project without logging into 'Azure DevOps'. 
    There is the ability to use any API service with a shell for any non-predefined call.
Three steps variable selection procedure based on random forests.
    Initially developed to handle high dimensional data (for which number of
    variables largely exceeds number of observations), the package is very
    versatile and can treat most dimensions of data, for regression and
    supervised classification problems. First step is dedicated to eliminate
    irrelevant variables from the dataset. Second step aims to select all
    variables related to the response for interpretation purpose. Third step
    refines the selection by eliminating redundancy in the set of variables
    selected by the second step, for prediction purpose.
    Genuer, R. Poggi, J.-M. and Tuleau-Malot, C. (2015)
    <https://journal.r-project.org/articles/RJ-2015-018/>.
Bayesian variable selection using shrinkage priors to identify significant variables in high-dimensional datasets. The package includes methods for determining the number of significant variables through innovative clustering techniques of posterior distributions, specifically utilizing the 2-Means and Sequential 2-Means (S2M) approaches. The package aims to simplify the variable selection process with minimal tuning required in statistical analysis.
Automatically generates HTML variable documentation including variable names, labels, classes, value labels (if applicable), value ranges, and summary statistics. See the vignette "vtable" for a package overview.
A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner.
    'vtreat' prepares variables so that data has fewer exceptional cases, making
    it easier to safely use models in production. Common problems 'vtreat' defends
    against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new
    categorical levels (levels seen during application, but not during training). Reference: 
    "'vtreat': a data.frame Processor for Predictive Modeling", Zumel, Mount, 2016, <DOI:10.5281/zenodo.1173313>.
A tool for calculating and drawing "variable trees". Variable trees display information about nested subsets of a data frame. <doi:10.18637/jss.v114.i04>.
An interactive document on  the topic of variance analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at  <https://predanalyticssessions1.shinyapps.io/chisquareVarianceTest/>.
Estimates the type of variables in non-quality controlled data. The prediction is based on a random forest model, trained on over 5000 medical variables with accuracy of 99%. The accuracy can hardy depend on type and coding style of data.
Contains functions for visualization univariate data: ccdplot and qddplot.
Make it easy to use 'vue' in R with helper
              dependency functions and examples.
Contains functions for analysis and summary of tidal datasets. Also provides access to tidal data collected by the National Oceanic and Atmospheric Administration's Center for Operational Oceanographic Products and Services and the Permanent Service for Mean Sea Level. For detailed description and application examples, see Hill, T.D. and S.C. Anisfeld (2021) <doi:10.6084/m9.figshare.14161202.v1> and Hill, T.D. and S.C. Anisfeld (2015) <doi:10.1016/j.ecss.2015.06.004>.
Offers a comprehensive set of assertion tests to help users validate the integrity of their data. 
    These tests can be used to check for specific conditions or properties within a dataset and 
    help ensure that data is accurate and reliable. 
    The package is designed to make it easy to add quality control checks to data analysis 
    workflows and to aid in identifying and correcting any errors or inconsistencies in data.
Provides functions to securely retrieve secrets from a 'Bitwarden Secrets Manager' vault using the 
              'Bitwarden CLI', enabling secret and configuration management within R packages and workflows. 
              For more information visit <https://bitwarden.com/products/secrets-manager/>.
Allow R users to interact with the 'Canvas' Learning Management System (LMS) API (see
    <https://canvas.instructure.com/doc/api/all_resources.html> for details).
    It provides a set of functions to access and manipulate course data, assignments, grades, users, 
    and other resources available through the 'Canvas' API.
Provides a set of functions for data transformations.
    Transformations are performed on character and numeric data. As the scope of the package is
    within Student Analytics, there are functions focused around the academic year.
Provides a user-friendly R 'shiny' app for performing various statistical tests on datasets. 
  It allows users to upload data in numerous formats and perform statistical analyses. 
  The app dynamically adapts its options based on the selected columns and supports both single and multiple column comparisons.
  The app's user interface is designed to streamline the process of selecting datasets, columns, and test options, 
  making it easy for users to explore and interpret their data. The underlying functions for statistical tests are well-organized and can be used independently within other R scripts.
Provides numerous functions to fill data.
    These can be applied either to missing or skewed data.
    The functions are designed within the scope of Student Analytics.
Offers a wide range of functions for reading and writing data in various file formats, 
    including CSV, RDS, Excel and ZIP files. 
    Additionally, it provides functions for retrieving metadata associated with files, 
    such as file size and creation date, making it easy to manage and organize large data sets. 
    This package is designed to simplify data import and export tasks, 
    and provide users with a comprehensive set of tools to work with different types of data files.
Provides a set of functions for manipulating data frames in accordance with specific business rules. 
    In addition, it includes wrapper functions for commonly used functions from the popular 'tidyverse' package, 
    making it easy to integrate these functions into data analysis workflows. 
    The package is designed to streamline data preprocessing and help users quickly and efficiently 
    perform data transformations that are specific to their business needs.
Provides an R interface for interacting with the 'Tableau' Server.
    It allows users to perform various operations such as publishing workbooks, refreshing data extracts, 
    and managing users using the 'Tableau' REST API (see <https://help.tableau.com/current/api/rest_api/en-us/REST/rest_api_ref.htm> for details). Additionally, 
    it includes functions to perform manipulations on local 'Tableau' workbooks.
Provides an R interface for interacting with the 'Semestry TermTime' services.
    It allows users to retrieve scheduling data from the API. see
    <https://github.com/vusaverse/vvtermtime/blob/main/openapi_7.7.0.pdf> for details.
Provides R functions to draw lines and curves with the width
             of the curve allowed to vary along the length of the curve.
Gaze data from the Visual World Paradigm requires significant
    preprocessing prior to plotting and analyzing the data. This package 
    provides functions for preparing visual world eye-tracking data for 
    statistical analysis and plotting. It can prepare data for linear 
    analyses (e.g., ANOVA, Gaussian-family LMER, Gaussian-family GAMM) as
    well as logistic analyses (e.g., binomial-family LMER and binomial-family GAMM).
    Additionally, it contains various plotting functions for creating grand average and
    conditional average plots. See the vignette for samples of the functionality.
    Currently, the functions in this package are designed for handling data
    collected with SR Research Eyelink eye trackers using Sample Reports created
    in SR Research Data Viewer.  While we would like to add functionality 
    for data collected with other systems in the future, the current package is 
    considered to be feature-complete; further updates will mainly entail maintenance
	and the addition of minor functionality.
A reference implementation of the Vertical Weighted Strips method
    explored by Raim, Livsey, and Irimata (2025) <doi:10.48550/arXiv.2401.09696>
    for rejection sampling.
Set of functions that improves the graphical presentations of the functions: wave.correlation and spin.correlation (waveslim package, Whitcher 2012) and the wave.multiple.correlation and wave.multiple.cross.correlation (wavemulcor package, Fernandez-Macho 2012b). The plot outputs (heatmaps) can be displayed in the screen or can be saved as PNG or JPG images or as PDF or EPS formats. The W2CWM2C package also helps to handle the (input data) multivariate time series easily as a list of N elements (times series) and provides a multivariate data set (dataexample) to exemplify its use. A description of the package was published in a scientific paper: Polanco-Martinez and Fernandez-Macho (2014), <doi:10.1109/MCSE.2014.96>.
R interface to a W3C Markup Validation service.
  See <https://validator.w3.org/> for more information.
Provides a set of utility function to prevent the spread of
    utility scripts in W4M (Workflow4Metabolomics) tools, and centralize
    them in a single package.
    To note, some are meant to be replaced by the use of dedicated packages in the future, like
    the parse_args() function: it is here only to prepare the ground for
    more global changes in W4M scripts and tools.
    This package is used by part of the W4M Galaxy modules, some of them  
    being available on the community-maintained GitHub repository for 
    Metabolomics' Galaxy tools <https://github.com/workflow4metabolomics/tools-metabolomics>. 
    See Delporte et al (2025) <doi:10.1002/cpz1.70095> for more details.
Contains inferential and graphical routines for multi-group analysis of while-alive loss (or event) rate for possibly recurrent nonfatal event in the presence of death.
Color palettes taken from the landscapes and cities of Washington 
    state. Colors were extracted from a set of photographs, and then combined to 
    form a set of continuous and discrete palettes.  Continuous palettes were 
    designed to be perceptually uniform, while discrete palettes were chosen to
    maximize contrast at several different levels of overall brightness and 
    saturation. Each palette has been evaluated to ensure colors are 
    distinguishable by colorblind people.
A multivariate weather generator for daily climate variables based 
    on weather-states (Flecher et al. (2010) <doi:10.1029/2009WR008098>). 
    It uses a Markov chain for modeling the succession of weather states. 
    Conditionally to the weather states, the multivariate variables are modeled using the family 
    of Complete Skew-Normal distributions. Parameters are estimated on measured series. Must 
    include the variable 'Rain' and can accept as many other variables as desired.
A user-friendly factor-like interface for converting strings of
    text into numeric vectors and rectangular data structures.
An R interface to the 'WebAIM' 'WAVE' accessibility evaluation
    API <https://wave.webaim.org/api/>. This package provides tools for analyzing web pages for
    accessibility issues, generating reports, and comparing accessibility
    across multiple websites.
Full screen and partial loading screens for 'Shiny' with spinners, progress bars, and notifications.
Generates random data sets including: data.frames, lists,
        and vectors.
Read 'Quake' assets including bitmap images and textures in 'wal' file format. This package also provides support for extracting these assets from 'WAD' and 'PAK' file archives. It can also read models in 'MDL' and 'MD2' formats.
Compare complex R objects and reveal the key differences.
    Designed particularly for use in testing packages where being able to
    quickly isolate key differences makes understanding test failures much
    easier.
Process GPS and accelerometry data to generate walk bouts. A walk bout is a period of activity with accelerometer movement matching the patterns of walking with corresponding GPS measurements that confirm travel. The inputs of the 'walkboutr' package are individual-level accelerometry and GPS data. The outputs of the model are walk bouts with corresponding times, duration, and summary statistics on the sample population, which collapse all personally identifying information. These bouts can be used to measure walking both as an outcome of a change to the built environment or as a predictor of health outcomes such as a cardioprotective behavior. Kang B, Moudon AV, Hurvitz PM, Saelens BE (2017) <doi:10.1016/j.trd.2017.09.026>.
Efficient Bayesian generalized linear models with time-varying coefficients 
    as in Helske (2022, <doi:10.1016/j.softx.2022.101016>). Gaussian, Poisson, and binomial 
    observations are supported. The Markov chain Monte Carlo (MCMC) computations are done using 
    Hamiltonian Monte Carlo provided by Stan, using a state space representation 
    of the model in order to marginalise over the coefficients for efficient sampling. 
    For non-Gaussian models, the package uses the importance sampling type estimators based on 
    approximate marginal MCMC as in Vihola, Helske, Franks (2020, <doi:10.1111/sjos.12492>).
Easily collect walk scores, bike scores, and transit scores (where
    available) from the 'Walk Score' API <https://www.walkscore.com/professional/api.php>, 
    a proprietary API that assigns locations a walkability score between 0 and 100.
A collection of functions to perform the Application
        Programming Interface (API) calls associated with the Walk
        Score website (www.walkscore.com) within the R environment.
        These functions can be used to query the Walk Score and Transit
        Score database for a wide variety of information using R
        scripts. This package includes the simple Walk Score and
        Transit Score API calls, which return the scores associated
        with an input location, as well as calls which return some data
        used to calculate the scores. These functions are especially
        useful for mass data collection and gathering Walk Score and
        Transit Score values for large lists of locations.
The 'shiny' application Wallace is a modular platform for 
    reproducible modeling of species niches and distributions. Wallace
    guides users through a complete analysis, from the acquisition of species
    occurrence and environmental data to visualizing model predictions on an 
    interactive map, thus bundling complex workflows into a single, 
    streamlined interface. An extensive vignette, which guides users through 
    most package functionality can be found on the package's GitHub Pages 
    website: <https://wallaceecomod.github.io/wallace/articles/tutorial-v2.html>.
Datasets from the WallOmics project. Contains phenomics, metabolomics, proteomics and transcriptomics data collected from two organs of five ecotypes of the model plant Arabidopsis thaliana exposed to two temperature growth conditions. Exploratory and integrative analyses of these data are presented in Durufle et al (2020) <doi:10.1093/bib/bbaa166> and Durufle et al (2020) <doi:10.3390/cells9102249>.
A prediction model is calibrated if, roughly, for any percentage x we can expect that x subjects out of 100 experience the event among all subjects that have a predicted risk of x%. A calibration plot provides a simple, yet useful, way of assessing the calibration assumption. The Wally plot consists of a sequence of usual calibration plots. Among the plots contained within the sequence, one is the actual calibration plot which has been obtained from the data and the others are obtained from similar simulated data under the calibration assumption. It provides the investigator with a direct visual understanding of the shape and sampling variability that are common under the calibration assumption. The original calibration plot from the data is included randomly among the simulated calibration plots, similarly to a police lineup. If the original calibration plot is not easily identified then the calibration assumption is not contradicted by the data. The method handles the common situations in which the data contain censored observations and occurrences of competing events.
Provides API access to the Walmart Open API <https://developer.walmartlabs.com/>, 
    that contains data about stores, Value of the day and products which 
    includes names, sale prices, shipping rates and taxonomies.
A toolbox of common robust statistical tests, including robust
  descriptives, robust t-tests, and robust ANOVA. It is also available as a
  module for 'jamovi' (see <https://www.jamovi.org> for more information).
  Walrus is based on the WRS2 package by Patrick Mair, which is in turn based on
  the scripts and work of Rand Wilcox. These analyses are described in depth in
  the book 'Introduction to Robust Estimation & Hypothesis Testing'.
Implements Weighted-Average Least Squares model averaging
    for negative binomial regression models of Huynh (2024) <doi:10.48550/arXiv.2404.11324>,
    generalized linear models of De Luca, Magnus, Peracchi (2018) 
    <doi:10.1016/j.jeconom.2017.12.007> and linear regression models of 
    Magnus, Powell, Pruefer (2010) <doi:10.1016/j.jeconom.2009.07.004>, see also 
    Magnus, De Luca (2016) <doi:10.1111/joes.12094>. Weighted-Average Least Squares
    for the linear regression model is based on the original 'MATLAB' code by 
    Magnus and De Luca <https://www.janmagnus.nl/items/WALS.pdf>, see also 
    Kumar, Magnus (2013) <doi:10.1007/s13571-013-0060-9> and 
    De Luca, Magnus (2011) <doi:10.1177/1536867X1201100402>.
The outcome of various rehabilitation strategies for water distribution systems can be modeled with the Water Management Simulator (WaMaSim). Pipe breaks and the corresponding damage and rehabilitation costs are simulated. It is mainly intended to be used as educational tool for the Water Infrastructure Experimental and Computer Laboratory at ETH Zurich, Switzerland.
'MIME' types are shorthand descriptors for
      file contents and can be determined from "magic"
      bytes in file headers, file contents or intuited
      from file extensions. Tools are provided to
      perform curated "magic" tests as well as mapping
      'MIME' types from a database of over 1,500
      extension mappings.
Provides the functions to perform a Welch's one-way Anova with fixed effects
  based on summary statistics (sample size, means, standard deviation) and the Games-Howell post hoc test
  for multiple comparisons and provides the effect size estimator adjusted omega squared.
  In addition sample size estimation can be computed based on Levy's method, and a Monte Carlo
  simulation is included to bootstrap residual normality and homoscedasticity
  Welch, B. L. (1951) <doi:10.1093/biomet/38.3-4.330>
  Kirk, R. E. (1996) <doi:10.1177/0013164496056005002>
  Carroll, R. M., & Nordholm, L. A. (1975) <doi:10.1177/001316447503500304>
  Albers, C., & Lakens, D. (2018) <doi:10.1016/j.jesp.2017.09.004>
  Games, P. A., & Howell, J. F. (1976) <doi:10.2307/1164979>
  Levy, K. J. (1978a) <doi:10.1080/00949657808810246>
  Show-Li, J., & Gwowen, S. (2014) <doi:10.1111/bmsp.12006>.
Utilities for using a probability sample to reweight prevalence estimates calculated from the All of Us research program. Weighted estimates will still not be representative of the general U.S. population. However, they will provide an early indication for how unweighted estimates may be biased by the sampling bias in the All of Us sample.
It generates the roster of turn for an outlet which is flowing 
        (water) 24X7 or 168 hours towards the area under command or agricutural 
        area (to be irrigated). The area under command is differentially owned 
        by different individual farmers. The Outlet runs for free of cost to 
        irrigate the area under command 24X7.
        So, flow time of the outlet has to be divided based on an area owned by 
        an individual farmer and the location of his land or farm. This roster 
        is known as 'warabandi' and its generation in agriculture practices is a 
        very tedious task. Calculations of time in microseconds are more 
        error-prone, especially whenever it is performed by hands. That division
        of flow time for an individual farmer can be calculated by 'warabandi'. 
        However, it generates a full publishable report for an outlet and all the 
        farmers who have farms subjected to be irrigated. 
        It reduces error risk and makes a more reproducible roster. For more 
        details about warabandi system you can found elsewhere in 
        Bandaragoda DJ(1995) <https://publications.iwmi.org/pdf/H_17571i.pdf>.
Functions aiming to facilitate the analysis of the structure of animal acoustic signals in 'R'. 'warbleR' makes use of the basic sound analysis tools from the packages 'tuneR' and 'seewave', and offers new tools for exploring and quantifying acoustic signal structure. The package allows to organize and manipulate multiple sound files, create spectrograms of complete recordings or individual signals in different formats, run several measures of acoustic structure, and characterize different structural levels in acoustic signals (Araya-Salas et al 2016 <doi:10.1111/2041-210X.12624>).
Toolkit to support and perform discrete event simulations with and without
    resource constraints in the context of health technology assessments (HTA).
    The package focuses on cost-effectiveness modelling and aims to be submission-ready
    to relevant HTA bodies in alignment with 'NICE TSD 15'
    <https://sheffield.ac.uk/nice-dsu/tsds/patient-level-simulation>.
    More details an examples can be found in the package website <https://jsanchezalv.github.io/WARDEN/>.
Provides estimation and inference for while-alive regression models targeting the while-alive loss rate for composite endpoints that include recurrent events and a terminal event. The implementation supports flexible time-varying covariate effects through user-selected time bases, including B-splines, natural splines, M-splines, step functions, truncated linear
    bases, interval-local bases, and piecewise polynomials. Inference can be performed using cluster-robust variance estimators for cluster-randomized trials, with subject-level (IID) variance as a special case. The package includes prediction and plotting utilities and K-fold cross-validation for
    selecting basis and tuning parameters. Methodology is based on Fang et al. (2025) <doi:10.1093/biostatistics/kxaf047>.
Heuristic methods to solve the routing problems in a warehouse management. Package includes several heuristics such as the Midpoint, Return, S-Shape and Semi-Optimal Heuristics for designation of the picker’s route in order picking. The heuristics aim to provide the acceptable travel distances while considering warehouse layout constraints such as aisles and shelves. 
    It also includes implementation of the COPRAS (COmplex PRoportional ASsessment) method for supporting selection of locations to be visited by the picker in shared storage systems. The package is designed to facilitate more efficient warehouse routing and logistics operations.     
    see:
    Bartholdi, J. J.,  Hackman, S. T. (2019). "WAREHOUSE & DISTRIBUTION SCIENCE. Release 0.98.1."
    The Supply Chain & Logistics Institute. H. Milton Stewart School of Industrial and Systems Engineering. 
    Georgia Institute of Technology. 
    <https://www.warehouse-science.com/book/editions/wh-sci-0.98.1.pdf>.
Estimation, simulation, hypothesis testing, AR-order selection,
    and forecasting for univariate higher-order stochastic volatility SV(p)
    models. Supports Gaussian, Student-t, and Generalized Error Distribution
    (GED) innovations, with optional leverage effects. Estimation uses
    closed-form Winsorized ARMA-SV (W-ARMA-SV) moment-based methods that
    avoid numerical optimization. Hypothesis testing includes Local Monte
    Carlo (LMC) and Maximized Monte Carlo (MMC) procedures for leverage
    effects, heavy tails, and autoregressive order. AR-order selection is
    also available via information criteria (BIC/AIC) using the Kalman-filter
    quasi-likelihood and the Hannan-Rissanen ARMA residual variance.
    Forecasting is based on Kalman filtering and smoothing. See Ahsan and
    Dufour (2021) <doi:10.1016/j.jeconom.2021.03.008>, Ahsan, Dufour, and
    Rodriguez-Rondon (2025) <doi:10.1111/jtsa.12851>, and Ahsan, Dufour, and
    Rodriguez-Rondon (2026) <doi:10.34989/swp-2026-8> for details.
Detects perceptions of warmth and competence in American English self-presentation language. Using trained elastic net regression models, this package provides a numerical representation of warmth and competence perceptions. Methods are described here:<https://github.com/bushraguenoun/warmthcompetence/tree/master/paper>.
This estimates precise weaning ages
	for a given skeletal population
	by analyzing the stable nitrogen isotope ratios of them.
	Bone collagen turnover rates estimated anew and
	the approximate Bayesian computation (ABC)
	were adopted in this package.
Infectious disease surveillance requires early outbreak detection. This
    package provides statistical tools for analyzing time-series monitoring 
    data through three core methods: 
    a) EWMA (Exponentially Weighted Moving Average)
    b) Modified-CUSUM (Modified Cumulative Sum)
    c) Adjusted-Serfling models
    Methodologies are based on:
    - Wang et al. (2010) <doi:10.1016/j.jbi.2009.08.003>
    - Wang et al. (2015) <doi:10.1371/journal.pone.0119923>
    Designed for epidemiologists and public health researchers working with
    disease surveillance systems.
Tooling to group dates by a variety of periods including:
    yearly, monthly, by second, by week of the month, and more.  The
    groups are defined in such a way that they also represent the distance
    between dates in terms of the period. This extracts valuable
    information that can be used in further calculations that rely on a
    specific temporal spacing between observations.
Urban water and sanitation survey dataset collected by Water and
    Sanitation for the Urban Poor (WSUP) with technical support from 
    Valid International. These citywide surveys have been collecting data 
    allowing water and sanitation service levels across the entire city to be 
    characterised, while also allowing more detailed data to be collected in 
    areas of the city of particular interest. These surveys are intended to 
    generate useful information for others working in the water and sanitation
    sector. Current release version includes datasets collected from a survey 
    conducted in Dhaka, Bangladesh in March 2017. This survey in Dhaka is one of 
    a series of surveys to be conducted by WSUP in various
    cities in which they operate including Accra, Ghana; Nakuru, Kenya; 
    Antananarivo, Madagascar; Maputo, Mozambique; and, Lusaka, Zambia. This 
    package will be updated once the surveys in other cities are completed and 
    datasets have been made available.
Time series outlier detection with non parametric test. This is a new outlier detection methodology (washer): efficient for time saving elaboration and implementation procedures, adaptable for general assumptions and for needing very short time series, reliable and effective as involving robust non parametric test. You can find two approaches: single time series (a vector) and grouped time series (a data frame). For other informations: Andrea Venturini (2011) Statistica - Universita di Bologna, Vol.71, pp.329-344. For an informal explanation look at R-bloggers on web.
Create plots and tables in a consistent style with WaSHI
    (Washington Soil Health Initiative) branding. Use 'washi' to easily
    style your 'ggplot2' plots and 'flextable' tables.
A toolkit to set up an R data package in a consistent structure. Automates tasks like tidy data export, data dictionary documentation, README and website creation, and citation management.
The wavelet-based variance transformation method is used for system modelling and prediction. It refines predictor spectral representation using Wavelet Theory, which leads to improved model specifications and prediction accuracy. Details of methodologies used in the package can be found in Jiang, Z., Sharma, A., & Johnson, F. (2020) <doi:10.1029/2019WR026962>, Jiang, Z., Rashid, M. M., Johnson, F., & Sharma, A. (2020) <doi:10.1016/j.envsoft.2020.104907>, and Jiang, Z., Sharma, A., & Johnson, F. (2021) <doi:10.1016/J.JHYDROL.2021.126816>.
Provides a set of functions to implement decision-making systems
    based on the W.A.S.P.A.S. method (Weighted Aggregated Sum Product Assessment),
    Chakraborty and Zavadskas (2012) <doi:10.5755/j01.eee.122.6.1810>.
    So this package offers functions that analyze and validate the
    raw data, which must be entered in a determined format;
    extract specific vectors and matrices from this raw database;
    normalize the input data; calculate rankings by intermediate methods;
    apply the lambda parameter for the main method; and a function that does
    everything at once. The package has an example database called choppers,
    with which the user can see how the input data should be organized so that
    everything works as recommended by the decision methods based on multiple
    criteria that this package solves. Basically, the data are composed of a set
    of alternatives, which will be ranked, a set of choice criteria, a matrix
    of values for each Alternative-Criterion relationship, a vector of weights
    associated with the criteria, since certain criteria are considered more
    important than others, as well as a vector that defines each criterion as
    cost or benefit, this determines the calculation formula, as there are those
    criteria that we want the highest possible value (e.g. durability)
    and others that we want the lowest possible value (e.g. price).
Functions to compute Wasserstein barycenters
    of subset posteriors using the swapping algorithm developed by Puccetti, 
    Rüschendorf and Vanduffel (2020) <doi:10.1016/j.jmaa.2017.02.003>. The 
    Wasserstein barycenter is a geometric approach for combining subset 
    posteriors. It allows for parallel and distributed computation of the 
    posterior in case of complex models and/or big datasets, thereby increasing
    computational speed tremendously.
R binding for 'libfswatch', a file system monitoring library.
    Watch files, or directories recursively, for changes in the
    background.  Log activity, or call an R function, upon every change
    event.
Calculates the water balance of starch potatoes from Normalized Distance Vegetation Index (NDVI) images, German Weather Service (DWD) reference evapotranspiration, German Weather Service RADOLAN precipitation data and irrigation information. For more details see Piernicke et al. (2025) <doi:10.3390/rs17183227>.
A not uncommon task for quants is to create 'waterfall charts'. There seems to be no simple way to do this in 'ggplot2' currently. This package contains a single function (waterfall) that simply draws a waterfall chart in a 'ggplot2' object. Some flexibility is provided, though often the object created will need to be modified through a theme.
The main purpose of waterquality is to quickly and easily convert
    satellite-based reflectance imagery into one or many well-known water quality
    algorithms designed for the detection of harmful algal blooms or the following
    pigment proxies: chlorophyll-a, blue-green algae (phycocyanin), and turbidity.
    Johansen et al. (2019) <doi:10.21079/11681/35053>.
Provides Water Year Hydrologic Classification Indices based on measured 
    unimpaired runoff (in million acre-feet). Data is provided by California Department of Water Resources
    and subject to revision.
Wrap-around Time Series (WATS) plots for interrupted time series
    designs with seasonal patterns.
    Longitudinal trajectories are shown in both Cartesian and polar coordinates.
    In many scenarios, a WATS plot more clearly shows the existence and effect size of
    of an intervention.
    This package accompanies
    "Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs"
    by Rodgers, Beasley, & Schuelke (2014)
    <doi:10.1080/00273171.2014.946589>;
    see 'citation("Wats")' for details.
Tools for fitting and simulating mixtures of Watson distributions. 
             The package is described in Sablica, Hornik and Leydold (2026) <doi:10.18637/jss.v115.i04>.
             The random sampling scheme of the package offers two sampling 
             algorithms that are based of the results of Sablica, Hornik and Leydold (2022)
             <doi:10.1080/10618600.2024.2416521>.
             What is more, the package offers a smart tool to combine these two methods,
             and based on the selected parameters, it approximates the relative sampling
             speed for both methods and picks the faster one. In addition, the package
             offers a fitting function for the mixtures of Watson distribution, that
             uses the expectation-maximization (EM) algorithm. Special features are
             the possibility to use multiple variants of the E-step and M-step,
             sparse matrices for the data representation and state of the art methods
             for numerical evaluation of needed special functions using the results of
             Sablica and Hornik (2022) <doi:10.1090/mcom/3690> and 
             Sablica and Hornik (2024) <doi:10.1016/j.jmaa.2024.128262>.
Efficiently read and write Waveform (WAV) audio files <https://en.wikipedia.org/wiki/WAV>. 
  Support for unsigned 8 bit Pulse-code modulation (PCM), signed 12, 16, 24 and 32 bit 
  PCM and other encodings.
Computes Bayesian wavelet shrinkage credible intervals for
	nonparametric regression.
	The method uses cumulants to derive Bayesian credible intervals for
	wavelet regression estimates.
	The first four cumulants of the posterior distribution of the
	estimates are expressed in terms of the observed data and integer
	powers of the mother wavelet functions.
	These powers are closely approximated by linear combinations of
	wavelet scaling functions at an appropriate finer scale.
	Hence, a suitable modification of the discrete wavelet transform allows
	the posterior cumulants to be found efficiently for any data set.
	Johnson transformations then yield the credible intervals themselves.
	Barber, S., Nason, G.P. and Silverman, B.W. (2002)
	<doi:10.1111/1467-9868.00332>.
Makes available code necessary to reproduce figures and
        tables in papers on the WaveD method for wavelet deconvolution
        of noisy signals as presented in The WaveD Transform in R,
        Journal of Statistical Software Volume 21, No. 3, 2007.
The wavelet and ANN technique have been combined to reduce the effect of data noise. This wavelet-ANN conjunction model is able to forecast time series data with better accuracy than the traditional time series model. This package fits hybrid Wavelet ANN model for time series forecasting using algorithm by Anjoy and Paul (2017) <DOI: 10.1007/s00521-017-3289-9>.
Noise in the time-series data significantly affects the accuracy of the ARIMA model. Wavelet transformation decomposes the time series data into subcomponents to reduce the noise and help to improve the model performance. The wavelet-ARIMA model can achieve higher prediction accuracy than the traditional ARIMA model. This package provides Wavelet-ARIMA model for time series forecasting based on the algorithm by Aminghafari and Poggi (2012) and Paul and Anjoy (2018) <doi:10.1142/S0219691307002002> <doi:10.1007/s00704-017-2271-x>.
Wavelet analysis and reconstruction of time series, cross-wavelets and phase-difference (with filtering options), significance with simulation algorithms.
ETS stands for Error, Trend, and Seasonality, and it is a popular time series forecasting method. Wavelet decomposition can be used for denoising, compression, and feature extraction of signals. By removing the high-frequency components, wavelet decomposition can remove noise from the data while preserving important features. A hybrid Wavelet ETS  (Error Trend-Seasonality) model has been developed for time series forecasting using algorithm of Anjoy and Paul (2017) <DOI:10.1007/s00521-017-3289-9>.
Fits the combination of Wavelet-GARCH model for time series forecasting using algorithm by Paul (2015) <doi:10.3233/MAS-150328>.
Wavelet decomposition method is very useful for modelling noisy time series data. Wavelet decomposition using 'haar' algorithm has been implemented to developed hybrid Wavelet GBM (Gradient Boosting Method) model for time series forecasting using algorithm by Anjoy and Paul (2017) <DOI:10.1007/s00521-017-3289-9>.
The employment of the Wavelet decomposition technique proves to be highly advantageous in the modelling of noisy time series data. Wavelet decomposition technique using the "haar" algorithm has been incorporated to formulate a hybrid Wavelet KNN (K-Nearest Neighbour) model for time series forecasting, as proposed by Anjoy and Paul (2017) <DOI:10.1007/s00521-017-3289-9>.
A wavelet-based LSTM model is a type of neural network architecture that uses wavelet technique to pre-process the input data before passing it through a Long Short-Term Memory (LSTM) network. The wavelet-based LSTM model is a powerful approach that combines the benefits of wavelet analysis and LSTM networks to improve the accuracy of predictions in various applications. This package has been developed using the algorithm of Anjoy and Paul (2017) and Paul and Garai (2021) <DOI:10.1007/s00521-017-3289-9> <doi:10.1007/s00500-021-06087-4>.
Wavelet decomposes a series into multiple sub series called detailed and smooth components which helps to capture volatility at multi resolution level by various models. Two hybrid Machine Learning (ML) models (Artificial Neural Network and Support Vector Regression have been used) have been developed in combination with stochastic models, feature selection, and optimization algorithms for prediction of the data. The algorithms have been developed following Paul and Garai (2021)  <doi:10.1007/s00500-021-06087-4>.
Four filters have been chosen namely 'haar', 'c6', 'la8', and 'bl14' (Kindly refer to 'wavelets' in 'CRAN' repository for more supported filters). Levels of decomposition are 2, 3, 4, etc. up to maximum decomposition level which is ceiling value of logarithm of length of the series base 2. For each combination two models are run separately. Results are stored in 'input'. First five metrics are expected to be minimum and last three metrics are expected to be maximum for a model to be considered good. Firstly, every metric value (among first five) is searched in every columns and minimum values are denoted as 'MIN' and other values are denoted as 'NA'. Secondly, every metric (among last three) is searched in every columns and maximum values are denoted as 'MAX' and other values are denoted as 'NA'. 'output' contains the similar number of rows (which is 8) and columns (which is number filter-level combinations) as of 'input'. Values in 'output' are corresponding 'NA', 'MIN' or 'MAX'. Finally, the column containing minimum number of 'NA' values is denoted as the best ('FL'). In special case, if two columns having equal 'NA', it has been checked among these two columns which one is having least 'NA' in first five rows and has been inferred as the best. 'FL_metrics_values' are the corresponding metrics values. 'WARIGAANbest' is the data frame (dimension: 1*8) containing different metrics of the best filter-level combination.  More details can be found in Garai and others (2023) <doi:10.13140/RG.2.2.11977.42087>.
The Wavelet Decomposition followed by Random Forest Regression (RF) models have been applied for time series forecasting. The maximum overlap discrete wavelet transform (MODWT) algorithm was chosen as it works for any length of the series. The series is first divided into training and testing sets. In each of the wavelet decomposed series, the  supervised machine learning approach namely random forest was employed to train the model. This package also provides accuracy metrics in the form of Root Mean Square Error (RMSE) and Mean Absolute Prediction Error (MAPE). This package is based on the algorithm of Ding et al. (2021) <DOI: 10.1007/s11356-020-12298-3>.
Contains functions for computing and plotting
        discrete wavelet transforms (DWT) and maximal overlap discrete
        wavelet transforms (MODWT), as well as their inverses.
        Additionally, it contains functionality for computing and
        plotting wavelet transform filters that are used in the above
        decompositions as well as multiresolution analyses.
The main aim of this package is to combine the advantage of wavelet and support vector machine models for time series forecasting. This package also gives the accuracy measurements in terms of RMSE and MAPE. This package fits the hybrid Wavelet SVR model for time series forecasting The main aim of this package is to combine the advantage of wavelet and Support Vector Regression (SVR) models for time series forecasting. This package also gives the accuracy measurements in terms of Root Mean Square Error (RMSE) and Mean Absolute Prediction Error (MAPE). This package is based on the algorithm of Raimundo and Okamoto (2018) <DOI: 10.1109/INFOCT.2018.8356851>.
Wavelet routines that calculate single sets of wavelet
    multiple regressions and correlations, and cross-regressions and
    cross-correlations from a multivariate time series.  Dynamic versions
    of the routines allow the wavelet local multiple (cross-)regressions
    and (cross-)correlations to evolve over time.
Functions for calculating the
    fetch (length of open water distance along given directions)
    and estimating wave energy from wind and wave monitoring data.
Tools for extracting and analyzing cyclic signals from time series.
Originally designed application in the context of
    resource-limited plant research and breeding programs, 'waves'
    provides an open-source solution to spectral data processing and model
    development by bringing useful packages together into a streamlined
    pipeline.  This package is wrapper for functions related to the
    analysis of point visible and near-infrared reflectance measurements.
    It includes visualization, filtering, aggregation, preprocessing,
    cross-validation set formation, model training, and prediction
    functions to enable open-source association of spectral and reference
    data. This package is documented in a peer-reviewed manuscript in the
    Plant Phenome Journal <doi:10.1002/ppj2.20012>.  Specialized
    cross-validation schemes are described in detail in Jarquín et al.
    (2017) <doi:10.3835/plantgenome2016.12.0130>. Example data is from
    Ikeogu et al. (2017) <doi:10.1371/journal.pone.0188918>.
Spatial data are generally auto-correlated, meaning that if two 
  units selected are close to each other, then it is likely that they share the
  same properties. For this reason, when sampling in the population it is often
  needed that the sample is well spread over space. A new method to draw a sample
  from a population with spatial coordinates is proposed. This method is called
  wave (Weakly Associated Vectors) sampling. It uses the less correlated vector
  to a spatial weights matrix to update the inclusion probabilities vector
  into a sample. For more details see Raphaël Jauslin and Yves Tillé (2019) <doi:10.1007/s13253-020-00407-1>.
Basic wavelet routines for time series (1D), image (2D) and array 
  (3D) analysis.  The code provided here is based on wavelet methodology 
  developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); 
  the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as
  implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002).  
  All figures in chapters 4-7 of GSW (2001) are reproducible using this package 
  and R code available at the book website(s) below.
An integrated wavelet-based spatial time series modelling framework designed to enhance predictive accuracy under noisy and nonstationary conditions by jointly exploiting multi-resolution (wavelet) information and spatial dependence. The package implements WaveSARIMA() (Wavelet Based Spatial AutoRegressive Integrated Moving Average model using regression features with forecast::auto.arima()) and WaveSNN() (Wavelet Based Spatial Neural Network model using neuralnet with hyperparameter search). Both functions support spatial transformation via a user-supplied spatial matrix, lag feature construction, MODWT-based wavelet sub-series feature generation, time-ordered train/test splitting, and performance evaluation (Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared (R²), and Mean Absolute Percentage Error (MAPE)), returning fitted models and actual vs predicted values for train and test sets. The package has been developed using the algorithm of Paul et al. (2023) <doi:10.1007/s43538-025-00581-1>.
Performs 1, 2 and 3D real and complex-valued wavelet transforms,
	nondecimated transforms, wavelet packet transforms, nondecimated
	wavelet packet transforms, multiple wavelet transforms,
	complex-valued wavelet transforms, wavelet shrinkage for
	various kinds of data, locally stationary wavelet time series,
	nonstationary multiscale transfer function modeling, density
	estimation.
Provides scalogram based wavelet tools for time series analysis: wavelet power spectrum, scalogram, windowed scalogram, windowed scalogram difference (see Bolos et al. (2017) <doi:10.1016/j.amc.2017.05.046>), scale index and windowed scale index (Benitez et al. (2010) <doi:10.1016/j.camwa.2010.05.010>).
Computation of approximate potentials for both gradient and non
    gradient fields. It is known from physics that only gradient fields, also
    known as conservative, have a well defined potential function. Here we
    present an algorithm, based on the classical Helmholtz decomposition, to
    obtain an approximate potential function for non gradient fields.
    More information in
    Rodríguez-Sánchez (2020) <doi:10.1371/journal.pcbi.1007788>.
Converts pathways from 'WikiPathways' GPML format or
  'KEGG' KGML format into 'igraph' objects. Includes tools to find all
  cycles in the resulting graphs and determine which ones involve
  negative feedback (inhibition).
Convert, validate, format and elegantly print geographic coordinates and waypoints
   (paired latitude and longitude values) in decimal degrees, degrees and minutes, and degrees,
   minutes and seconds using high performance C++ code to enable rapid conversion and formatting
   of large coordinate and waypoint datasets.
Provides routing based on the 'path-tree' 'Rust' crate. The routing
    is general purpose in the sense that any type of R object can be associated
    with a path, not just a handler function.
Assessing predictive models of spatial data can be
    challenging, both because these models are typically built for
    extrapolating outside the original region represented by training data
    and due to potential spatially structured errors, with "hot spots" of
    higher than expected error clustered geographically due to spatial
    structure in the underlying data. Methods are provided for assessing
    models fit to spatial data, including approaches for measuring the
    spatial structure of model errors, assessing model predictions at
    multiple spatial scales, and evaluating where predictions can be made
    safely. Methods are particularly useful for models fit using the
    'tidymodels' framework. Methods include Moran's I ('Moran' (1950)
    <doi:10.2307/2332142>), Geary's C ('Geary' (1954)
    <doi:10.2307/2986645>), Getis-Ord's G ('Ord' and 'Getis' (1995)
    <doi:10.1111/j.1538-4632.1995.tb00912.x>), agreement coefficients from
    'Ji' and Gallo (2006) (<doi: 10.14358/PERS.72.7.823>), agreement
    metrics from 'Willmott' (1981) (<doi: 10.1080/02723646.1981.10642213>)
    and 'Willmott' 'et' 'al'. (2012) (<doi: 10.1002/joc.2419>), an
    implementation of the area of applicability methodology from 'Meyer'
    and 'Pebesma' (2021) (<doi:10.1111/2041-210X.13650>), and an
    implementation of multi-scale assessment as described in 'Riemann'
    'et' 'al'. (2010) (<doi:10.1016/j.rse.2010.05.010>).
The BACON algorithms are methods for multivariate outlier
    nomination (detection) and robust linear regression by Billor, Hadi,
    and Velleman (2000) <doi:10.1016/S0167-9473(99)00101-2>. The extension
    to weighted problems is due to Beguin and Hulliger (2008)
    <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X200800110616>; see
    also <doi:10.21105/joss.03238>.
Computation of the Wasserstein Bipolarization Index as 
    described in Lee and Sobel (Forthcoming) 
    <doi:10.48550/arXiv.2408.03331>. Provides both 
    asymptotic (Sommerfeld, 2017 
    <https://ediss.uni-goettingen.de/bitstream/handle/11858/00-1735-0000-0023-3FA1-C/DissertationSommerfeldRev.pdf?sequence=1>) 
    and bootstrap methods (Efron and Narasimhan, 2020 
    <doi:10.1080/10618600.2020.1714633>) for calculating 
    confidence intervals.
Access and analyze the World Bank's International Debt Statistics
  (IDS) <https://www.worldbank.org/en/programs/debt-statistics/ids>.
  IDS provides creditor-debtor relationships between countries, regions, and
  institutions. 'wbids' enables users to download, process and work with IDS
  series across multiple geographies, counterparts, and time periods.
Provides efficient implementation of the Wild Binary Segmentation and Binary
    Segmentation algorithms for estimation of the number and locations of
    multiple change-points in the piecewise constant function plus Gaussian
    noise model.
Implements the diagnostic "theta" developed in Poetscher and Preinerstorfer (2020) "How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?" <doi:10.48550/arXiv.2005.04089>, which appeared as <doi:10.1017/S0266466622000184> in Econometric Theory , Volume 39 , Issue 4 , August 2023 , pp. 789 - 847. The diagnostic "theta" can be used to detect and weed out bootstrap-based procedures that provably have size equal to one for a given testing problem. The implementation covers a large variety of bootstrap-based procedures, cf. the above mentioned article for details. A function for computing bootstrap p-values is provided.
Search and download data from the World Bank Data API.
Implements detection for the number and locations of
    the change-points in a time series using the Wild Binary Segmentation and
    the Locally Stationary Wavelet model of Korkas and Fryzlewicz (2017) <doi:10.5705/ss.202015.0262>.
Access and analyze the World Bank's World Development Indicators 
  (WDI) using the corresponding API <https://datahelpdesk.worldbank.org/knowledgebase/articles/889392-about-the-indicators-api-documentation>. 
  WDI provides more than 24,000 country or region-level indicators for various
  contexts. 'wbwdi' enables users to download, process and work with WDI
  series across multiple countries, aggregates, and time periods.
Calculates Windowed Cross Correlation for pairs of time series.
    Provides support for surrogate analysis for nonparametric test of significance.
    Calculates aggregate statistics over a range of parameter values.
    Plots the results as Windowed Cross Correlation plots and heat maps.
    The method is described in "Boker, S. M., Rotondo, J. L., Xu, M., & King, K. (2002). Windowed cross-correlation and peak picking for the analysis of variability in the association between behavioral time series. Psychological Methods, 7(3), 338."
Download and plot education specific demographic data from the Wittgenstein Centre for Demography and Human Capital Data Explorer <https://dataexplorer.wittgensteincentre.org/>.
A flexible method for modeling cumulative effects of time-varying exposures, weighted according to their relative proximity in time, and represented by time-dependent covariates. The current implementation estimates the weight function in the Cox proportional hazards model. The function that assigns weights to doses taken in the past is estimated using cubic regression splines.
Analyze given data frame with multiple endpoints and return Kaplan-Meier survival probabilities together with the specified confidence interval. See Nabipoor M, Westerhout CM, Rathwell S, and Bakal JA (2023) <doi:10.1186/s12874-023-01857-0>.
K-means clustering, hierarchical clustering, and PCA with observational 
    weights and/or variable weights. It also includes the corresponding functions 
    for data nuggets which serve as representative samples of large datasets.
    Cherasia et al., (2022) <doi:10.1007/978-3-031-22687-8_20>. 
    Amaratunga et al., (2009) <doi:10.1002/9780470317129>.
Retrieval the leaf area index (LAI) and soil moisture (SM) from  microwave backscattering data using water cloud model (WCM) model . The WCM algorithm attributed to Pervot et al.(1993) <doi:10.1016/0034-4257(93)90053-Z>. The authors are grateful to SAC, ISRO, Ahmedabad for providing financial support to Dr. Prashant K Srivastava to conduct this research work.
Implements inferential and graphic procedures for the semiparametric proportional 
  means regression of weighted composite endpoint of recurrent event and death (Mao and Lin, 
  2016, <doi:10.1093/biostatistics/kxv050>).
Allows users to create weighted confusion matrices and accuracy
    metrics that help with the model selection process for classification
    problems, where distance from the correct category is important. The
    package includes several weighting schemes which can be parameterized, as
    well as custom configuration options. Furthermore, users can decide
    whether they wish to positively or negatively affect the accuracy score
    as a result of applying weights to the confusion matrix. Functions are
    included to calculate accuracy metrics for imbalanced data. Finally,
    'wconf' integrates well with the 'caret' package, but it can also work
    standalone when provided data in matrix form.
    References:
    Kuhn, M. (2008) "Building Perspective Models in R Using the caret Package"
    <doi:10.18637/jss.v028.i05>
    Monahov, A. (2021) "Model Evaluation with Weighted Threshold Optimization
    (and the mewto R package)" <doi:10.2139/ssrn.3805911>
    Monahov, A. (2024) "Improved Accuracy Metrics for Classification with
    Imbalanced Data and Where Distance from the Truth Matters, with the wconf R
    Package" <doi:10.2139/ssrn.4802336>
    Starovoitov, V., Golub, Y. (2020). New Function for Estimating Imbalanced
    Data Classification Results. Pattern Recognition and Image Analysis, 295–302
    Van de Velden, M., Iodice D'Enza, A., Markos, A., Cavicchia, C. (2023)
    "A general framework for implementing distances for categorical variables"
    <doi:10.48550/arXiv.2301.02190>.
Calculates Pearson, Spearman, polychoric, and polyserial correlation coefficients, in weighted or unweighted form. The package implements tetrachoric correlation as a special case of the polychoric and biserial correlation as a specific case of the polyserial.
A new inverse probability of selection weighted Cox model to deal with outcome-dependent sampling in survival analysis.
Calibrates Bayesian two-stage designs for single-arm phase II trials with
    time-to-event endpoints using a window-cohort with controlled roll-on.
    Interim monitoring is anchored to a locked interim cohort and a
    pre-specified follow-up requirement, so analysis timing remains
    predictable while preserving follow-up maturity. The package searches
    feasible interim rules, optimizes final sample size and decision
    thresholds, evaluates operating characteristics by Monte Carlo simulation,
    and supports exponential, Weibull, log-normal, log-logistic, and
    user-defined baseline survival models. Related published foundations
    include Simon (1989) <doi:10.1016/0197-2456(89)90015-9> and Cotterill and
    Whitehead (2015) <doi:10.1002/sim.6426>.
Standardizes and reconciles scientific plant names against
    a World Checklist of Vascular Plants ('WCVP')-style taxonomic
    backbone. The package parses names into taxonomic components and
    applies staged exact and fuzzy matching for binomial and trinomial
    inputs, including infraspecific rank-aware checks. It also returns
    accepted-name context and row-level matching flags to support
    reproducible, auditable preprocessing for downstream biodiversity,
    spatial, and trait analyses. A user-supplied backbone can be passed
    through 'target_df'; when the optional companion package 'wcvpdata'
    is installed, its default checklist can also be used.
Analyzes and models data subject to sampling biases.
    Provides functions to estimate the density and cumulative distribution
    functions from biased samples of continuous distributions. Includes
    the estimators proposed by Bhattacharyya et al. (1988)
    <doi:10.1080/03610928808829825> and Jones (1991) <doi:10.2307/2337020>
    for density, and by Cox (2005, ISBN:052184939X) and Bose and Dutta
    (2022) <doi:10.1007/s00184-021-00824-3> for distribution, with
    different bandwidth selectors. Also includes a real length-biased
    dataset on shrub width from Muttlak (1988)
    <https://www.proquest.com/openview/3dd74592e623cdbcfa6176e85bd3d390/1?cbl=18750&diss=y&pq-origsite=gscholar>.
Search and download data from over 40 databases hosted by the World Bank, including the World Development Indicators ('WDI'), International Debt Statistics, Doing Business, Human Capital Index, and Sub-national Poverty indicators.
Provides functions to calculate the Water Deficit Index (WDI) and 
    the Evaporative Fraction (EF) using geospatial raster data such as fractional 
    vegetation cover (FVC) and surface-air temperature difference (TS-TA). 
    The package automates regression-based edge fitting and produces continuous 
    spatial maps of surface moisture and evaporative dynamics.
Provides a workflow for exploring World Development Indicators (WDI) country-level panel data. It downloads WDI data using the 'WDI' package and computes diagnostic indices that capture the temporal behaviour of the data by incorporating the grouping structure of the data. The set of diagnostic indices implemented includes variation features, trend and shape features, and sequential temporal features. This method is described in Akinfenwa, Cahill, and Hurley (2025) "'wdiexplorer': An R package Designed for Exploratory Analysis of World Development Indicators (WDI) Data" <doi:10.48550/arXiv.2511.07027>. We adapt the clustering diagnostics and visualisation methodology described in Rousseeuw (1987) <doi:10.1016/0377-0427(87)90125-7> and selected time series features from Hyndman and Athanasopoulos (2021) "Forecasting: Principles and Practice" <https://otexts.com/fpp3/>.
Provides efficient implementations of weighted dependence measures
  and related asymptotic tests for independence. Implemented measures are
  the Pearson correlation, Spearman's rho, Kendall's tau, Blomqvist's beta, and
  Hoeffding's D; see, e.g., Nelsen (2006) <doi:10.1007/0-387-28678-0> and
  Hollander et al. (2015, ISBN:9780470387375).
There are a number of binary files associated with the
    'Webdriver'/'Selenium' project. This package provides functions to download
    these binaries and to manage processes involving them.
Assortativity coefficients, centrality measures, 
    and clustering coefficients for weighted and directed networks.
    Rewiring unweighted networks with given assortativity coefficients.
    Generating general preferential attachment networks.
Functions for finding and pulling data from the
  'Wisconsin Department of Natural Resources ArcGIS REST APIs'
  <https://dnrmaps.wi.gov/arcgis/rest/services> and 
  <https://dnrmaps.wi.gov/arcgis2/rest/services>.
Fetch and clean data from the World Database on Protected
    Areas (WDPA) and the World Database on Other Effective Area-Based
    Conservation Measures (WDOECM). Data is obtained from Protected Planet
    <https://www.protectedplanet.net/en>. To augment data cleaning procedures,
    users can install the 'prepr' R package (available at
    <https://github.com/prioritizr/prepr>). For more information on this
    package, see Hanson (2022) <doi:10.21105/joss.04594>.
Implements weighted double score matching (WDSM) for estimating
    population-level causal effects from complex survey data. Combines
    propensity scores and prognostic scores with survey design weights for
    matching, survey-weighted imputation within match sets, and Hajek
    normalization to target the population average treatment effect (PATE) and
    the population average treatment effect on the treated (PATT). Supports
    both retrospective (treatment-dependent) and prospective
    (treatment-independent) sampling designs. Achieves double robustness:
    consistent estimation when either the propensity score or prognostic score
    model is correctly specified. Provides polynomial sieve bias correction
    and linearization-based multinomial bootstrap variance estimation that
    preserves the survey-weighted matching structure without re-matching.
    Methods are described in Zeng, Tong, Tong, Lu, Mukherjee, and Li
    (2026, under review) "Where to weight? Estimating population causal
    effects with weighted double score matching in complex surveys".
Numerous time series admit autoregressive moving average (ARMA)
  representations, in which the errors are uncorrelated but not necessarily
  independent.
  These models are called weak ARMA by opposition to the standard ARMA models, 
  also called strong ARMA models, in which the error terms are supposed to be 
  independent and identically distributed (iid).
  This package allows the study of nonlinear time series models through weak 
  ARMA representations.
  It determines identification, estimation and validation for ARMA models and 
  for AR and MA models in particular. 
  Functions can also be used in the strong case.
  This package also works on white noises by omitting arguments 'p', 'q', 'ar'
  and 'ma'.
  See Francq, C. and Zakoïan, J. (1998) <doi:10.1016/S0378-3758(97)00139-0> and 
  Boubacar Maïnassara, Y. and Saussereau, B. (2018)
  <doi:10.1080/01621459.2017.1380030> for more details.
Weather indices represent the overall weekly effect of a weather variable on crop yield throughout the cropping season. This package contains functions that can convert the weekly weather data into yearly weighted Weather indices with weights being the correlation coefficient between weekly weather data over the years and crop yield over the years. This can be done for an individual weather variable and for two weather variables at a time as the interaction effect. This method was first devised by Jain, RC, Agrawal R, and Jha, MP (1980), "Effect of climatic variables on rice yield and its forecast",MAUSAM, 31(4), 591–596, <doi:10.54302/mausam.v31i4.3477>. Later, the method have been used by various researchers and the latest can found in Gupta, AK, Sarkar, KA, Dhakre, DS, & Bhattacharya, D (2022), "Weather Based Potato Yield Modelling using Statistical and Machine Learning Technique",Environment and Ecology, 40(3B), 1444–1449,<https://www.environmentandecology.com/volume-40-2022>.
High-level tools to attach gridded weather data from the NASA POWER Project
    to event-based datasets. The package plans efficient spatio-temporal API calls via the 'nasapower'
    R package, caches downloaded segments locally, and joins weather variables back to the input
    table using exact or rolling joins. This package is not affiliated with or endorsed by NASA.
Functions to convert between weather metrics, including conversions
    for metrics of temperature, air moisture, wind speed, and precipitation.
    This package also includes functions to calculate the heat index from
    air temperature and air moisture.
Provides automated downloading, parsing and formatting of
    weather data for Australia through API endpoints provided by the
    Department of Primary Industries and Regional Development (DPIRD) of
    Western Australia and by the Science and Technology Division of the
    Queensland Government's Department of Environment and Science (DES).
    As well as the Bureau of Meteorology (BOM) of the Australian
    government precis and coastal forecasts,
    and downloading and importing radar and satellite imagery files.
    DPIRD weather data are accessed through public APIs provided by
    DPIRD, <https://www.dpird.wa.gov.au/online-tools/apis/>, providing
    access to weather station data from the DPIRD weather station
    network.  Australia-wide weather data are based on data from the
    Australian Bureau of Meteorology (BOM) data and accessed through
    SILO (Scientific Information for Land Owners) Jeffrey et al. (2001)
    <doi:10.1016/S1364-8152(01)00008-1>.  DPIRD data are made available
    under a Creative Commons Attribution 3.0 Licence (CC BY 3.0 AU)
    license <https://creativecommons.org/licenses/by/3.0/au/deed.en>.
    SILO data are released under a Creative Commons Attribution 4.0
    International licence (CC BY 4.0)
    <https://creativecommons.org/licenses/by/4.0/>. BOM data are (c)
    Australian Government Bureau of Meteorology and released under a
    Creative Commons (CC) Attribution 3.0 licence or Public Access Licence
    (PAL) as appropriate, see
    <https://www.bom.gov.au/copyright> for further details.
A comprehensive suite of functions for processing,
  analyzing, and visualizing textual data from tweets is offered.  
  Users can clean tweets, analyze their sentiments, visualize data, 
  and examine the correlation between sentiments and environmental 
  data such as weather conditions. Main features include text processing,  
  sentiment analysis, data visualization, correlation analysis, and 
  synthetic data generation. Text processing involves cleaning and preparing  
  tweets by removing textual noise and irrelevant words. Sentiment analysis 
  extracts and accurately analyzes sentiments from tweet texts using advanced 
  algorithms. Data visualization creates various charts like word clouds
  and sentiment polarity graphs for visual representation of data. Correlation 
  analysis examines and calculates the correlation between tweet sentiments 
  and environmental variables such as weather conditions. Additionally, 
  random tweets can be generated for testing and evaluating the performance 
  of analyses, empowering users to effectively analyze and interpret 'Twitter' 
  data for research and commercial purposes.
Download daily weather data recorded at airport weather stations using the National Centers for Environmental Information (NCEI) API <https://www.ncei.noaa.gov/support/access-search-service-api-user-documentation>.
Enables interaction with the National Weather Service application programming web-interface for fetching of real-time and forecast meteorological data. Users can provide latitude and longitude, Automated Surface Observing System identifier, or Automated Weather Observing System identifier to fetch recent weather observations and recent forecasts for the given location or station. Additionally, auxiliary functions exist to identify stations nearest to a point, convert wind direction from character to degrees, and fetch active warnings. Results are returned as simple feature objects whenever possible.
Provides Apache and IIS log analytics for transaction performance, client populations and workload definitions.
Chemical information from around the web. This package interacts 
    with a suite of web services for chemical information. Sources include: Alan
    Wood's Compendium of Pesticide Common Names, Chemical Identifier Resolver,
    ChEBI, Chemical Translation Service, ChemSpider, ETOX, Flavornet,
    NIST Chemistry WebBook, OPSIN, PubChem, SRS, Wikidata.
An easy-to-use interface for interacting with 'WebDAV' servers,
    including 'OwnCloud'. It simplifies the use of 'WebDAV' methods such as COPY, MOVE, DELETE and others. 
    With built-in authentication and request handling, it allows for easy
    management of files and directories over the 'WebDAV' protocol.
Organizational framework for web development in R including functions to  
    serve static and dynamic content via HTTP methods, includes the html5 package to
    create HTML pages, and offers other utility functions for common tasks related 
    to web development.
A client for the 'WebDriver' 'API'. It allows driving a
    (probably headless) web browser, and can be used to test web
    applications, including 'Shiny' apps. In theory it works with any
    'WebDriver' implementation, but it was only tested with 'PhantomJS'.
Functions for easily creating interactive web pages using
    'R Markdown' that students can use in self-guided learning.
Create a web app that makes it easier to test web clients
    without using the internet. It includes a web app framework with path
    matching, parameters and templates. Can parse various 'HTTP' request
    bodies. Can send 'JSON' data or files from the disk. Includes a web
    app that implements the 'httpbin.org' web service.
The web version WebGestalt <https://www.webgestalt.org> supports 12 organisms, 354 gene identifiers and 321,251 function categories. Users can upload the data and functional categories with their own gene identifiers. In addition to the Over-Representation Analysis, WebGestalt also supports Gene Set Enrichment Analysis and Network Topology Analysis. The user-friendly output report allows interactive and efficient exploration of enrichment results. The WebGestaltR package not only supports all above functions but also can be integrated into other pipeline or simultaneously analyze multiple gene lists.
Displays geospatial data on an interactive 3D globe in the web browser.
Creates interactive web maps using the 'JavaScript' 'Leaflet'
    library with base layers of 'The National Map' ('TNM'). 'TNM' services
    provide access to base geospatial information that describes the landscape
    of the United States and its territories. This package is dependent on, and
    intended to be used with, the 'leaflet' package.
Stubbing and setting expectations on 'HTTP' requests.
    Includes tools for stubbing 'HTTP' requests, including expected
    request conditions and response conditions. Match on
    'HTTP' method, query parameters, request body, headers and
    more. Can be used for unit tests or outside of a testing
    context.
Lossless webp images are 26% smaller in size compared to PNG. Lossy
    webp images are 25-34% smaller in size compared to JPEG. This package reads
    and writes webp images into a 3 (rgb) or 4 (rgba) channel bitmap array using
    conventions from the 'jpeg' and 'png' packages.
This is a collection of tools for conducting both basic and advanced statistical power analysis including correlation, proportion, t-test, one-way ANOVA, two-way ANOVA, linear regression, logistic regression, Poisson regression, mediation analysis, longitudinal data analysis, structural equation modeling and multilevel modeling. It also serves as the engine for conducting power analysis online at <https://webpower.psychstat.org>.
Several analysis-related functions for the book entitled
    "Web-based Analysis without R in Your Computer"(written in Korean, ISBN 978-89-5566-185-9)
    by Keon-Woong Moon. The main function plot.htest() shows the distribution of statistic for
    the object of class 'htest'.
R is used by a vast array of people for a vast array of purposes
    - including web analytics. This package contains functions for consuming and
    munging various common forms of request log, including the Common and Combined
    Web Log formats and various Amazon access logs.
A collection of tools to fit and work with trophic Species Distribution Models. Trophic Species Distribution Models combine knowledge of trophic interactions with Bayesian structural equation models that model each species as a function of its prey (or predators) and environmental conditions. It exploits the topological ordering of the known trophic interaction network to predict species distribution in space and/or time, where the prey (or predator) distribution is unavailable. The method implemented by the package is described in Poggiato, Andréoletti, Pollock and Thuiller (2022) <doi:10.22541/au.166853394.45823739/v1>.
Functions that allow for accessing domains and a number of search engines.
Takes screenshots of web pages, including Shiny applications and R
    Markdown documents.
Takes screenshots of web pages, including Shiny applications
    and R Markdown documents. 'webshot2' uses headless Chrome or Chromium
    as the browser back-end.
Provides a 'WebSocket' client interface for R.
    'WebSocket' is a protocol for low-overhead real-time communication:
    <https://en.wikipedia.org/wiki/WebSocket>.
Data structures and methods to work with web tracking data. The functions cover data preprocessing steps, enriching web tracking data with external information and methods for the analysis of digital behavior as used in several academic papers (e.g., Clemm von Hohenberg et al., 2023 <doi:10.17605/OSF.IO/M3U9P>; Stier et al., 2022 <doi:10.1017/S0003055421001222>).
A Stata-style `webuse()` function for importing named datasets from Stata's online collection.
Parses http request data in application/json, multipart/form-data, 
    or application/x-www-form-urlencoded format. Includes example of hosting
    and parsing html form data in R using either 'httpuv' or 'Rhttpd'.
Provides functions to create factor variables with contrasts based on weighted effect coding, and their interactions. In weighted effect coding the estimates from a first order regression model show the deviations per group from the sample mean. This is especially useful when a researcher has no directional hypotheses and uses a sample from a population in which the number of observation per group is different.
Makes research involving EMDAT and related datasets easier. These Datasets are manually filled and have several formatting and compatibility issues. Weed aims to resolve these with its functions.
Provides functions for analysing Water-Energy-Food-Nutrient-Carbon
    (WEFNC) nexus interactions in agricultural production systems. Includes
    functions for computing water use efficiency (WUE), water productivity (WP),
    and water footprint (WF) including green, blue, and grey components following
    the methodology of Hoekstra et al. (2011, ISBN:9781849712798). Includes energy
    budgeting tools for energy use efficiency (EUE), energy return on investment
    (EROI), net energy (NE), and energy productivity (EP). Computes nutrient use
    efficiency (NUE) metrics including agronomic efficiency (AE), physiological
    efficiency (PE), recovery efficiency (RE), and partial factor productivity
    (PFP) as defined by Dobermann (2007)
    <https://digitalcommons.unl.edu/agronomyfacpub/316/> and
    Congreves et al. (2021) <doi:10.3389/fpls.2021.637108>. Estimates carbon
    footprint (CF), greenhouse gas (GHG) emissions, soil organic carbon (SOC)
    stocks, and global warming potential (GWP) using Intergovernmental Panel on
    Climate Change (IPCC) Sixth Assessment Report (AR6) default values
    (CH4 = 27, N2O = 273) as reported in Forster et al. (2021)
    <doi:10.1017/9781009157896.009>. Computes composite
    Water-Energy-Food-Nutrient-Carbon (WEFNC) nexus indices,
    trade-off correlation matrices, and generates radar and heatmap
    visualizations for comparing agricultural treatments. Supports conservation
    agriculture (CA), irrigated and rain-fed systems, and arid and semi-arid
    production environments. Methods follow Lal (2004)
    <doi:10.1016/j.envint.2004.03.005> for carbon emissions from farm
    operations, and Hoover et al. (2023) <doi:10.1016/j.scitotenv.2022.160992>
    for water use efficiency indicators.
Calculates the WEGE (Weighted Endemism including Global 
    Endangerment index) index for a particular area. Additionally it also 
    calculates rasters of KBA's (Key Biodiversity Area) criteria (A1a, A1b, A1e, 
    and B1), Weighted endemism (WE), the EDGE (Evolutionarily Distinct and
    Globally Endangered) score, Evolutionary Distinctiveness (ED) and Extinction
    risk (ER). Farooq, H., Azevedo, J., Belluardo F., Nanvonamuquitxo, C.,
    Bennett, D., Moat, J., Soares, A., Faurby, S. & Antonelli, A. (2020)
    <doi:10.1101/2020.01.17.910299>.
A utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.
Provides a single function to fit data of an input data frame into one of the selected Weibull functions (w2, w3 and it's truncated versions), calculating the scale, location and shape parameters accordingly. The resulting plots and files are saved into the 'folder' parameter provided by the user. References: a) John C. Nash, Ravi Varadhan (2011). "Unifying Optimization Algorithms to Aid Software System Users: optimx for R" <doi:10.18637/jss.v043.i09>.
Provides maximum likelihood estimation methods for eight modified 
    Weibull-type distributions. It returns parameter estimates, 
    log-likelihood, AIC, and BIC, and also supports model fitting, validation, 
    and comparison across different distributional forms. These methods can be 
    applied to reliability, survival, and lifetime data analysis, making the package 
    useful for researchers and practitioners in statistics, engineering, and medicine. 
    The following distributions are included: Rangoli2023, Peng2014, Lai2003, Xie1996, 
    Sarhan2009, Rangoli2025, Mustafa2012, and Alwasel2009.
Conducts a goodness-of-fit test for the Weibull distribution (referred to as the weibullness test) and furnishes parameter estimations for both the two-parameter and three-parameter Weibull distributions. Notably, the threshold parameter is derived through correlation from the Weibull plot. Additionally, this package conducts goodness-of-fit assessments for the exponential, Gumbel, and inverse Weibull distributions, accompanied by parameter estimations.
  For more details, see Park (2017) <doi:10.23055/ijietap.2017.24.4.2848>, 
  Park (2018) <doi:10.1155/2018/6056975>, and Park (2023) <doi:10.3390/math11143156>. 
  This work was supported by the National Research Foundation of Korea (NRF) grants funded by 
  the Korea government (MSIT) (No. 2022R1A2C1091319, RS-2023-00242528).
Life data analysis in the graphical tradition of Waloddi Weibull. Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson (1982, ISBN: 9780471094586), William Q. Meeker and  Lois A. Escobar (1998, ISBN: 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986).
Graphical data analysis of accelerated life tests. Methods derived from  Wayne Nelson (1990, ISBN: 9780471522775), William Q. Meeker and  Lois A. Escobar (1998, ISBN: 1-471-14328-6).
Providing quantitative tools for input estimation, portfolio construction, and performance evaluation.
Estimates high-dimensional multivariate normal copula regression models with the weighted composite likelihood estimating equations in Nikoloulopoulos (2023) <doi:10.1016/j.csda.2022.107654>. It provides autoregressive moving average correlation structures and binary, ordinal, Poisson, and negative binomial regressions.
Clusters state sequences and weighted data. It provides an optimized weighted PAM algorithm as well as functions for aggregating replicated cases, computing cluster quality measures for a range of clustering solutions, sequence analysis typology validation using parametric bootstraps and plotting (fuzzy) clusters of state sequences. It further provides a fuzzy and crisp CLARA algorithm to cluster large database with sequence analysis, and a methodological framework for Robustness Assessment of Regressions using Cluster Analysis Typologies (RARCAT).
The weighted ensemble method is a valuable approach for combining forecasts. This algorithm employs several optimization techniques to generate optimized weights. This package has been developed using algorithm of Armstrong (1989) <doi:10.1016/0024-6301(90)90317-W>.
R interface to the 'weightederm' package for 'Python', which
    provides 'scikit-learn'-style estimators for offline change point
    regression (data segmentation) via weighted empirical risk minimization.
    Supports least-squares, Huber, and logistic losses with fixed or
    cross-validated numbers of change points. Wraps 'Python' via 'reticulate'.
    Arpino and Venkataramanan (2026) <doi:10.48550/arXiv.2604.11746>.
A conditional independence test that can be applied both to
    univariate and multivariate random variables. The test is based on a
    weighted form of the sample covariance of the residuals after a
    nonlinear regression on the conditioning variables. Details are
    described in Scheidegger, Hoerrmann and Buehlmann (2022) "The Weighted
    Generalised Covariance Measure" <http://jmlr.org/papers/v23/21-1328.html>.
    The test is a generalisation of the Generalised Covariance Measure (GCM)
    implemented in the R package 'GeneralisedCovarianceMeasure' by Jonas Peters and
    Rajen D. Shah based on Shah and Peters (2020) "The Hardness of
    Conditional Independence Testing and the Generalised Covariance
    Measure" <doi:10.1214/19-AOS1857>.
An implementation of the Weighted Portmanteau Tests described
      in "New Weighted Portmanteau Statistics for Time Series Goodness-of-Fit Testing"
      published by the Journal of the American Statistical Association, Volume 107, 
      Issue 498, pages 777-787, 2012.
Performs a sensitivity analysis using weighted rank tests in observational studies with I blocks of size J; see Rosenbaum (2024) <doi:10.1080/01621459.2023.2221402>.  The package can perform adaptive inference in block designs; see Rosenbaum (2012) <doi:10.1093/biomet/ass032>.  The package can increase design sensitivity using the conditioning tactic in Rosenbaum (2025) <doi:10.1093/jrsssb/qkaf007>.  The main functions are wgtRank(), wgtRankCI(), wgtRanktt() and wgtRankC().
Fast computation of
 Receiver Operating Characteristic (ROC) curves
 and Area Under the Curve (AUC)
 for weighted binary classification problems
 (weights are example-specific cost values).
The weighted scores method and composite likelihood information criteria as an intermediate step for variable/correlation selection for longitudinal ordinal and count data in Nikoloulopoulos, Joe and Chaganty (2011)  <doi:10.1093/biostatistics/kxr005>, Nikoloulopoulos (2016) <doi:10.1002/sim.6871> and Nikoloulopoulos (2017) <arXiv:1510.07376>.
Provides survival analysis functions with support for time-dependent 
    and subject-specific (e.g., propensity score) weighting. Implements weighted 
    estimation for Cox models, Kaplan-Meier survival curves, and treatment 
    differences with point-wise and simultaneous confidence bands. Includes 
    restricted mean survival time (RMST) comparisons evaluated across all 
    potential truncation times with both point-wise and simultaneous confidence 
    bands. See Cole, S. R. & Hernán, M. A. (2004) 
    <doi:10.1016/j.cmpb.2003.10.004> for methodological background.
Treemaps are a visually appealing graphical representation of
    numerical data using a space-filling approach. A plane or 'map' is
    subdivided into smaller areas called cells.  The cells in the map are
    scaled according to an underlying metric which allows to grasp the
    hierarchical organization and relative importance of many objects at
    once. This package contains two different implementations of treemaps,
    Voronoi treemaps and Sunburst treemaps.  The Voronoi treemap function
    subdivides the plot area in polygonal cells according to the highest
    hierarchical level, then continues to subdivide those parental cells
    on the next lower hierarchical level, and so on. The Sunburst treemap
    is a computationally less demanding treemap that does not require
    iterative refinement, but simply generates circle sectors that are
    sized according to predefined weights.  The Voronoi tesselation is
    based on functions from Paul Murrell (2012)
    <https://www.stat.auckland.ac.nz/~paul/Reports/VoronoiTreemap/voronoiTreeMap.html>.
Provides tools for weighted spatial tessellation using
    Euclidean and geodesic distances within constrained polygonal domains.
    The package can generate complete and connected spatial partitions
    that respect complex boundaries, heterogeneous point weights, and optional
    resistance or terrain effects. The methods extend weighted Voronoi
    tessellations to constrained domains and graph-based cost-distance
    surfaces. For background see Aurenhammer (1991)
    <doi:10.1145/116873.116880> and van Etten (2017)
    <doi:10.18637/jss.v076.i13>.
Generates balancing weights for causal effect estimation in observational studies with
             binary, multi-category, or continuous point or longitudinal treatments by easing and
             extending the functionality of several R packages and providing in-house estimation methods.
             Available methods include those that rely on parametric modeling, optimization, and machine learning. Also
             allows for assessment of weights and checking of covariate balance by interfacing directly
             with the 'cobalt' package. Methods for estimating weighted regression models that take into account 
             uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how
             to install any optional package 'WeightIt' uses, including those that may not be on CRAN.
Applies the item weighting method from Kilic & Dogan (2019) <doi:10.21031/epod.516057>. To improve construct validity, this method re-computes scores by utilizing the item discrimination index in conjunction with a condition established upon person ability and item difficulty.
Estimation of observation-specific weights for incomplete longitudinal data and bootstrap procedure for weighted quantile regressions. See Jacqmin-Gadda, Rouanet, Mba, Philipps, Dartigues (2020) for details <doi:10.1177/0962280220909986>.
Estimates the Vevea and Hedges (1995)
    weight-function model. By specifying arguments, users can
    also estimate the modified model described in Vevea and Woods (2005), 
    which may be more practical with small datasets. Users 
    can also specify moderators to estimate a linear model. 
    The package functionality allows users to easily extract the 
    results of these analyses as R objects for other uses. In addition, 
    the package includes a function to launch both models as 
    a Shiny application. Although the Shiny application is also available online, 
    this function allows users to launch it locally if they choose.
Provides a variety of functions for producing simple weighted statistics, such as weighted Pearson's correlations, partial correlations, Chi-Squared statistics, histograms, and t-tests as well as simple weighting graphics including weighted histograms, box plots, bar plots, and violin plots.  Also includes software for quickly recoding survey data and plotting estimates from interaction terms in regressions (and multiply imputed regressions) both with and without weights and summarizing various types of regressions. Some portions of this package were assisted by AI-generated suggestions using OpenAI's GPT model, with human review and integration.
Functions for subject/instance weighted support vector machines (SVM). 
    It uses a modified version of 'libsvm' and is compatible with package 'e1071'. It also allows user defined kernel matrix.
All functions and data sets required for the examples in the book
    Hyndman (2026) "That's Weird: Anomaly Detection Using R" <https://OTexts.com/weird/>.
    All packages needed to run the examples are also loaded.
Provides computational support for flow over weirs, such as sharp-crested, broad-crested, and embankments. Initially, the package supports broad- and sharp-crested weirs.
Estimates the standard and weighted Elo (WElo, Angelini et al., 2022 <doi:10.1016/j.ejor.2021.04.011>) rates. The current version provides Elo and WElo rates for tennis, according to different systems of weights (games or sets) and scale factors (constant, proportional to the number of matches, with more weight on Grand Slam matches or matches played on a specific surface). Moreover, the package gives the possibility of estimating the (bootstrap) standard errors for the rates. Finally, the package includes betting functions that automatically select the matches on which place a bet.
Run mixed-effects models that include weights at every level. The WeMix package fits a weighted mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. Both linear and logit models are supported. Models may have up to three levels. Random effects are estimated using the PIRLS algorithm from 'lme4pureR' (Walker and Bates (2013) <https://github.com/lme4/lme4pureR>).
Palettes generated mostly from 'Wes Anderson' movies.
Implements a functional approximation of the four panel
    cointegration tests developed by Westerlund (2007)
    <doi:10.1111/j.1468-0084.2007.00477.x>. The tests are based on structural
    rather than residual dynamics and allow for heterogeneity in both the
    long-run cointegrating relationship and the short-run dynamics. The package
    includes logic for automated lag and lead selection via AIC/BIC, Bartlett 
    kernel long-run variance estimation, and a bootstrap procedure to handle 
    cross-sectional dependence. It also includes a bootstrapping distribution
    visualization function for diagnostic purposes.
The distributions of the weight of evidence (log Bayes factor) favouring case over noncase status in a test dataset (or test folds generated by cross-validation) can be used to quantify the performance of a diagnostic test. This package can be used with any test dataset on which you have computed prior probabilities of case status, posterior probabilities of case status, and you have the observed case-control status.  In comparison with the C-statistic (area under ROC curve), the expected weight of evidence (expected information for discrimination) has several advantages as a summary measure of predictive performance. To quantify how the predictor will behave as a risk stratifier, the quantiles of the distributions of weight of evidence in cases and controls can be calculated and plotted.
Computes exact observation weights for the Kalman filter and smoother, following Koopman and Harvey (2003) <www.sciencedirect.com/science/article/pii/S0165188902000611>.
    The package provides tools for analyzing linear Gaussian state-space models,
    allowing users to quantify the contribution of individual observations to
    filtered and smoothed state estimates. These weights can be used for
    interpretation, decomposition, and diagnostic analysis in time series models,
    including applications such as dynamic factor models. See the README for examples.
A suite of routines for Weyl algebras.  Notation follows
   Coutinho (1995, ISBN 0-521-55119-6, "A Primer of Algebraic
   D-Modules").  Uses 'disordR' discipline
   (Hankin 2022 <doi:10.48550/arXiv.2210.03856>).  To cite
   the package in publications, use Hankin
   2022 <doi:10.48550/arXiv.2212.09230>.
Manage skills for large language model coding agents. Supports
    installing skills from 'GitHub' or local directories, tracking versions in
    a lock file, and keeping installations current. Installations can be scoped
    to a single project or shared globally across projects.
Provides a computationally efficient way of fitting
	     weighted linear fixed effects estimators for causal
	     inference with various weighting schemes. Weighted linear
	     fixed effects estimators can be used to estimate the
	     average treatment effects under different identification
	     strategies. This includes stratified randomized
	     experiments, matching and stratification for
	     observational studies, first differencing, and
	     difference-in-differences. The package implements methods
	     described in Imai and Kim (2017) "When should We Use
	     Linear Fixed Effects Regression Models for Causal
	     Inference with Longitudinal Data?", available at
	     <https://imai.fas.harvard.edu/research/FEmatch.html>.
Implementation of Weighted Fast Greedy algorithm for community detection in networks with mixed types of attributes.
Provides a large English words list and tools to find words by patterns. In particular, anagram finder and scrabble word finder.
Provides a convenient data set, a set of helper functions, and a benchmark function for
    economically (profit) driven wind farm layout optimization. This enables researchers in the field
    of the NP-hard (non-deterministic polynomial-time hard) problem of wind farm layout optimization
    to focus on their optimization methodology contribution and also provides a realistic benchmark
    setting for comparability among contributions. See Croonenbroeck, Carsten & Hennecke, David (2020)
    <doi:10.1016/j.energy.2020.119244>.
A computationally efficient whole genome approach to detecting and estimating significant QTL in linkage maps using the flexible linear mixed modelling functionality of ASReml-R.
Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.
Provides function, wget_set(), to change the method (default to 'wget -c') using in download.file().
  Using 'wget -c' allowing continued downloading, which is especially useful for slow internet connection and for downloading large files.
  User can run wget_unset() to restore previous setting.
Functions for determining the effect of data weights on the variance of survey data: users will load a data set which has a weights column, and the package will calculate the design effect (DEFF), weighting loss, root design effect (DEFT), effective sample size (ESS), and/or weighted margin of error.
An enhanced implementation of Whittaker-Henderson smoothing for the graduation 
    of one-dimensional and two-dimensional actuarial tables used to quantify Life Insurance risks.
    'WH' is based on the methods described in Biessy (2025) <doi:10.48550/arXiv.2306.06932>.
    Among other features, it generalizes the original smoothing algorithm to maximum likelihood estimation, 
    automatically selects the smoothing parameter(s) and extrapolates beyond the range of data.
Provides tools for simulating the biophysical effects of vessel-strikes on whales. The aim is to support the evaluation of marine policies limiting ship speeds through regions in which whales reside. This is important because ship strikes are a major source of lethality for several whale species, including the critically endangered North Atlantic right whale. In this analysis, whales are modelled with a four-layer system comprising skin, blubber, sub-layer (muscle or organ) and bone. Reasonable values for the material properties of these layers, along with other factors such as whale surface area and mass, are provided for a variety of whale species. Similarly, key values are provided for several ship types.  The collision is modelled according to Newtonian dynamics, with stresses and strains within the whale layers being simulated over time. The simulation results are analyzed in the context of whale-strike data, to develop a Lethality Index for the whale in the modelled collision.  For the underlying science, see Kelley and other "Assessing the Lethality of Ship Strikes on Whales Using Simple Biophysical Models." (2021) <doi:10.1111/mms.12745>. For more on the R code, see Kelley "`whalestrike`: An R package for simulating ship strikes on whales" (2024) <doi:10.21105/joss.06473>.
Provides an 'R' interface to the 'Whapi' 'API' <https://whapi.cloud>, enabling sending and receiving 'WhatsApp' messages directly from 'R'. Functions include sending text, images, documents, stickers, geographic locations, and interactive messages (buttons and lists). Also includes 'webhook' parsing utilities and channel health checks.
Inferences about counterfactuals are essential for prediction,
      answering what if questions, and estimating causal effects.
      However, when the counterfactuals posed are too far from the data at
      hand, conclusions drawn from well-specified statistical analyses
      become based largely on speculation hidden in convenient modeling
      assumptions that few would be willing to defend. Unfortunately,
      standard statistical approaches assume the veracity of the model
      rather than revealing the degree of model-dependence, which makes this
      problem hard to detect. 'WhatIf' offers easy-to-apply methods to
      evaluate counterfactuals that do not require sensitivity testing over
      specified classes of models. If an analysis fails the tests offered
      here, then we know that substantive inferences will be sensitive to at
      least some modeling choices that are not based on empirical evidence,
      no matter what method of inference one chooses to use. 'WhatIf'
      implements the methods for evaluating counterfactuals discussed in
      Gary King and Langche Zeng, 2006, "The Dangers of Extreme
      Counterfactuals," Political Analysis 14 (2) <DOI:10.1093/pan/mpj004>;
      and Gary King and Langche Zeng, 2007, "When Can History Be Our Guide? The
      Pitfalls of Counterfactual Inference," International Studies
      Quarterly 51 (March) <DOI:10.1111/j.1468-2478.2007.00445.x>.
Simulates the results of completed randomized controlled
    trials, as if they had been conducted as adaptive Multi-Arm Bandit
    (MAB) trials instead. Augmented inverse probability weighted
    estimation (AIPW), outlined by Hadad et al. (2021)
    <doi:10.1073/pnas.2014602118>, is used to robustly estimate the
    probability of success for each treatment arm under the adaptive
    design. Provides customization options to simulate perfect/imperfect
    information, stationary/non-stationary bandits, blocked treatment
    assignments, along with control augmentation, and other hybrid
    strategies for assigning treatment arms. The methods used in
    simulation were inspired by Offer-Westort et al.  (2021)
    <doi:10.1111/ajps.12597>.
Imports 'WhatsApp' chat logs and parses them into
    a usable dataframe object. The parser works on chats exported 
    from Android or iOS phones and on Linux, macOS and Windows. The parser has  multiple options for extracting smileys and emojis
    from the messages, extracting URLs and domains from the messages, extracting names and types of sent 
    media files from the messages, extracting timestamps from messages, extracting and anonymizing author 
    names from messages. Can be used to create anonymized versions of data.
Use the 'what3words' API 
    <https://developer.what3words.com/public-api> to return three words which 
    uniquely identify every 3m x 3m square on Earth. It is also possible to 
    return coordinates from any valid three words location. Supports multiple 
    languages.
Builds complex plots, heatmaps in particular, using natural semantics. Bigger plots can be assembled using directives such as 'LeftOf', 'RightOf', 'TopOf', and 'Beneath' and more. Other features include clustering, dendrograms and integration with 'ggplot2' generated grid objects. This package is particularly designed for bioinformaticians to assemble complex plots for publication.
In Multidimensional Systems the When dimension allows us to
    express when the analysed facts have occurred. The purpose of this
    package is to provide support for implementing this dimension in the
    form of date and time tables for Relational On-Line Analytical Processing 
    star database systems.
A set of tools for processing and analyzing data developed in the
    context of the "Who Has Eaten the Planet" (WHEP) project, funded by the
    European Research Council (ERC). For more details on multi-regional
    input–output model "Food and Agriculture Biomass Input–Output" (FABIO) see 
    Bruckner et al. (2019) <doi:10.1021/acs.est.9b03554>.
Provides a clean syntax for vectorising the use of
    Non-Standard Evaluation (NSE), for example in 'ggplot2', 'dplyr', or
    'data.table'.
Robust and reliable functions to return informative outputs to 
        console with the run or source location of a command. This can be from
        the  'RScript'/R terminal commands or 'RStudio' console, source editor, 
        'Rmarkdown' document and a Shiny application.
Retrieve geographical information for airports using their IATA or ICAO codes.
Set of tools for manipulating gas exchange data from cardiopulmonary exercise testing.
Logging of scripts suitable for clinical trials using
    'Quarto' to create nice human readable logs. 'whirl' enables
    execution of scripts in batch, while simultaneously creating logs for
    the execution of each script, and providing an overview summary log of
    the entire batch execution.
Speech-to-text transcription using a native R 'torch' implementation
    of 'OpenAI' 'Whisper' model <https://github.com/openai/whisper>. Supports
    multiple model sizes from tiny (39M parameters) to large-v3 (1.5B parameters)
    with integrated download from 'HuggingFace' <https://huggingface.co/> via the
    'hfhub' package. Provides automatic speech recognition with optional language
    detection and translation to English. Audio preprocessing, mel spectrogram
    computation, and transformer-based encoder-decoder inference are all
    implemented in R using the 'torch' package.
An R frontend for the 'WhiteboxTools' library, which is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. 'WhiteboxTools' can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. 'WhiteboxTools' also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. Suggested citation: Lindsay (2016) <doi:10.1016/j.cageo.2016.07.003>.
A collection of functions related to novel methods for estimating R(t), 
  created by the lab of Professor Laura White. Currently implemented methods include 
  two-step Bayesian back-calculation and now-casting for line-list data with missing reporting delays, 
  adapted in 'STAN' from Li (2021) <doi:10.1371/journal.pcbi.1009210>, 
  and calculation of time-varying reproduction number assuming a flux between various adjacent states, adapted into 'STAN' from 
  Zhou (2021) <doi:10.1371/journal.pcbi.1010434>.
Implements the whitening methods (ZCA, PCA, Cholesky,
 ZCA-cor, and PCA-cor) discussed in Kessy, Lewin, and Strimmer (2018)
 "Optimal whitening and decorrelation", <doi:10.1080/00031305.2016.1277159>,
 as well as the whitening approach to canonical correlation analysis allowing
 negative canonical correlations described in Jendoubi and Strimmer (2019)
 "A whitening approach to probabilistic canonical correlation analysis for omics
 data integration", <doi:10.1186/s12859-018-2572-9>. The package also offers
 functions to simulate random orthogonal matrices, compute (correlation) loadings
 and explained variation. It also contains four example data sets (extended UCI 
 wine data, TCGA LUSC data, nutrimouse data, extended pitprops data).
Formal implementation of White test of heteroskedasticity and a bootstrapped version of it, developed under the methodology of Jeong, J., Lee, K. (1999) <https://yonsei.pure.elsevier.com/en/publications/bootstrapped-whites-test-for-heteroskedasticity-in-regression-mod>.
Shinohara (2014) <doi:10.1016/j.nicl.2014.08.008>
    introduced 'WhiteStripe', an intensity-based normalization of T1 
    and T2 images, where normal 
    appearing white matter performs well, but requires segmentation.
    This method performs white matter mean and standard deviation
    estimates on data that has been rigidly-registered to the 'MNI'
    template and uses histogram-based methods.
Provides methods for retrieving United States Geological Survey (USGS) water data using sequential and parallel processing (Bengtsson, 2022 <doi:10.32614/RJ-2021-048>). In addition to parallel methods, data wrangling and additional statistical attributes are provided.
This is a small, lightweight package that lets users investigate the distribution of genotypes in genotype-by-sequencing (GBS) data where they expect (by and large) Hardy-Weinberg equilibrium, in order to assess rates of genotyping errors and the dependence of those rates on read depth.  It implements a Markov chain Monte Carlo (MCMC) sampler using 'Rcpp' to compute a Bayesian estimate of what we call the heterozygote miscall rate for restriction-associated digest (RAD) sequencing data and other types of reduced representation GBS data. It also provides functions to generate plots of expected and observed genotype frequencies. Some background on these topics can be found in a recent paper "Recent advances in conservation and population genomics data analysis" by Hendricks et al. (2018) <doi:10.1111/eva.12659>, and another paper describing the MCMC approach is in preparation with Gordon Luikart and Thierry Gosselin.
Look up the username and full name of the current user,
    the current user's email address and 'GitHub' username,
    using various sources of system and configuration information.
The Model Disability Survey (MDS) <https://www.who.int/activities/collection-of-data-on-disability> is a World Health Organization (WHO) general population survey
    instrument to assess the distribution of disability within a country or 
    region, grounded in the International Classification of Functioning, 
    Disability and Health <https://www.who.int/standards/classifications/international-classification-of-functioning-disability-and-health>. This package provides fit-for-purpose functions 
    for calculating and presenting the results from this survey, as used by 
    the WHO. The package primarily provides functions for implementing
    Rasch Analysis (see Andrich (2011) <doi:10.1586/erp.11.59>) to
    calculate a metric scale for disability.
Implements the 2019 World Health Organization (WHO) cardiovascular 
    disease (CVD) risk prediction models, as described in Kaptoge et al. (2019) 
    <doi:10.1016/S2214-109X(19)30318-3>. Provides two validated models for 
    estimating 10-year risk of fatal and non-fatal cardiovascular events 
    (myocardial infarction and stroke): a laboratory-based model using age, sex, 
    systolic blood pressure, total cholesterol, smoking status, and diabetes 
    history; and a non-laboratory-based model substituting body mass index (BMI) 
    for cholesterol and diabetes, suitable for resource-limited settings. Risk 
    estimates are recalibrated to 21 Global Burden of Disease regions using 
    region-specific incidence rates and risk factor distributions derived from 
    the Emerging Risk Factors Collaboration. Functions are fully vectorized for 
    efficient batch calculations and support automatic country-to-region mapping 
    via ISO 3166-1 alpha-3 country codes.
Interactive tools for generating random samples. Users select an
    .xlsx, .csv, or delimited .txt file with population data and are walked through selecting the
    sample type (Simple Random Sample or Stratified), the number of backups
    desired, and a "stratify_on" value (if desired). The sample size is determined
    using a normal approximation to the hypergeometric distribution based on
    Nicholson (1956) <doi:10.1214/aoms/1177728270>. An .xlsx file is created
    with the sample and key metadata for reference. It is menu-driven and lets
    users pick an output directory. See vignettes for a detailed walk-through.
Tools to download data from the online World Inequality Database directly into R. The World Inequality
    Database is an extensive source on the historical evolution of the
    distribution of income and wealth both within and between countries.
    It relies on the combined effort of an international network of over a
    hundred researchers covering more than seventy countries from all continents.
Computationally easy modeling, interpolation, forecasting of massive temporal-spacial data.
Construct a Canonical Variate Analysis Biplot via the Generalised Singular Value Decomposition, for cases when the number of samples is less than the number of variables. For more information on biplots, see Gower JC, Lubbe SG, Le Roux NJ (2011) <doi:10.1002/9780470973196> and for more information on the generalised singular value decomposition, see Edelman A, Wang Y (2020) <doi:10.1137/18M1234412>.
Provides two functions 'frameableWidget()', and 'frameWidget()'.
  The 'frameableWidget()' is used to add extra code to a 'htmlwidget' which
  allows is to be rendered correctly inside a responsive 'iframe'.
  The 'frameWidget()' is a 'htmlwidget' which displays content of another 'htmlwidget'
  inside a responsive 'iframe'.
  These functions allow for easier embedding of 'htmlwidgets' in content management systems
  such as 'wordpress', 'blogger' etc.
  They also allow for separation of widget content from main HTML content where
  CSS of the main HTML could interfere with the widget.
Interface to the World Inequality Database (WID) API <https://wid.world>. Downloads distributional national accounts data with filters for country, year, percentile, age group, and population type. Includes code validation and reference tables. Independent implementation unaffiliated with the World Inequality Lab (WIL) or the Paris School of Economics.
Encapsulates the pattern of untidying data into a wide
    matrix, performing some processing, then turning it back into a tidy
    form. This is useful for several operations such as co-occurrence
    counts, correlations, or clustering that are mathematically convenient
    on wide matrices.
The german Wikibook "GNU R" introduces R to new users. This package is a collection of functions and datas used in the german WikiBook "GNU R".
Query Wikidata and get facts from current and historic Wikipedia main pages.
Scrape lake metadata tables from Wikipedia <https://www.wikipedia.org/>.
A wrapper for the MediaWiki API, aimed particularly at the
    Wikimedia 'production' wikis, such as Wikipedia. It can be used to retrieve
    page text, information about users or the history of pages, and elements of
    the category tree.
Queries online 'WikiPathway' graphics and allows mapping user data (e.g., expression values) on the graph. The package designs a grammar of graphic syntax that using pipe operator to add graphic layer.
'Taxonomic' information from 'Wikipedia', 'Wikicommons',
    'Wikispecies', and 'Wikidata'. Functions included for getting
    taxonomic information from each of the sources just listed, as
    well performing taxonomic search.
A set of wrappers intended to check, read and download information from the Wikimedia sources. It is specifically created to work with names of celebrities, in which case their information and statistics can be downloaded. Additionally, it also builds links and snippets to use in combination with the function gallery() in netCoin package.
Access 'Wikipedia' through the several 'MediaWiki' APIs
    (<https://www.mediawiki.org/wiki/API>), as well as through the
    'XTools' API (<https://www.mediawiki.org/wiki/XTools/API>). Ensure
    your API calls are correct, and receive results in tidy tibbles.
An implementation of the 1-Sample Wilcoxon Sign rank test for medians. 
              It includes 2 functions, W_stat(), which computes the 
              exact probabilities of the Wilcoxon Sign Rank Test Statistic, W.
              The second function, Wilcox.m.test() allows the user to conduct the
              1-Sample Wilcoxon Sign Rank hypothesis test for medians, this also 
              allows the user to conduct the hypothesis test for the normal approximation, 
              based on the techniques of Bickel and Doksum (1973, ISBN:013850363X).
Dynamic interaction refers to spatial-temporal associations in the movements of two (or more) animals. This package provides tools for calculating a suite of indices used for quantifying dynamic interaction with wildlife telemetry data. For more information on each of the methods employed see the references within. The package (as of version >= 0.3) also has new tools for automating contact analysis in large tracking datasets. The package (as of version 1.0) uses the 'move2' class of objects for working with tracking dataset.
Conducts single coefficient tests and multiple-contrast hypothesis tests of meta-regression models using cluster wild bootstrapping, based on methods examined in Joshi, Pustejovsky, and Beretvas (2022) <DOI:10.1002/jrsm.1554>.
Provides insight into how the best hand for a poker game changes based on the game dealt, players who stay in until the showdown and wildcards added to the base game.  At this time the package does not support player tactics, so draw poker variants are not included.
Tool-set of modules for creating web-based applications that use plot based strategies to visualize and analyze multi-omics data.
    This package utilizes the 'shiny' and 'plotly' frameworks to provide a user friendly dashboard for interactive plotting.
Obtain the native stack trace and fuse it with R's
    stack trace for easier debugging of R packages with native code.
Post-construction fatality monitoring studies at wind
    facilities are based on data from searches for bird and bat carcasses
    in plots beneath turbines. Bird and bat carcasses can fall outside of
    the search plot. Bird and bat carcasses from wind turbines often fall
    outside of the searched area. To compensate, area correction (AC)
    estimations are calculated to estimate the percentage of fatalities
    that fall within the searched area versus those that fall outside of
    it. This package provides two likelihood based methods and one physics
    based method (Hull and Muir (2010)
    <doi:10.1080/14486563.2010.9725253>, Huso and Dalthorp (2014)
    <doi:10.1002/jwmg.663>) to estimate the carcass fall distribution.
    There are also functions for calculating the proportion of area
    searched within one unit annuli, log logistic distribution functions,
    and truncated distribution functions.
Provides a tool to fit and compare the wind turbine power curves 
    with successful curve fitting techniques. Facilitates to examine and compare 
    the performance of a user-defined power curve fitting techniques. 
    Also, provide features to generate power curve discrete points from a graphical 
    power curves. Data on the power curves of the wind turbine from major 
    manufacturers are provided.
Analysing convergent evolution using the Wheatsheaf index, described in Arbuckle et al. (2014) <doi: 10.1111/2041-210X.12195>, and some other unrelated but perhaps useful functions.
Evaluation of prediction performance of smaller regions of
    spectra for Chemometrics. Segmentation of spectra, evolving dimensions
    regions and sliding windows as selection methods. Election of the best
    model among those computed based on error metrics. Chen et al.(2017)
    <doi:10.1007/s00216-017-0218-9>.
Collect multichannel marketing data from sources such as Google analytics, Facebook Ads, and many others using the 'Windsor.ai' API <https://www.windsor.ai/api-fields/>.
Computes inequality measures of a given variable taking into account weights. Suitable for ratio, interval and ordered scale. Includes Gini, Theil, Leti index, Palma ratio, 20:20 ratio, Allison and Foster index, Jenkins index, Cowell and Flechaire index, Abul Naga and Yalcin index, Apouey index, Blair and Lacy index. Bootstrap provides distribution of inequality measures enabling significance tests.
Obtain information on peak flow data from the National River Flow Archive (NRFA) in the United Kingdom, either from the Peak Flow Dataset files <https://nrfa.ceh.ac.uk/data/peak-flow-dataset> once these have been downloaded to the user's computer or using the NRFA's API. These files are in a format suitable for direct use in the 'WINFAP' software, hence the name of the package.
Generate continuous maps of genetic diversity using moving windows with options for rarefaction, interpolation, and masking as described in Bishop et al. (2023) <doi:10.1111/2041-210X.14090>.
Using a time-varying random parameters model developed in
    Koutchade et al., (2024) <https://hal.science/hal-04318163>, this
    package allows allocating variable input costs among crops produced by
    farmers based on panel data including information on input expenditure
    aggregated at the farm level and acreage shares. It also considers in
    fairly way the weighting data and can allow integrating time-varying
    and time-constant control variables.
A multi-visit clinical trial may collect participant responses on an ordinal scale and may utilize a stratified design, such as randomization within centers, to assess treatment efficacy across multiple visits. Baseline characteristics may be strongly associated with the outcome, and adjustment for them can improve power. The win ratio (ignores ties) and the win odds (accounts for ties) can be useful when analyzing these types of data from randomized controlled trials. This package provides straightforward functions for adjustment of the win ratio and win odds for stratification and baseline covariates, facilitating the comparison of test and control treatments in multi-visit clinical trials. For additional information concerning the methodologies and applied examples within this package, please refer to the following publications:
	1. Weideman, A.M.K., Kowalewski, E.K., & Koch, G.G. (2024). “Randomization-based covariance adjustment of win ratios and win odds for 	randomized multi-visit studies with ordinal outcomes.” Journal of Statistical Research, 58(1), 33–48. <doi:10.3329/jsr.v58i1.75411>.
	2. Kowalewski, E.K., Weideman, A.M.K., & Koch, G.G. (2023). “SAS macro for randomization-based methods for covariance and stratified adjustment 	of win ratios and win odds for ordinal outcomes.” SESUG 2023 Proceedings, Paper 139-2023.
Calculate the win ratio for prioritized outcomes and the 95% confidence interval based on Bebu and Lachin (2016) <doi:10.1093/biostatistics/kxv032>. Three type of outcomes can be analyzed: survival "failure-time" events, repeated survival "failure-time" events and continuous or ordinal "non-failure time" events that are captured at specific time-points in the study.
Calculate the win statistics (win ratio, net benefit and win odds) for prioritized multiple endpoints, plot the win statistics and win proportions over study time if at least one time-to-event endpoint is analyzed, and simulate datasets with dependent endpoints. The package can handle any type of outcomes (continuous, ordinal, binary, time-to-event) and allow users to perform stratified analysis, inverse probability of censoring weighting (IPCW) and inverse probability of treatment weighting (IPTW) analysis.
Performs an analysis of time-to-event clinical trial data using various "win time" methods, 
  including 'ewt', 'ewtr', 'rmt', 'ewtp', 'rewtp', 'ewtpr', 'rewtpr', 'max', 'wtr', 'rwtr', 'pwt', and 'rpwt'. These methods are used to calculate and compare 
  treatment effects on ordered composite endpoints. The package handles event times, event indicators, and treatment 
  arm indicators and supports calculations on observed and resampled data. Detailed explanations of each method and 
  usage examples are provided in "Use of win time for ordered composite endpoints in clinical trials," by Troendle et al. 
  (2024)<https://pubmed.ncbi.nlm.nih.gov/38417455/>. For more information, see the package documentation or the vignette titled "Introduction to wintime."
Implementation of the weighted iterative proportional fitting (WIPF) procedure for updating/adjusting a N-dimensional array given a weight structure and some target marginals.
   Acknowledgements:
   The author wish to thank Conselleria de Educación, Cultura, Universidades y Empleo (grant CIAICO/2023/031), Ministerio de Ciencia, Innovación y Universidades (grant PID2021-128228NB-I00) and Fundación Mapfre (grant 'Modelización espacial e intra-anual de la mortalidad en España. Una herramienta automática para el cálculo de productos de vida') for supporting this research.
Builds a joint probabilistic forecast across series and horizons using adaptive copulas (Gaussian/t) with shrinkage-repaired correlations. At the low level it calls a probabilistic mixer per series and horizon, which backtests several simple predictors, predicts next-window Continuous Ranked Probability Score (CRPS), and converts those scores into softmax weights to form a calibrated mixture (r/q/p/dfun). The mixer blends eight simple predictors: a naive predictor that wraps the last move in a PERT distribution; an arima predictor using auto.arima for one-step forecasts; an Exponentially Weighted Moving Average (EWMA) gaussian predictor with mean/variance under a Gaussian; a historical bootstrap predictor that resamples past horizon-aligned moves; a drift residual bootstrap predictor combining linear trend with bootstrapped residuals; a volatility-scaled naive predictor centering on the last move and scaling by recent volatility; a robust median mad predictor using median/MAD with Laplace or Normal shape; and a shrunk quantile predictor that fits a few quantile regressions over time and interpolates to a full predictive. The function then couples the per-series mixtures on a common transform (additive/multiplicative/log-multiplicative), simulates coherent draws, and returns both transformed- and level-scale samplers and summaries.
In the course of a genome-wide association study, the situation often arises that some phenotypes are known with greater precision than others.
    It could be that some individuals are known to harbor more micro-environmental variance than others.
    In the case of inbred strains of model organisms, it could be the case that more organisms were observed from some strains than others, so the strains with more organisms have better-estimated means.
    Package 'wISAM' handles this situation by allowing for weighting of each observation according to residual variance.
    Specifically, the 'weight' parameter to the function conduct_scan() takes the precision of each observation (one over the variance).
Provides functions for computing moments and coefficients related to the Beta-Wishart and Inverse Beta-Wishart distributions. 
    It includes functions for calculating the expectation of matrix-valued functions of the Beta-Wishart distribution, 
    coefficient matrices C_k and H_k, expectation of matrix-valued functions of the inverse Beta-Wishart distribution, 
    and coefficient matrices \tilde{C}_k and \tilde{H}_k. For more details, refer Hillier and Kan (2024) <https://www-2.rotman.utoronto.ca/~kan/papers/wishmom.pdf>, 
    "On the Expectations of Equivariant Matrix-valued Functions of Wishart and Inverse Wishart Matrices".
Adds ... to a function's argument list so that it can
    tolerate non-matching arguments.
Lets you temporarily execute an expression or a local block with a different here() root in the 'here' package. This is useful for sourcing code in other projects which expect the root directory of here() to be the project directory of those projects. This may be the case with git submodules for example.
A set of functions to run code 'with' safely and temporarily
    modified global state. Many of these functions were originally a part
    of the 'devtools' package, this provides a simple package with limited
    dependencies to provide access to these functions.
A comprehensive data analysis framework for NIH-funded research that streamlines workflows for both data cleaning and preparing NIH Data Archive ('NDA') submission templates. Provides unified access to multiple data sources ('REDCap', 'MongoDB', 'Qualtrics', 'SQL', 'ORACLE') through interfaces to their APIs, with specialized functions for data cleaning, filtering, merging, and parsing. Features automatic validation, field harmonization, and memory-aware processing to enhance reproducibility in multi-site collaborative research as described in Mittal et al. (2021) <doi:10.20900/jpbs.20210011>.
Provides a minimal R and C++ API for parsing
  well-known binary and well-known text representation of
  geometries to and from R-native formats.
  Well-known binary is compact
  and fast to parse; well-known text is human-readable
  and is useful for writing tests. These formats are
  useful in R only if the information they contain can be
  accessed in R, for which high-performance functions
  are provided here.
Utility functions to convert between the 'Spatial' classes
  specified by the package 'sp', and the well-known binary '(WKB)'
  representation for geometry specified by the 'Open Geospatial Consortium'.
  Supports 'Spatial' objects of class 'SpatialPoints',
  'SpatialPointsDataFrame', 'SpatialLines', 'SpatialLinesDataFrame',
  'SpatialPolygons', and 'SpatialPolygonsDataFrame'. Supports 'WKB' geometry
  types 'Point', 'LineString', 'Polygon', 'MultiPoint', 'MultiLineString', and
  'MultiPolygon'. Includes extensions to enable creation of maps with
  'TIBCO Spotfire'.
Establishes and maintains vertex pool topology for geometry 
    handled by 'wk'. Segments are the atomic unit, vertices are shared via
    integer references into a pool. Topology is made discoverable via coincident
    vertex detection while not requiring modification of the input data. 
    Topological data models follow principles described in Worboys and
    Duckham (2004, ISBN:978-0415283755). The edge-based topology geometry decomposed 
    into vertices and directed edge pairs is a simplification of the quad-edge case in
    Guibas & Stolfi (1985) <doi:10.1145/282918.282923>.
Converts weekly data to monthly data.
     Users can use three types of week formats: ISO week, epidemiology week (epi week) and calendar date.
It proposes a novel variable selection approach in classification problem that takes into account the correlations that may exist between the predictors of the design matrix in a high-dimensional logistic model. Our approach consists in rewriting the initial high-dimensional logistic model to remove the correlation between the predictors and in applying the generalized Lasso criterion.
Use various regression models for the analysis of win loss endpoints 
             adjusting for non-binary and multivariate covariates.
Streamlines the process of transitioning between data formats commonly used in survival analysis. Functions convert longitudinal data between formats used as input for survival models as well as support overall preparation. Users are able to focus on model building rather than data wrangling.
Implementation of integrative weighting approaches for multiple observational studies and causal inferences. The package features three weighting approaches, each representing a special case of the unified weighting framework, introduced by Guha and Li (2024) <doi:10.1093/biomtc/ujae070>, which includes an extension of inverse probability weights for data integration settings.
Calculate magnetic field at a given location and time according to 
  the World Magnetic Model (WMM). Both the main field and secular variation 
  components are returned. This functionality is useful for physicists and 
  geophysicists who need orthogonal components from WMM. Currently, this package 
  supports annualized time inputs between 2000 and 2025. If desired, users can
  specify which WMM version to use, e.g., the original WMM2015 release or the 
  recent out-of-cycle WMM2015 release. Methods used to implement WMM, including 
  the Gauss coefficients for each release, are described in the following 
  publications: Chulliat et al (2020) <doi:10.25923/ytk1-yx35>,
  Chulliat et al (2019) <doi:10.25921/xhr3-0t19>, 
  Chulliat et al (2015) <doi:10.7289/V5TB14V7>, 
  Maus et al (2010) <https://www.ngdc.noaa.gov/geomag/WMM/data/WMMReports/WMM2010_Report.pdf>, 
  McLean et al (2004) <https://www.ngdc.noaa.gov/geomag/WMM/data/WMMReports/TRWMM_2005.pdf>,
  and Macmillian et al (2000) <https://www.ngdc.noaa.gov/geomag/WMM/data/WMMReports/wmm2000.pdf>.
Provides inference for the Wilcoxon-Mann-Whitney test under the null hypothesis H0: AUC = 0.5 for continuous, discrete or mixed random variables. Traditional implementations test H0: F = G, which is inappropriately broad and leads to erroneous inferences. Methods are described in M. Grendar (2025) "Wilcoxon-Mann-Whitney Test of No Group Discrimination" <doi:10.48550/arXiv.2511.20308>.
Performs Wilcoxon-Mann-Whitney test in the presence of missing data with controlled Type I error regardless of the values of missing data.
Power calculator for the two-sample Wilcoxon-Mann-Whitney rank-sum test for a continuous outcome (Mollan, Trumble, Reifeis et. al., Mar. 2020) <doi:10.1080/10543406.2020.1730866> <arXiv:1901.04597>, (Mann and Whitney 1947) <doi:10.1214/aoms/1177730491>, (Shieh, Jan, and Randles 2006) <doi:10.1080/10485250500473099>.
Calculates the minimal sample size for the Wilcoxon-Mann-Whitney test
    that is needed for a given power and two sided type I error rate. The method works for metric data with and without
    ties, count data, ordered categorical data, and even dichotomous data.
    But data is needed for the reference group to generate synthetic data for the treatment group based on a relevant effect.
    See Happ et al. (2019, <doi:10.1002/sim.7983>) for details.
This is a set of minimization tools (maximum likelihood estimation and least square fitting) to solve examples in the Johan Gabrielsson and Dan Weiner's book "Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications" 5th ed. (ISBN:9198299107). Examples include linear and nonlinear compartmental model, turn-over model, single or multiple dosing bolus/infusion/oral models, allometry, toxicokinetics, reversible metabolism, in-vitro/in-vivo extrapolation, enterohepatic circulation, metabolite modeling, Emax model, inhibitory model, tolerance model, oscillating response model, enantiomer interaction model, effect compartment model, drug-drug interaction model, receptor occupancy model, and rebound phenomena model.
New tools for the imputation of missing values in high-dimensional
    data are introduced using the non-parametric nearest neighbor methods. It
    includes weighted nearest neighbor imputation methods that use specific
    distances for selected variables. It includes an automatic procedure of cross
    validation and does not require prespecified values of the tuning parameters.
    It can be used to impute missing values in high-dimensional data when the sample
    size is smaller than the number of predictors. For more information see Faisal
    and Tutz (2017) <doi:10.1515/sagmb-2015-0098>.
Estimates Poole and Rosenthal's (1985 <doi:10.2307/2111172>, 1991 <doi:10.2307/2111445>)
	W-NOMINATE scores from roll call votes supplied though a 'rollcall'
	object from the 'pscl' package.
Implements the Whale Optimization Algorithm(WOA) for k-medoids clustering, providing tools for effective and efficient cluster analysis in various data sets. The methodology is based on "The Whale Optimization Algorithm" by Mirjalili and Lewis (2016) <doi:10.1016/j.advengsoft.2016.01.008>.
Descriptive statistics for large data tend to be low resolution on the tails. 
    Whisker Odds generate a table of descriptive statistics for large data. This is the same as
    letter-values, but with an alternative naming of depths which allow for depths beyond 26. For 
    a reference to letter-values see 'Heike Hofmann' and 'Hadley Wickham' and 'Karen Kafadar' (2017) <doi:10.1080/10618600.2017.1305277>.
Shows the relationship between an independent and dependent variable through Weight of Evidence and Information Value.
Implements an automated binning of numeric variables and factors with
 respect to a dichotomous target variable.
 Two approaches are provided: An implementation of fine and coarse classing that
 merges granular classes and levels step by step. And a tree-like approach that
 iteratively segments the initial bins via binary splits. Both procedures merge,
 respectively split, bins based on similar weight of evidence (WOE) values and
 stop via an information value (IV) based criteria.
 The package can be used with single variables or an entire data frame. It provides
 flexible tools for exploring different binning solutions and for deploying them to
 (new) data.
Implements a spatiotemporal boundary detection model with a dissimilarity
    metric for areal data with inference in a Bayesian setting using Markov chain
    Monte Carlo (MCMC). The response variable can be modeled as Gaussian (no nugget),
    probit or Tobit link and spatial correlation is introduced at each time point
    through a conditional autoregressive (CAR) prior. Temporal correlation is introduced
    through a hierarchical structure and can be specified as exponential or first-order
    autoregressive. Full details of the package can be found in the accompanying vignette.
    Furthermore, the details of the package can be found in "Diagnosing Glaucoma 
    Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method", 
    by Berchuck et al (2019) <doi:10.1080/01621459.2018.1537911>.
A hierarchy of classes and methods for manipulating matrices formed implicitly from the sums of the inverses of other matrices, a situation commonly encountered in spatial statistics and related fields. Enables easy use of the Woodbury matrix identity and the matrix determinant lemma to allow computation (e.g., solving linear systems) without having to form the actual matrix. More information on the underlying linear algebra can be found in Harville, D. A. (1997) <doi:10.1007/b98818>.
Tools for generating simulated sawn timber
    strength grading data with a main focus on statistical simulation based on
    covariance matrices. Simulation data
    for Norway spruce sawn timber from Austria and reference values of means and
    standard deviations of grade determining properties from literature
    for a number of European countries are provided, as well.
Monetary valuation of wood in German forests
             (stumpage values), including estimations of harvest quantities, 
             wood revenues, and harvest costs. The functions are sensitive to
             tree species, mean diameter of the harvested trees, stand quality,
             and logging method. The functions include estimations for the
             consequences of disturbances on revenues and costs. The underlying
             assortment tables are taken from Offer and Staupendahl (2018) with
             corresponding functions for salable and skidded volume derived in
             Fuchs et al. (2023). Wood revenue and harvest cost
             functions were taken from v. Bodelschwingh (2018). The consequences
             of disturbances refer to Dieter (2001), Moellmann and Moehring
             (2017), and Fuchs et al. (2022a, 2022b). For the full references 
             see documentation of the functions, package README, and Fuchs et
             al. (2023). Apart from Dieter (2001) and Moellmann and
             Moehring (2017), all functions and factors are based on data from
             HessenForst, the forest administration of the Federal State of
             Hesse in Germany.
Students learning both econometrics and R may find the introduction 
    to both challenging. The wooldridge data package aims to lighten the task by efficiently 
    loading any data set found in the text with a single command. Data sets have been 
    compressed to a fraction of their original size. Documentation files contain page numbers, 
    the original source, time of publication, and notes from the author suggesting avenues for 
    further analysis and research. If one needs an introduction to R model syntax, a 
    vignette contains solutions to examples from chapters of the text. 
    Data sets are from the 7th edition (Wooldridge 2020, ISBN-13 978-1-337-55886-0), 
    and are backwards compatible with all previous versions of the text.
Create reproducible and transparent research projects in 'R'.
    This package is based on the Workflow for Open
    Reproducible Code in Science (WORCS), a step-by-step procedure based on best
    practices for
    Open Science. It includes an 'RStudio' project template, several
    convenience functions, and all dependencies required to make your project
    reproducible and transparent. WORCS is explained in the tutorial paper
    by Van Lissa, Brandmaier, Brinkman, Lamprecht, Struiksma, & Vreede (2021).
    <doi:10.3233/DS-210031>.
Learn vector representations of words by continuous bag of words and skip-gram implementations of the 'word2vec' algorithm. 
    The techniques are detailed in the paper "Distributed Representations of Words and Phrases and their Compositionality" by Mikolov et al. (2013), available at <doi:10.48550/arXiv.1310.4546>.
Functionality to create pretty word clouds, visualize differences and similarity between documents, and avoid over-plotting in scatter plots with text.
A fast visualization tool for creating wordcloud
    by using 'wordcloud2.js'. 'wordcloud2.js' is a JavaScript library to create 
    wordle presentation on 2D canvas or HTML <https://timdream.org/wordcloud2.js/>.
The 'Wordle' game. Players have six attempts to guess a 
    five-letter word. After each guess, the player is informed which 
    letters in their guess are either: anywhere in the word; in the right 
    position in the word. This can be used to inform the next guess. Can be 
    played interactively in the console, or programmatically. Based on Josh 
    Wardle's game <https://www.powerlanguage.co.uk/wordle/>.
Application to estimate statistical values using properties provided by a group of individuals to describe
  concepts using 'shiny'. It estimates the underlying distribution to generate new descriptive words
  Canessa et al. (2023) <doi:10.3758/s13428-022-01811-w>, applies a new clustering model, and uses simulations to estimate 
  the probability that two persons describe the same words based on their descriptions
  Canessa et al. (2022) <doi:10.3758/s13428-022-02030-z>.
Extract features and classify documents with noisy labels given by document-meta data or keyword matching Watanabe & Zhou (2020) <doi:10.1177/0894439320907027>.
An interface to WordNet using the Jawbone Java API to WordNet.
  WordNet (<https://wordnet.princeton.edu/>) is a large lexical database of
  English.  Nouns, verbs, adjectives and adverbs are grouped into sets of
  cognitive synonyms (synsets), each expressing a distinct concept.  Synsets
  are interlinked by means of conceptual-semantic and lexical relations.
  Please note that WordNet(R) is a registered tradename.  Princeton
  University makes WordNet available to research and commercial users
  free of charge provided the terms of their license
  (<https://wordnet.princeton.edu/license-and-commercial-use>) are followed,
  and proper reference is made to the project using an appropriate
  citation (<https://wordnet.princeton.edu/citing-wordnet>).
  The WordNet database files need to be made available separately,
  either via package 'wordnetDicts' from <https://datacube.wu.ac.at>,
  installing system packages where available, or direct download from
  <https://wordnetcode.princeton.edu/3.0/WNdb-3.0.tar.gz>.
Methods for estimating profit, profit-maximizing price, demand and consumer surplus of Word-of-Mouth-campaigns on mean-field networks.
Apply 'Wordpiece' (<arXiv:1609.08144>) tokenization to input text, 
 given an appropriate vocabulary. The 'BERT' (<arXiv:1810.04805>) tokenization 
 conventions are used by default.
Provides data to be used by the wordpiece algorithm in order to 
    tokenize text into somewhat meaningful chunks. Included vocabularies were 
    retrieved from 
    <https://huggingface.co/bert-base-cased/resolve/main/vocab.txt> and 
    <https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt> and parsed
    into an R-friendly format.
Collects several classical word pools used most often
    to provide lists of words in psychological studies of learning and memory. It
    provides a simple function, 'pickList' for selecting random samples of words
    within given ranges.
The word puzzle game requires you to find out the letters in a word within a limited number of guesses. In each round, if your guess hit any letters in the word, they reveal themselves. If all letters are revealed before your guesses run out, you win this game; otherwise you fail. You may run multiple games to guess different words.
Serves for rendering MS Word documents with R inline code and inserting tables and plots.
List of english scrabble words as listed in the OTCWL2014
    <https://www.scrabbleplayers.org/w/Official_Tournament_and_Club_Word_List_2014_Edition>.
    Words are collated from the 'Word Game Dictionary' <https://www.wordgamedictionary.com/word-lists/>.
Provides access to various word embedding methods (GloVe, 
    fasttext and word2vec) to extract word vectors using a unified framework to
    increase reproducibility and correctness.
An interactive laboratory for research on distributional semantic models ('DSM',
             see <https://en.wikipedia.org/wiki/Distributional_semantics> for more information).
Create dense vector representation of words and documents using 'quanteda'. Implements Word2vec (Mikolov et al., 2013) <doi:10.48550/arXiv.1310.4546>, Doc2vec (Le & Mikolov, 2014) <doi:10.48550/arXiv.1405.4053> and Latent Semantic Analysis (Deerwester et al., 1990) <doi:10.1002/(SICI)1097-4571(199009)41:6%3C391::AID-ASI1%3E3.0.CO;2-9>.
Provides a workflow for your analysis projects by combining
  literate programming ('knitr' and 'rmarkdown') and version control
  ('Git', via 'git2r') to generate a website containing time-stamped,
  versioned, and documented results.
Managing both a 'parsnip' model and a preprocessor, such as a
    model formula or recipe from 'recipes', can often be challenging. The
    goal of 'workflows' is to streamline this process by bundling the
    model alongside the preprocessor, all within the same object.
A workflow is a combination of a model and preprocessors
    (e.g, a formula, recipe, etc.) (Kuhn and Silge (2021)
    <https://www.tmwr.org/>). In order to try different combinations of
    these, an object can be created that contains many workflows. There
    are functions to create workflows en masse as well as training them
    and visualizing the results.
Functions for the import, transformation, and analysis of data 
    from muscle physiology experiments. The work loop technique is used to 
    evaluate the mechanical work and power output of muscle. Josephson (1985) 
    <doi:10.1242/jeb.114.1.493> modernized the technique for
    application in comparative biomechanics. Although our initial motivation 
    was to provide functions to analyze work loop experiment data, as we 
    developed the package we incorporated the ability to analyze data from 
    experiments that are often complementary to work loops. There are currently 
    three supported experiment types: work loops, simple twitches, and tetanus 
    trials. Data can be imported directly from .ddf files or via an object 
    constructor function. Through either method, data can then be cleaned or 
    transformed via methods typically used in studies of muscle physiology. 
    Data can then be analyzed to determine the timing and magnitude of force 
    development and relaxation (for isometric trials) or the magnitude of work, 
    net power, and instantaneous power among other things (for work loops). 
    Although we do not provide plotting functions, all resultant objects are 
    designed to be friendly to visualization via either base-R plotting or 
    'tidyverse' functions.
 This package has been peer-reviewed by rOpenSci (v. 1.1.0).
Create, store, read and manage structured collections of
    datasets and other objects using a 'workspace', then bundle it into a
    compressed archive.  Using open and interoperable formats makes it
    possible to exchange bundled data from 'R' to other languages such as
    'Python' or 'Julia'.  Multiple formats are supported 'Parquet',
    'JSON', 'yaml', spatial data and raster data are supported.
Download and search data from the 'World Bank' APIs,
    including the 'Indicators' API, the 'Poverty and Inequality Platform
    (PIP)' API, the 'Finances One' API, and the 'Projects' API. See
    <https://datahelpdesk.worldbank.org/knowledgebase/articles/889386-developer-information-overview>
    for further details.
World Flora Online is an online flora of all known plants, available from <https://www.worldfloraonline.org/>. Methods are provided of matching a list of plant names (scientific names, taxonomic names, botanical names) against a static copy of the World Flora Online Taxonomic Backbone data that can be downloaded from the World Flora Online website. The World Flora Online Taxonomic Backbone is an updated version of The Plant List (<http://www.theplantlist.org/>), a working list of plant names that has become static since 2013.
Allow users to obtain clean and tidy
    football (soccer) game, team and player data. Data is collected from a
    number of popular sites, including 'FBref',
    transfer and valuations data from
    'Transfermarkt'<https://www.transfermarkt.com/> and shooting location
    and other match stats data from 'Understat'<https://understat.com/>
    and 'fotmob'<https://www.fotmob.com/>. It gives users the
    ability to access data more efficiently, rather than having to export
    data tables to files before being able to complete their analysis.
Easily plot heat maps of the world, based on continuous or categorical data. Country labels can also be added to the map.
Functions to import data from more than 30,000 surface
    meteorological sites around the world managed by the National Oceanic
    and Atmospheric Administration (NOAA) Global Historical Climate
    Network (GHCN) and Integrated Surface Database (ISD).
A toolkit to detect clusters from distance matrices. 
    The distance matrices are assumed to be calculated between the cells of 
    multiple animals ('Caenorhabditis elegans') from input time-series matrices. 
    Some functions for generating distance matrices, performing clustering, 
    evaluating the clustering, and visualizing the results of clustering and 
    evaluation are available. We're also providing the download function to 
    retrieve the calculated distance matrices from 
    'figshare' <https://figshare.com>.
Client for World Register of Marine Species
    (<https://www.marinespecies.org/>). Includes functions for each
    of the API methods, including searching for names by name, date and
    common names, searching using external identifiers, fetching
    synonyms, as well as fetching taxonomic children and
    taxonomic classification.
Generate wordsearch and crossword puzzles using
    custom lists of words (and clues).  Make them easy or hard,
    and print them to solve offline with paper and pencil!
R clients to the 'Web of Science' and 'InCites' 
  <https://clarivate.com/products/data-integration/> APIs, which 
  allow you to programmatically download publication and citation data
  indexed in the 'Web of Science' and 'InCites' databases.
It shows the connections between selected clusters from the latest time point and the clusters from all the previous time points. The transition matrices between time point t and t+1 are obtained from Waddington-OT analysis <https://github.com/ScialdoneLab/WOTPLY>.
This method generates a tour path by interpolating between d-D frames in p-D using Givens rotations. The algorithm arises from the problem of zeroing elements of a matrix. This interpolation method is useful for showing specific d-D frames in the tour, as opposed to d-D planes, as done by the geodesic interpolation. It is useful for projection pursuit indexes which are not s invariant. See more details in Buj, Cook, Asimov and Hurley (2005) <doi:10.1016/S0169-7161(04)24014-7> and Batsaikhan, Cook and Laa (2023) <doi:10.48550/arXiv.2311.08181>.
Opinionated functions that enable easier and faster
    analysis of Viva Insights data. There are three main types of functions in 'wpa':
    (i) Standard functions create a 'ggplot' visual or a summary table based on a specific
    Viva Insights metric; (2) Report Generation functions generate HTML reports on
    a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover
    more specific applications (e.g. Subject Line text mining) of Viva Insights data.
    This package adheres to 'tidyverse' principles and works well with the pipe syntax.
    'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for
    simplicity.
Analyzing pedigree data of wild
    populations. While primarily designed to process outputs from the
    'COLONY' (Jones & Wang (2010) <doi:10.1111/j.1755-0998.2009.02787.x>)
    pedigree reconstruction software, it can also accommodate
    data from other sources. By linking reconstructed pedigrees with
    genetic sample metadata, 'wpeR' produces spatial and temporal
    visualizations as well as tabular summaries that support
    interpretation of family structures and dynamics. The main goal of the
    package is to provide a solution for the analysis of
    complex wild pedigree data and to help the user to gain insights
    into genetic relationships within wild animal populations.
Weighted Piecewise Kernel Density Estimation for large data.
Data from the United Nation's World Population Prospects 2008
Data from the United Nation's World Population Prospects
        2010
Data from the United Nation's World Population Prospects 2012
Provides data from the United Nation's World Population Prospects 2015.
Provides data from the United Nation's World Population Prospects 2017.
Provides data from the United Nation's World Population Prospects 2019.
Explore data in the 'wpp2019' (or 2017, 2015, ...) package using a 'shiny' interface.
Performs Wasserstein projections from the predictive distributions of any model into the space of predictive distributions of linear models. We utilize L1 penalties to also reduce the complexity of the model space. This package employs the methods as described in Dunipace, Eric and Lorenzo Trippa (2020) <doi:10.48550/arXiv.2012.09999>.
Estimate and plot wavelet quantile correlations(Kumar and Padakandla,2022) between two time series. Wavelet quantile correlation is used to capture the dependency between two time series across quantiles and different frequencies. This method is useful in identifying potential hedges and safe-haven instruments for investment purposes. See Kumar and Padakandla(2022) <doi:10.1016/j.frl.2022.102707> for further details.
Functions to assist in the processing and
    exploration of data from environmental monitoring programs.
    The package name stands for "water quality" and reflects the
    original focus on time series data for physical and chemical
    properties of water, as well as the biota. Intended for
    programs that sample approximately monthly, quarterly or
    annually at discrete stations, a feature of many legacy data
    sets. Most of the functions should be useful for analysis of
    similar-frequency time series regardless of the subject
    matter.
The wavelet-based quantile mapping (WQM) technique is designed to correct biases in spatio-temporal precipitation forecasts across multiple time scales. The WQM method effectively enhances forecast accuracy by generating an ensemble of precipitation forecasts that account for uncertainties in the prediction process. For a comprehensive overview of the methodologies employed in this package, please refer to Jiang, Z., and Johnson, F. (2023) <doi:10.1029/2022EF003350>. The package relies on two packages for continuous wavelet transforms: 'WaveletComp', which can be installed automatically, and 'wmtsa', which is optional and available from the CRAN archive <https://cran.r-project.org/src/contrib/Archive/wmtsa/>. Users need to manually install 'wmtsa' from this archive if they prefer to use 'wmtsa' based decomposition.
Implements a permutation test method for the weighted quantile sum (WQS) regression, building off the 'gWQS' package (Renzetti et al. <https://CRAN.R-project.org/package=gWQS>). Weighted quantile sum regression is a statistical technique to evaluate the effect of complex exposure mixtures on an outcome (Carrico et al. 2015 <doi:10.1007/s13253-014-0180-3>). The model features a statistical power and Type I error (i.e., false positive) rate trade-off, as there is a machine learning step to determine the weights that optimize the linear model fit. This package provides an alternative method based on a permutation test that should reliably allow for both high power and low false positive rate when utilizing WQS regression (Day et al. 2022 <doi:10.1289/EHP10570>).
Assess Water Quality Trends for Long-Term Monitoring Data in Estuaries using
  Generalized Additive Models following Wood (2017) <doi:10.1201/9781315370279> and Error
  Propagation with Mixed-Effects Meta-Analysis following Sera et al. (2019) <doi:10.1002/sim.8362>.
  Methods are available for model fitting, assessment of fit, annual and seasonal trend tests, and
  visualization of results.
Implements various win ratio methodologies for composite endpoints of death and 
  non-fatal events, including the (stratified) proportional win-fractions (PW) regression models 
  (Mao and Wang, 2020 <doi:10.1111/biom.13382>), (stratified) two-sample tests with possibly 
  recurrent nonfatal event, and sample size calculation for standard win ratio test (Mao et al., 
  2021 <doi:10.1111/biom.13501>).
Supports systematic scrutiny, modification, and integration of
    data. The function status() counts rows that have missing values in 
    grouping columns (returned by na() ), have non-unique combinations of 
    grouping columns (returned by dup() ), and that are not locally sorted
    (returned by unsorted() ). Functions enumerate() and itemize() give 
    sorted unique combinations of columns, with or without occurrence counts,
    respectively. Function ignore() drops columns in x that are present in y,
    and informative() drops columns in x that are entirely NA; constant() returns
    values that are constant, given a key.  Data that have defined unique 
    combinations of grouping values behave more predictably during merge operations.
The main functionalities of 'wrappedtools' are:
    adding backticks to variable names; rounding to desired precision 
    with special case for p-values; 
    selecting columns based on pattern and storing their position, name, 
    and backticked name; computing and formatting of descriptive statistics 
    (e.g. mean±SD), comparing groups and creating publication-ready tables with 
    descriptive statistics and p-values; creating specialized plots for 
    correlation matrices. Functions were mainly written for my own daily work or 
    teaching, but may be of use to others as well.
Helper functions to easily add functionality to functions.  The package can 
  assign functions to have an lazy evaluation allowing you to save and update the 
  arguments before and after each function call.  You can set a temporary working 
  directory within functions and wrap console messages around other functions.
Tools for writing and debugging R code. Provides: 
    '%.>%' dot-pipe (an 'S3' configurable pipe), unpack/to (R style multiple assignment/return),
    'build_frame()'/'draw_frame()' ('data.frame' example tools),
    'qc()' (quoting concatenate), 
    ':=' (named map builder), 'let()' (converts non-standard evaluation interfaces to parametric standard
    evaluation interfaces, inspired by 'gtools::strmacro()' and 'base::bquote()'), and more.
A wrapper around Michel Scheffers's 'libassp' (<https://libassp.sourceforge.net/>).
    The 'libassp' (Advanced Speech Signal Processor) library aims at providing
    functionality for handling speech signal files in most common audio formats
    and for performing analyses common in phonetic science/speech science. This
    includes the calculation of formants, fundamental frequency, root mean
    square, auto correlation, a variety of spectral analyses, zero crossing
    rate, filtering etc. This wrapper provides R with a large subset of
    'libassp's signal processing functions and provides them to the user in a
    (hopefully) user-friendly manner.
Provides simple functions for accessing data from 'Wharton Research
    Data Services' ('WRDS'), a widely used financial database in academic
    research. Includes credential management via the system keyring,
    database tools, and functions for downloading generic tables, 'Compustat'
    fundamentals, and linking tables.
A collection of color palettes that were extracted from various books on my sons(Wren) bookshelf. Also included are a number of functions and wrappers to utilize them, as well as to subset the palettes to desired number/specific colors.
Calculates non-parametric estimates of the sample size, power and confidence intervals for the win-ratio. For more detail on the theory behind the methodologies implemented see Yu, R. X. and Ganju, J. (2022) <doi:10.1002/sim.9297>.
Additional options for making graphics in the context of analyzing high-throughput data are available here.
  This includes automatic segmenting of the current device (eg window) to accommodate multiple new plots, 
  automatic checking for optimal location of legends in plots, small histograms to insert as legends, 
  histograms re-transforming axis labels to linear when plotting log2-transformed data,
  a violin-plot <doi:10.1080/00031305.1998.10480559> function for a wide variety of input-formats, 
  principal components analysis (PCA) <doi:10.1080/14786440109462720> with bag-plots <doi:10.1080/00031305.1999.10474494> to highlight and compare the center areas for groups of samples, 
  generic MA-plots (differential- versus average-value plots) <doi:10.1093/nar/30.4.e15>, 
  staggered count plots and generation of mouse-over interactive html pages.
Implementation of the methodologies described in 1) Alexander Petersen, Xi Liu and Afshin A. Divani (2021) <doi:10.1214/20-aos1971>, including global F tests, partial F tests, intrinsic Wasserstein-infinity bands and Wasserstein density bands, and 2) Chao Zhang, Piotr Kokoszka and Alexander Petersen (2022) <doi:10.1111/jtsa.12590>, including estimation, prediction, and inference of the Wasserstein autoregressive models.
Provides functions, tutorials, and examples to preprocess, 
    analyze, and visualize data from whole room indirect calorimeters (WRIC) by 
    Maastricht Instruments, using the 'OmniCal' software. Some functions may also 
    work with WRICs from other manufacturers, though full functionality has only 
    been validated for Maastricht Instruments devices.
A powerful yet simple graphical tool available in the field of psychometrics is the Wright Map (also known as item maps or item-person maps), which presents the location of both respondents and items on the same scale. Wright Maps are commonly used to present the results of dichotomous or polytomous item response models. The 'WrightMap' package provides functions to create these plots from item parameters and person estimates stored as R objects. Although the package can be used in conjunction with any software used to estimate the IRT model (e.g. 'TAM', 'mirt', 'eRm' or 'IRToys' in 'R', or 'Stata', 'Mplus', etc.),  'WrightMap' features special integration with 'ConQuest' to facilitate reading and plotting its output directly.The 'wrightMap' function creates Wright Maps based on person estimates and item parameters produced by an item response analysis. The 'CQmodel' function reads output files created using 'ConQuest' software and creates a set of data frames for easy data manipulation, bundled in a 'CQmodel' object. The 'wrightMap' function can take a 'CQmodel' object as input or it can be used to create Wright Maps directly from data frames of person and item parameters.
Imports variables from 'ReaderBench' (Dascalu et al.,
    2018)<doi:10.1007/978-3-319-66610-5_48>, 'Coh-Metrix' (McNamara et
    al., 2014)<doi:10.1017/CBO9780511894664>, and/or 'GAMET' (Crossley et
    al., 2019) <doi:10.17239/jowr-2019.11.02.01> output files; downloads
    predictive scoring models described in Mercer & Cannon
    (2022)<doi:10.31244/jero.2022.01.03> and Mercer et
    al.(2021)<doi:10.1177/0829573520987753>; and generates predicted
    writing quality and curriculum-based measurement (McMaster & Espin,
    2007)<doi:10.1177/00224669070410020301> scores.
Provides unified syntax to write data from lazy 'dplyr' 'tbl' or
    'dplyr' 'sql' query or a dataframe to a database table with modes such as
    create, append, insert, update, upsert, patch, delete, overwrite,
    overwrite_schema.
Zero-dependency data frame to xlsx exporter based on 'libxlsxwriter'
    <https://libxlsxwriter.github.io>. Fast and no Java or Excel required.
Cross-platform Perl based R function to create Excel 2003 (XLS) and Excel 2007 (XLSX)
             files from one or more data frames. Each data frame will be
             written to a separate named worksheet in the Excel spreadsheet.
             The worksheet name will be the name of the data frame it contains
             or can be specified by the user.
The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions. 
  Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc.  
  Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM)  
  for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates). 
  A group of functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc. 
  Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values. 
  Other functions help aligning a matrix or data.frame to a reference using partial matching or to mine an experimental setup to extract patterns of replicate samples.
  Many times large experimental datasets need some additional filtering, adequate functions are provided. 
  Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too.
  Batch reading (or writing) of sets of files and combining data to arrays is supported, too.
A collection of robust statistical methods based on Wilcox' WRS functions. It implements robust t-tests (independent and dependent samples), robust ANOVA (including between-within subject designs), quantile ANOVA, robust correlation, robust mediation, and nonparametric ANCOVA models based on robust location measures.
Tools for constructing, simulating, and analyzing large-scale
    water resources systems. The package provides functions to represent
    system components such as reservoirs, aquifers, rivers, diversions,
    and demand sites, and to simulate system behavior under Standard
    Operating Policy. It also supports the development and evaluation
    of water allocation strategies and hydropower operations within
    integrated water resources systems.
A collection of implementations of classical and
    novel algorithms for weighted sampling without replacement.
An adaptation for estuaries (tidal waters) of weighted regression
    on time, discharge, and season to evaluate trends in water quality time series. 
    Please see Beck and Hagy (2015) <doi:10.1007/s10666-015-9452-8> for 
    details.
Top-Down mass spectrometry aims to identify entire proteins as well as their (post-translational) modifications or ions bound (eg Chen et al (2018) <doi:10.1021/acs.analchem.7b04747>). 
    The pattern of internal fragments (Haverland et al (2017) <doi:10.1007/s13361-017-1635-x>) may reveal important information about the original structure of the proteins studied 
    (Skinner et al (2018) <doi:10.1038/nchembio.2515> and Li et al (2018) <doi:10.1038/nchem.2908>). 
    However, the number of possible internal fragments gets huge with longer proteins and subsequent identification of internal fragments remains challenging, 
    in particular since the the accuracy of measurements with current mass spectrometers represents a limiting factor.   
    This package attempts to deal with the complexity of internal fragments and allows identification of terminal and internal fragments from deconvoluted mass-spectrometry data.
Predicts individual race/ethnicity using surname, first name,
    middle name, geolocation, and other attributes, such as gender and
    age. The method utilizes Bayes' Rule (with optional measurement error
    correction) to compute the posterior probability of each racial
    category for any given individual. The package implements methods
    described in Imai and Khanna (2016) "Improving Ecological Inference by
    Predicting Individual Ethnicity from Voter Registration Records"
    Political Analysis <DOI:10.1093/pan/mpw001> and Imai, Olivella, and
    Rosenman (2022) "Addressing census data problems in race imputation
    via fully Bayesian Improved Surname Geocoding and name supplements"
    <DOI:10.1126/sciadv.adc9824>.  The package also incorporates the data
    described in Rosenman, Olivella, and Imai (2023) "Race and ethnicity
    data for first, middle, and surnames"
    <DOI:10.1038/s41597-023-02202-2>.
Non- and semiparametric regression for generalized additive, partial linear, and varying coefficient models as well as their combinations via smoothed backfitting. Based on Roca-Pardinas J and Sperlich S (2010) <doi:10.1007/s11222-009-9130-2>; Mammen E, Linton O and Nielsen J (1999) <doi:10.1214/aos/1017939138>; Lee YK, Mammen E, Park BU (2012) <doi:10.1214/12-AOS1026>.
This dataset was collected using a new four-arm within-study comparison design. The study aimed to examine the impact of a mathematics training intervention and a vocabulary study session on post-test scores in mathematics and vocabulary, respectively. The innovative four-arm within-study comparison design facilitates both experimental and quasi-experimental identification of average causal effects.
Easily override the default visual choices in 'ggplot2' to make 
    your time series plots look more like the Wall Street Journal. Specific 
    theme design choices include omitting x-axis grid lines and displaying 
    sparse light grey y-axis grid lines. Additionally, this allows to label 
    the y-axis scales with your units only displayed on the top-most number, 
    while also removing the bottom most number (unless specifically 
    overridden). The goal is visual simplicity, because who has time to waste 
    looking at a cluttered graph?
Entropy weighted k-means (ewkm) by Liping Jing, Michael
        K. Ng and Joshua Zhexue Huang (2007)
        <doi:10.1109/TKDE.2007.1048> is a weighted subspace clustering
        algorithm that is well suited to very high dimensional data.
        Weights are calculated as the importance of a variable with
        regard to cluster membership.  The two-level variable
        weighting clustering algorithm tw-k-means (twkm) by Xiaojun
        Chen, Xiaofei Xu, Joshua Zhexue Huang and Yunming Ye (2013)
        <doi:10.1109/TKDE.2011.262> introduces two types of weights,
        the weights on individual variables and the weights on
        variable groups, and they are calculated during the clustering
        process.  The feature group weighted k-means (fgkm) by Xiaojun
        Chen, Yunminng Ye, Xiaofei Xu and Joshua Zhexue Huang (2012)
        <doi:10.1016/j.patcog.2011.06.004> extends this concept by
        grouping features and weighting the group in addition to
        weighting individual features.
Within-subject mediation analysis using structural equation modeling.
    Examine how changes in an outcome variable between two conditions are mediated 
    through one or more variables. Supports within-subject mediation analysis using 
    the 'lavaan' package by Rosseel (2012) <doi:10.18637/jss.v048.i02>, 
    and extends Monte Carlo confidence interval estimation to missing data scenarios 
    using the 'semmcci' package by Pesigan and Cheung (2023) <doi:10.3758/s13428-023-02114-4>.
A weighted selection probability to locate rare variants associated with multiple phenotypes.
A parallel implementation of Weighted Subspace Random Forest.  The
    Weighted Subspace Random Forest algorithm was proposed in the
    International Journal of Data Warehousing and Mining by Baoxun Xu,
    Joshua Zhexue Huang, Graham Williams, Qiang Wang, and Yunming Ye
    (2012) <DOI:10.4018/jdwm.2012040103>.  The algorithm can classify
    very high-dimensional data with random forests built using small
    subspaces.  A novel variable weighting method is used for variable
    subspace selection in place of the traditional random variable
    sampling.This new approach is particularly useful in building
    models from high-dimensional data.
Weighted versions of common descriptive statistics (variance,
    standard deviation, covariance, correlation, quantiles).
Implements the Welch-Satterthwaite approximation for differences
    of non-standardized t-distributed random variables in both univariate and 
    multivariate settings. The package provides methods for computing effective
    degrees of freedom and scale parameters, as well as distribution functions
    for the approximated difference distribution. The methodology extends the
    classical Welch-Satterthwaite framework from variance combinations to
    t-distribution differences through careful moment matching. Methods build
    on the classical Welch-Satterthwaite approach described in Welch (1947)
    <doi:10.1093/biomet/34.1-2.28> and Satterthwaite (1946) <doi:10.2307/3002019>.
Tools for a wavelet-based approach to analyzing spatial synchrony, principally in ecological data. Some tools will be useful for studying community synchrony. See, for instance, Sheppard et al (2016) <doi: 10.1038/NCLIMATE2991>, Sheppard et al (2017) <doi: 10.1051/epjnbp/2017000>, Sheppard et al (2019) <doi: 10.1371/journal.pcbi.1006744>.
Perform the calculation of W-test, diagnostic checking, calculate
    minor allele frequency (MAF) and odds ratio.
Computes the Weighted Topological Overlap with positive and negative signs (wTO) networks given a data frame containing the mRNA count/ expression/ abundance per sample, and a vector containing the interested nodes of interaction (a subset of the elements of the full data frame). It also computes the cut-off threshold or p-value based on the individuals bootstrap or the values reshuffle per individual. It also allows the construction of a consensus network, based on multiple wTO networks. The package includes a visualization tool for the networks.  More about the methodology can be found at <doi:10.1186/s12859-018-2351-7>.
Evaluation of alternatives based on multiple criteria using weighted technique for Order preference by similarity to an ideal solution method. Reference: Hwang CL. (1981, ISBN:978-3-540-10558-9).
Allows form managers to download entries from their respondents
    using Wufoo JSON API (<https://www.wufoo.com>). Additionally, the Wufoo reports - when public - can be
    also acquired programmatically. Note that building new forms within this package
    is not supported.
Provides a series of tools to compute and plot quantities related to classical and robust wavelet variance for time series and regular lattices. More details can be found, for example, in Serroukh, A., Walden, A.T., & Percival, D.B. (2000) <doi:10.2307/2669537> and Guerrier, S. & Molinari, R. (2016) <doi:10.48550/arXiv.1607.05858>.
Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'.  
   Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, 
   conditioned scatter plot with marginal densities,
   box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Book is "Linear Mixed Models: A Practical Guide Using
        Statistical Software" published in 2006 by Chapman Hall / CRC
        Press.
Provides a collection of white noise hypothesis tests for functional time series and related visualizations. 
  These include tests based on the norms of autocovariance operators that are built under both strong and weak 
  white noise assumptions. Additionally, tests based on the spectral density operator and on principal component
  dimensional reduction are included, which are built under strong white noise assumptions. 
  Also, this package provides goodness-of-fit tests for functional autoregressive of order 1 models.
  These methods are described in Kokoszka et al. (2017) <doi:10.1016/j.jmva.2017.08.004>, Characiejus and Rice (2019) 
  <doi:10.1016/j.ecosta.2019.01.003>, Gabrys and Kokoszka (2007) <doi:10.1198/016214507000001111>, 
  and Kim et al. (2023) <doi: 10.1214/23-SS143>
  respectively.
A weather generator to simulate precipitation and temperature for regions with seasonality. Users input training data containing precipitation, temperature, and seasonality (up to 26 seasons). Including weather season as a training variable allows users to explore the effects of potential changes in season duration as well as average start- and end-time dates due to phenomena like climate change. Data for training should be a single time series but can originate from station data, basin averages, grid cells, etc.
    Bearup, L., Gangopadhyay, S., & Mikkelson, K. (2021). "Hydroclimate Analysis Lower Santa Cruz River Basin Study (Technical Memorandum No ENV-2020-056)." Bureau of Reclamation.
    Gangopadhyay, S., Bearup, L. A., Verdin, A., Pruitt, T., Halper, E., & Shamir, E. (2019, December 1). "A collaborative stochastic weather generator for climate impacts assessment in the Lower Santa Cruz River Basin, Arizona." Fall Meeting 2019, American Geophysical Union. <https://ui.adsabs.harvard.edu/abs/2019AGUFMGC41G1267G>.
Meta testing is the ability to test a function without having to 
    provide its parameter values.
    Those values will be generated, based on semantic naming of parameters, as 
    introduced by package 'wyz.code.offensiveProgramming'.
    Value generation logic can be completed with your own data types 
    and generation schemes. This to meet your most specific requirements and to 
    answer to a wide variety of usages, from general use case to very specific
    ones.
    While using meta testing, it becomes easier to generate stress test 
    campaigns, non-regression test campaigns and robustness test campaigns, as 
    generated tests can be saved and reused from session to session. 
    Main benefits of using 'wyz.code.metaTesting' is ability to discover valid 
    and invalid function parameter combinations, ability to infer valid 
    parameter values, and to provide smart summaries that allows you to focus
    on dysfunctional cases.
Allows to turn standard R code into offensive programming code. 
    Provides code instrumentation to ease this change and tools to assist and 
    accelerate code production and tuning while using offensive programming code 
    technics. 
    Should improve code robustness and quality. Function calls can be easily 
    verified on-demand or in batch mode to assess parameter types and length 
    conformities. 
    Should improve coders productivity as offensive programming reduces the code
    size due to reduced number of controls all along the call chain. 
    Should speed up processing as many checks will be reduced to one single check.
Allows to generate on-demand or by batch, any R documentation file,
    whatever is kind, data, function, class or package. It populates
    documentation sections, either automatically or by considering
    your input. Input code could be standard R code or offensive programming code. 
    Documentation content completeness depends on the type of code you use. With
    offensive programming code, expect generated documentation to be fully 
    completed, from a format and content point of view. With some standard R 
    code, you will have to activate post processing to fill-in any section that 
    requires complements. Produced manual page validity is automatically tested 
    against R documentation compliance rules. Documentation language 
    proficiency, wording style, and phrasal adjustments remains your job.
Allows to generate automatically 'testthat' code files from offensive 
    programming test cases. Generated test files are complete and ready to run.
    Using 'wyz.code.testthat' you will earn a lot of time, reduce the number of
    errors in test case production, be able to test immediately generated files 
    without any need to view or modify them, and enter a zero time latency between 
    code implementation and industrial testing. As with 'testthat', you may
    complete provided test cases according to your needs to push testing further, 
    but this need is nearly void when using 'wyz.code.offensiveProgramming'.
The 'X13-ARIMA-SEATS' <https://www.census.gov/data/software/x13as.html> methodology and software is a widely used software and developed by the US Census Bureau. It can be accessed from 'R' with this package and 'X13-ARIMA-SEATS' binaries are provided by the 'R' package 'x13binary'.
The US Census Bureau provides a seasonal adjustment program now
 called 'X-13ARIMA-SEATS' building on both earlier programs called X-11 and
 X-12 as well as the SEATS program by the Bank of Spain. The US Census Bureau
 offers both source and binary versions -- which this package integrates for
 use by other R packages.
The x3p file format  is specified in ISO standard 5436:2000 to 
    describe 3d surface measurements. 'x3ptools' allows reading, writing and 
    basic modifications to the 3D surface measurements.
We consider the problem where we observe k vectors (possibly of different lengths), each representing an independent multinomial random vector. For a given function that takes in the concatenated vector of multinomial probabilities and outputs a real number, this is a Monte Carlo estimation procedure of an exact p-value and confidence interval. The resulting inference is valid even in small samples, when the parameter is on the boundary, and when the function is not differentiable at the parameter value, all situations where asymptotic methods and the bootstrap would fail. For more details see Sachs, Fay, and Gabriel (2025) <doi:10.48550/arXiv.2406.19141>.
A few functions which provide a quick way of subsetting
    genomic admixture data and generating customizable stacked barplots.
Create HTML5 slides with R Markdown and the JavaScript library
    'remark.js' (<https://remarkjs.com>).
Extras and extensions for 'xaringan' slides. Navigate your
    slides with tile view. Make your slides editable, live! Announce slide
    changes with subtle tones. Animate slide transitions with
    'animate.css'. Add tabbed panels to slides with 'panelset'. Use the
    'Tachyons CSS' utility toolkit for rapid slide development. Scribble
    on your slides. Add a copy button to your code chunks with
    'clipboard'. Add a logo or top or bottom banner to every slide.
    Broadcast slides to stay in sync with remote viewers. Include yourself
    in your slides with 'webcam'.  Plus a whole lot more!
Create beautifully color-coordinated and customized themes
    for your 'xaringan' slides, without writing any CSS. Complete your
    slide theme with 'ggplot2' themes that match the font and colors used
    in your slides.  Customized styles can be created directly in your
    slides' 'R Markdown' source file or in a separate external script.
Implementation of Bayesian models for estimating object lengths and morphological relationships between object lengths using photographic data collected from drones.  The Bayesian model is described in "Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from drones" (Bierlich et al., 2021, <doi:10.3354/meps13814>).
Functions for Estimating a (c)DCC-GARCH Model in large dimensions
    based on a publication by Engle et,al (2017) <doi:10.1080/07350015.2017.1345683> and Nakagawa et,al (2018) <doi:10.3390/ijfs6020052>.
    This estimation method is consist of composite likelihood method by Pakel et al. (2014) <http://paneldataconference2015.ceu.hu/Program/Cavit-Pakel.pdf>
    and (Non-)linear shrinkage estimation of covariance matrices by Ledoit and Wolf (2004,2015,2016). (<doi:10.1016/S0047-259X(03)00096-4>,
    <doi:10.1214/12-AOS989>, <doi:10.1016/j.jmva.2015.04.006>).
Hamiltonian Monte Carlo for both continuous and discontinuous posterior 
    distributions with a customizable trajectory length termination criterion. 
    See Nishimura et al. (2020) <doi:10.1093/biomet/asz083> for the original 
    Discontinuous Hamiltonian Monte Carlo; Hoffman et al. (2014) 
    <doi:10.48550/arXiv.1111.4246> and Betancourt (2016) <doi:10.48550/arXiv.1601.00225> 
    for the definition of possible Hamiltonian Monte Carlo termination criteria.
High-level functions to render 'LaTeX' fragments in plots, 
             including as labels and data symbols in 'ggplot2' plots, plus
             low-level functions to 
             author 'LaTeX' fragments (to produce 'LaTeX' documents), 
             typeset 'LaTeX' documents (to produce 'DVI' files), 
             read 'DVI' files (to produce "DVI" objects), 
             and render "DVI" objects.
Miscellaneous functions used for x-engineering (feature engineering) or 
  for supporting in other packages maintained by 'Shichen Xie'.
Implementation of a scalable, highly configurable, and 
        e(x)tended architecture for (e)volutionary and (g)enetic (a)lgorithms.
        Multiple representations (binary, real-coded, permutation, and 
        derivation-tree), a rich collection of genetic operators, 
        as well as an extended processing pipeline are provided 
        for genetic algorithms (Goldberg, D. E. (1989, ISBN:0-201-15767-5)),
        differential evolution (Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005)
        <doi:10.1007/3-540-31306-0>), simulated annealing (Aarts, E., and Korst, J.
        (1989, ISBN:0-471-92146-7)), grammar-based genetic programming 
        (Geyer-Schulz (1997, ISBN:978-3-7908-0830-X)), grammatical evolution 
        (Ryan, C., O'Neill, M., and Collins, J. J. (2018) <doi:10.1007/978-3-319-78717-6>), 
        and grammatical differential evolution (O'Neill, M. and Brabazon, A. (2006) in  
        Arabinia, H. (2006, ISBN:978-193-241596-3).
        All algorithms reuse basic adaptive mechanisms for performance optimization.
        For 'xega''s architecture, see Geyer-Schulz, A. (2025) <doi:10.5445/IR/1000187255>.
        Sequential or parallel execution (on multi-core machines, 
        local clusters, and high-performance computing environments) 
        is available for all algorithms. See 
        <https://github.com/ageyerschulz/xega/tree/main/examples/executionModel>.
Translates a BNF (Backus-Naur Form) specification of a 
             context-free language into an R grammar object
             which consists of the start symbol, the symbol table, 
             the production table, and a short production table.
             The short production table is non-recursive. 
             The grammar object contains the file name from 
             which it was generated (without a path).
             In addition, it provides functions to determine the type 
             of a symbol (isTerminal() and isNonterminal()) and functions
             to access the production table (rules() and derives()).
             For the BNF specification, see Backus, John et al. (1962)
             "Revised Report on the Algorithmic Language ALGOL 60".
             (ALGOL60 standards page <http://www.algol60.org/2standards.htm>,
              html-edition <https://www.masswerk.at/algol60/report.htm>)
             A preprocessor for macros which expand to standard BNF 
             is included. 
             The grammar compiler is an extension of the APL2 implementation in 
             Geyer-Schulz, Andreas (1997, ISBN:978-3-7908-0830-X).
Derivation tree operations are needed for implementing 
            grammar-based genetic programming and grammatical evolution:  
            Generating a random derivation trees of a context-free grammar 
            of bounded depth, decoding a derivation tree, 
            choosing a random node in a derivation tree, 
            extracting a tree whose root is a specified node, and 
            inserting a subtree into a derivation tree at a specified node.
            These operations are necessary for the initialization and 
            for decoders of a random population of programs, 
            as well as for implementing crossover and mutation operators.
            Depth-bounds are guaranteed by switching to a grammar 
            without recursive production rules. 
            For executing the examples, the package 'BNF' is needed.
            The basic tree operations for generating, extracting, and 
            inserting derivation trees as well as the conditions 
            for guaranteeing complete derivation trees have been 
            presented in Geyer-Schulz (1997, ISBN:978-3-7908-0830-X).
            The use of random integer vectors for the generation 
            of derivation trees has been introduced in 
            Ryan, C., Collins, J. J., and  O'Neill, M. (1998)
            <doi:10.1007/BFb0055930> for grammatical evolution.
Representation-dependent gene-level operations  
        for genetic and evolutionary algorithms with real-coded genes
        used in the R-package 'xega' <https://CRAN.R-project.org/package=xega>
        are collected in this package. The common feature of the gene
        operations is that all of them are useful for derivation-free
        optimization algorithms. At the moment the package  
        implements initialization, mutation, crossover, and replication 
        operations for differential evolution as described in
        Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005)
        <doi:10.1007/3-540-31306-0>.  In addition, several (more recent) 
        methods for determining the scale factor are provided.
        For 'xega''s architecture,
        see Geyer-Schulz, A. (2025) <doi:10.5445/IR/1000187255>.
Representation-dependent gene level operations of a 
        genetic algorithm with binary coded genes
        for the R-package 'xega' <https://CRAN.R-project.org/package=xega>:
        Initialization of random binary genes, several gene maps for 
        binary genes, several mutation operators, several crossover
        operators with 1 and 2 kids, replication 
        pipelines for 1 and 2 kids, and, last but not least, function 
        factories for configuration. 
        See Goldberg, D. E. (1989, ISBN:0-201-15767-5).
        For crossover operators, see 
        Syswerda, G. (1989, ISBN:1-55860-066-3),
        Spears, W. and De Jong, K. (1991, ISBN:1-55860-208-9).
        For mutation operators, see 
        Stanhope, S. A. and Daida, J. M. (1996, ISBN:0-18-201-031-7).
        For 'xega''s architecture,
        see Geyer-Schulz, A. (2025) <doi:10.5445/IR/1000187255>.
Grammatical evolution  (see O'Neil, M. and 
        Ryan, C.  (2003,ISBN:1-4020-7444-1)) uses decoders to 
        convert linear (binary or integer genes) into programs.  
        In addition, automatic determination of codon precision 
        with a limited rule choice bias is provided.
        For a recent survey of grammatical evolution, 
        see Ryan, C., O'Neill, M., and Collins, J. J. (2018)
        <doi:10.1007/978-3-319-78717-6>.
An implementation of
        the representation-dependent gene level operations of grammar-based
        genetic programming with genes which are derivation trees
        of a context-free grammar: Initialization of a gene with a 
        complete random derivation tree, decoding of a derivation tree.
        Crossover is implemented by exchanging subtrees. Depth-bounds
        for the minimal and the maximal depth of the roots of the subtrees
        exchanged by crossover can be set. 
        Mutation is implemented by replacing a subtree by a random subtree. 
        The depth of the random subtree and the insertion node are 
        configurable. For details, 
        see Geyer-Schulz (1997, ISBN:978-3-7908-0830-X).
An implementation of 
        representation-dependent gene level operations for
        genetic algorithms with genes representing permutations: 
        Initialization of genes, mutation, and crossover.
        The crossover operation provided is position-based crossover 
        (Syswerda, G., Chap. 21 in Davis, L. (1991, ISBN:0-442-00173-8). 
        For mutation, several variants are included: Order-based mutation
        (Syswerda, G., Chap. 21 in Davis, L. (1991, ISBN:0-442-00173-8), 
        randomized Lin-Kernighan heuristics
        (Croes, G. A. (1958) <doi:10.1287/opre.6.6.791> and
         Lin, S. and Kernighan. B. W. (1973) 
        <doi:10.1287/opre.21.2.498>), 
        and randomized greedy operators.
        A random mix operator for mutation selects a mutation variant 
        randomly.
This collection of gene representation-independent functions 
   implements the population layer of extended evolutionary and genetic 
   algorithms and its support
   for the R-package 'xega' <https://CRAN.R-project.org/package=xega>.
   The population layer consists of functions 
   for initializing, logging, observing, evaluating a population of genes, 
   as well as of computing the next population. For parallel evaluation of a 
   population of genes 4 execution models - named Sequential, MultiCore, 
   FutureApply, and Cluster - are provided. They are implemented by 
   configuring the lapply() function. The execution model FutureApply can be 
   externally configured as recommended by Bengtsson (2021) 
   <doi:10.32614/RJ-2021-048>. Configurable acceptance rules and cooling 
   schedules (see Kirkpatrick, S., Gelatt, C. D. J, and Vecchi, M. P. (1983) 
   <doi:10.1126/science.220.4598.671>, and Aarts, E., and Korst, J. 
   (1989, ISBN:0-471-92146-7) offer simulated annealing or greedy randomized 
   approximate search procedure elements. Adaptive crossover and mutation 
   rates depending on population statistics generalize the approach of 
   Stanhope, S. A. and Daida, J. M. (1996, ISBN:0-18-201-031-7). 
   For 'xega''s architecture, 
   see Geyer-Schulz, A. (2025) <doi:10.5445/IR/1000187255>.
Datasets and definitions of generic functions used in dependencies of the 'xergm' package.
Read and write XES Files to create event log objects used by the 'bupaR' framework. XES (Extensible Event Stream) is the `IEEE` standard for storing and sharing event data (see <http://standards.ieee.org/findstds/standard/1849-2016.html> for more info).
Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
This tool enables in-database scoring of 'XGBoost' models built in R, by translating trained model objects into SQL query. 
  'XGBoost' <https://github.com/dmlc/xgboost> provides parallel tree boosting (also known as gradient boosting machine, or GBM) algorithms
  in a highly efficient, flexible and portable way. GBM algorithm is introduced by Friedman (2001) <doi:10.1214/aos/1013203451>, 
  and more details on 'XGBoost' can be found in Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
Extreme Gradient Boosting, which is an efficient implementation
    of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
    This package is its R interface. The package includes efficient linear
    model solver and tree learning algorithms. The package can automatically
    do parallel computation on a single machine which could be more than 10
    times faster than existing gradient boosting packages. It supports
    various objective functions, including regression, classification and ranking.
    The package is made to be extensible, so that users are also allowed to define
    their own objectives easily.
Provides the platform layer for explanation geometry in R.
    The package standardizes generic explanation tables into a normalized
    backend state object, computes embeddings, diagnostics, and multiscale
    level-of-detail summaries, and serializes backend-neutral state for
    reproducible workflows. It also exposes selected long-table and regular-grid
    views for downstream use-case packages. Rendering and viewport
    orchestration are delegated to downstream frontends such as 'ggWebGL'.
Compute surrogate explanation groves for predictive machine learning models and analyze complexity vs. explanatory power of an explanation according to Szepannek, G. and von Holt, B. (2023) <doi:10.1007/s41237-023-00205-2>.
Supports a structured approach
    for exploring PKPD data <https://opensource.nibr.com/xgx/>. It also
    contains helper functions for enabling the modeler to follow best R
    practices (by appending the program name, figure name location, and
    draft status to each plot). In addition, it enables the modeler to
    follow best graphical practices (by providing a theme that
    reduces chart ink, and by providing time-scale, log-scale, and
    reverse-log-transform-scale functions for more readable axes).
    Finally, it provides some data checking and summarizing functions for
    rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
Fits relative survival regression models with or without proportional excess hazards and with the additional possibility to correct for background mortality by one or more parameter(s). These models are relevant when the observed mortality in the studied group is not comparable to that of the general population or in population-based studies where the available life tables used for net survival estimation are insufficiently stratified. In the latter case, the proposed model by Touraine et al. (2020) <doi:10.1177/0962280218823234> can be used. The user can also fit a model that relaxes the proportional expected hazards assumption considered in the Touraine et al. excess hazard model. This extension was proposed by Mba et al. (2020) <doi:10.1186/s12874-020-01139-z> to allow non-proportional effects of the additional variable on the general population mortality. In non-population-based studies, researchers can identify non-comparability source of bias in terms of expected mortality of selected individuals. An excess hazard model correcting this selection bias is presented in Goungounga et al. (2019) <doi:10.1186/s12874-019-0747-3>. This class of model with a random effect at the cluster level on excess hazard is presented in Goungounga et al. (2023) <doi:10.1002/bimj.202100210>.
Computes Chatterjee's non-parametric correlation coefficient for time series data. It extends the original metric to time series analysis by providing the Xi-Autocorrelation Function (Xi-ACF) and Xi-Cross-Correlation Function (Xi-CCF). The package allows users to test for non-linear dependence using Iterative Amplitude Adjusted Fourier Transform (IAAFT) surrogate data with strict Family-Wise Error Rate ('FWER') control via Max-statistic approaches. Methodologies are based on Chatterjee (2021) <doi:10.1080/01621459.2020.1758115> and surrogate data testing methods by Schreiber and Schmitz (1996) <doi:10.1103/PhysRevLett.77.635>.
Computes robust association measures that do not 
    presuppose linearity. The xi correlation (xicor) is based
    on cross correlation between ranked increments.
    The reference for the methods implemented here is 
    Chatterjee, Sourav (2020) <arXiv:1909.10140>
    This package includes the Galton peas example.
Provides a simple XML tree parser/generator. It includes
        functions to read XML files into R objects, get information out of
        and into nodes, and write R objects back to XML code. It's not as
        powerful as the 'XML' package and doesn't aim to be, but for simple
        XML handling it could be useful. It was originally developed for
        the R GUI and IDE 'RKWard' <https://rkward.kde.org>, to make plugin
        development easier.
Provides custom geoms and themes to create charts and graphics in 
    the distinctive, hand-drawn 'XKCD' webcomic style using the 'ggplot2' framework. 
    The package utilizes custom layers for jittered lines, segments, circles, and 
    figures, and includes a theme that supports the necessary 'XKCD' font.
The XKCD color survey asked participants to name colours. Randall Munroe published the top thousand(roughly) names and their sRGB hex values. This package lets you use them.
Download data from individual XKCD comics, written by Randall Munroe <https://xkcd.com/>.
An R interface to the 'OpenPyXL' 'Python' library to create 
  native 'Excel' charts and work with Microsoft 'Excel' files.
Provides comprehensive functionality to read, write and format Excel data.
Parse entire folders of non-rectangular 'xlsx' files into a single
  rectangular and tidy 'data.frame' based on a custom template file defining the 
  column names of the output.
Provides a tool for non linear mapping (non linear regression) using a mixture of regression model and an inverse regression strategy. The methods include the GLLiM model (see Deleforge et al (2015) <DOI:10.1007/s11222-014-9461-5>) based on Gaussian mixtures and a robust version of GLLiM, named SLLiM (see Perthame et al (2016) <DOI:10.1016/j.jmva.2017.09.009>) based on a mixture of Generalized Student distributions. The methods also include BLLiM (see Blein--Nicolas et al (2024) <DOI:10.1093/jrsssc/qlae012>) which is an extension of GLLiM with a sparse block diagonal structure for large covariance matrices (particularly interesting for transcriptomic data).
A high-level interface for creating and exporting summary tables to
  'Excel'. Built on 'dplyr' and 'openxlsx', it provides tools for generating
  one-way to n-way tables, and summarizing multiple response questions 
  and question blocks. Tables are exported with native 'Excel' formatting, 
  including titles, footnotes, and basic styling options.
Given the date column as an ascending entry, future errors are included in the sum of squares of error that should be minimized based on the number of steps and weights you determine. Thus, it is prevented that the variables affect each other's coefficients unrealistically.
Converts an 'XLSForm' (survey in 'Excel') into a well-structured 'Word' document, including sections, skip logic, options, and question labels.
    Designed to support survey documentation, training materials, and data collection workflows.
    The package was developed based on field experience with 'XLSForm' and humanitarian operations, aiming to streamline documentation and enhance training efficiency.
Provide R functions to read/write/format Excel 2007 and Excel 97/2000/XP/2003 file formats.
Reading and writing sheets of a single 'Excel' file into and from a list of data frames. Eases I/O of tabular data in bioinformatics while keeping them in a human readable format.
The xlsxjars package collects all the external jars
  required for the xlxs package. This release corresponds to POI
  3.13.
Provides support for transformations of numeric aggregates
   between statistical classifications (e.g. occupation or industry categorisations) using the 'Crossmaps' framework. 
   Implements classes for representing transformations between a source and target classification
   as graph structures, and methods for validating and applying crossmaps to transform
   data collected under the source classification into data indexed using the target classification codes.
   Documentation about the 'Crossmaps' framework is provided in the included vignettes
   and in Huang (2024, <doi:10.48550/arXiv.2406.14163>).
A toolbox for meta-analysis. This package includes: 1,a robust multivariate meta-analysis of continuous or binary outcomes; 2, a bivariate Egger's test for detecting small study effects; 3, Galaxy Plot: A New Visualization Tool of Bivariate Meta-Analysis Studies; 4, a bivariate T&F method accounting for publication bias in bivariate meta-analysis, based on symmetry of the galaxy plot. Hong C. et al(2020) <doi:10.1093/aje/kwz286>, Chongliang L. et al(2020) <doi:10.1101/2020.07.27.20161562>.
Many approaches for both reading and
        creating XML (and HTML) documents (including DTDs), both local
        and accessible via HTTP or FTP.  Also offers access to an
        'XPath' "interpreter".
Bindings to 'libxml2' for working with XML data using a simple, 
    consistent interface based on 'XPath' expressions. Also supports XML schema
    validation; for 'XSLT' transformations see the 'xslt' package.
Helpers for transforming
    XML content into number of tables while preserving parent to child
    relationships.
Import an XML document with nested object structures and convert
    it into a relational data model. The result is a set of R dataframes 
    with foreign key relationships. The data model and the data can be exported as
    SQL code of different SQL flavors.
Converts XML documents to R dataframes and dataframes to XML documents.
  A wide variety of options allows for different XML formats and flexible control
  of the conversion process. Results can be exported to CSV and Excel, if desired. 
  Also converts XML data to R lists.
Convert the output of 'utils::getParseData()' to an 'XML'
    tree, that one can search via 'XPath', and easier to manipulate in
    general.
'XML' package for creating and reading and manipulating 'XML', with an object model based on 'Reference Classes'.
The 'XML-RPC' is a remote procedure call protocol 
    based on 'XML'. The 'xmlrpc2' package is inspired by the 'XMLRPC'
	package but uses the 'curl' and 'xml2' packages instead 'RCurl' and 'XML'.
Provides a fast and elegant interface for generating XML
 fragments and documents. It can be used in companion with R packages 'XML'
 or 'xml2' to generate XML documents. The fast XML generation is implemented using the
 'Rcpp' package.
Edit 'XMP' metadata <https://en.wikipedia.org/wiki/Extensible_Metadata_Platform> 
    in a variety of media file formats as well as 
    edit bookmarks (aka outline aka table of contents) and documentation info entries in 'pdf' files.
    Can detect and use a variety of command-line tools to perform these operations such as
    'exiftool' <https://exiftool.org/>, 'ghostscript' <https://www.ghostscript.com/>, 
    and/or 'pdftk' <https://gitlab.com/pdftk-java/pdftk>.
XMRs combine X-Bar control charts and Moving Range control charts. These functions also will recalculate the reference lines when significant change has occurred.
Fit a two-step kernel ridge regression model for
        predicting edges in networks, and carry out cross-validation
        using shortcuts for swift and accurate performance assessment
        (Stock et al, 2018 <doi:10.1093/bib/bby095> ).
Tests whether a set of counts fit a given expected ratio. For
    example, a genetic cross might be expected to produce four types in the
    relative frequencies of 9:3:3:1. To see whether a set of observed counts
    fits this expectation, one can examine all possible outcomes with xmulti() or a
    random sample of them with xmonte() and find the probability of an observation
    deviating from the expectation by at least as much as the observed. As a
    measure of deviation from the expected, one can use the log-likelihood
    ratio, the multinomial probability, or the classic chi-square statistic. A
    histogram of the test statistic can also be plotted and compared with the
    asymptotic curve.
Analysis of crossover interference in experimental crosses,
    particularly regarding the gamma model. See, for example,
    Broman and Weber (2000) <doi:10.1086/302923>.
Cross platform solution to open files, directories or 'URLs'
    with their associated programs.
Implements a probabilistic approach to time series forecasting combining XGBoost regression with conformal inference methods. The package provides functionality for generating predictive distributions, evaluating uncertainty, and optimizing hyperparameters using Bayesian, coarse-to-fine, or random search strategies.
Helps systematize and ease the process of 
    building unit tests with the 'testthat' package by providing 
    tools for generating expectations.
Allows to provide live interpretations and explanations of statistical 
    functions in R. These interpretations and explanations are shown when the explained function 
    is called by the user. They can interact with the values of the explained function's actual 
    results to offer relevant, meaningful insights. The 'xplain' interpretations and explanations 
    are based on an easy-to-use XML format that allows to include R code to interact with the 
    returns of the explained function.
Provides a consistent interface for common feature importance
    methods as described in Ewald et al. (2024)
    <doi:10.1007/978-3-031-63797-1_22>, including permutation feature
    importance (PFI), conditional and relative feature importance (CFI,
    RFI), leave one covariate out (LOCO), and Shapley additive global
    importance (SAGE), as well as feature sampling mechanisms to support
    conditional importance methods.
Tools for interactive data exploration built using 'shiny'. Includes apps for descriptive 
    statistics, visualizing probability distributions, inferential statistics, linear regression, 
    logistic regression and RFM analysis.
Provides a set of functions devoted to multivariate exploratory statistics on textual data. Classical methods such as correspondence analysis and agglomerative hierarchical clustering are available. Chronologically constrained agglomerative hierarchical clustering enriched with labelled-by-words trees is offered. Given a division of the corpus into parts, their characteristic words and documents are identified. Further, accessing to 'FactoMineR' functions is very easy. Two of them are relevant in textual domain. MFA() addresses multiple lexical table allowing applications such as dealing with multilingual corpora as well as simultaneously analyzing both open-ended and closed questions in surveys. See <http://xplortext.unileon.es> for examples.
Tools to build CDISC compliant data sets and check for CDISC
    compliance.
Diagnostics for non-linear mixed-effects (population) 
    models from 'NONMEM' <https://www.iconplc.com/solutions/technologies/nonmem/>. 
    'xpose' facilitates data import, creation of numerical run summary 
    and provide 'ggplot2'-based graphics for data exploration and model 
    diagnostics.
Extension to 'xpose' to support 'nlmixr2'. Provides functions to import 'nlmixr2' fit data into an 'xpose' data object, allowing the use of 'xpose' for 'nlmixr2' model diagnostics.
Adding some at-present missing functionality, or functions 
    unlikely to be added to the base 'xpose' package.  This includes some 
    diagnostic plots that have been missing in translation from 'xpose4', 
    but also some useful features that truly extend the capabilities of what 
    can be done with 'xpose'. These extensions include the concept of a set of
    'xpose' objects, and diagnostics for likelihood-based models.
A model building aid for nonlinear mixed-effects 
    (population) model analysis using NONMEM, facilitating data set 
    checkout, exploration and visualization, model diagnostics, candidate 
    covariate identification and model comparison. The methods are described 
    in Keizer et al. (2013) <doi:10.1038/psp.2013.24>, and Jonsson et al. (1999) 
    <doi:10.1016/s0169-2607(98)00067-4>.
There is limited native support for external pointers in the R interface.
 This package provides some basic tools to verify, create and modify 'externalptr' objects.
Support for interfaces from R to other languages,
    built around a class for evaluators and a combination of functions, classes and
    methods for communication. Will be used through a specific language interface
    package. Described in the book "Extending R".
Tools to analyze datasets previous to any statistical modeling.
    Has various functions designed to find inconsistencies and understanding the distribution of the data.
Fits flexible maximum likelihood regression models supporting censored,
    interval, and hybrid continuous/dichotomous data. Provides explicit analytic and
    numerical gradient computation, random intercept models via Gauss-Hermite
    quadrature, and multiple distribution families.
An implementation of the RuleFit algorithm as described in
    Friedman & Popescu (2008) <doi:10.1214/07-AOAS148>. eXtreme Gradient
    Boosting ('XGBoost') is used to build rules, and 'glmnet' is used to
    fit a sparse linear model on the raw and rule features. The result is
    a model that learns similarly to a tree ensemble, while often offering
    improved interpretability and achieving improved scoring runtime in
    live applications. Several algorithms for reducing rule complexity are
    provided, most notably hyperrectangle de-overlapping. All algorithms
    scale to several million rows and support sparse representations to
    handle tens of thousands of dimensions.
Contains functions to identify tree-ring borders based on X-ray micro-density profiles and a Graphical User Interface (GUI) to visualize density profiles and correct tree-ring borders. Campelo F, Mayer K, Grabner M. (2019) <doi:10.1016/j.dendro.2018.11.002>.
Fits hierarchical regularized regression models
    to incorporate potentially informative external data, Weaver and Lewinger (2019) <doi:10.21105/joss.01761>. 
    Utilizes coordinate descent to efficiently fit regularized regression models both with and without
    external information with the most common penalties used in practice (i.e. ridge, lasso, elastic net). 
    Support for standard R matrices, sparse matrices and big.matrix objects.
This is a set of statistical quality control functions,  that allows plotting control charts and its iterations, process capability for variable and attribute control, highlighting the xrs_gr() function, like a first iteration for variable chart, meanwhile the we_rules() function detects non random patterns in sample.
An extension for the 'xml2' package to transform XML documents
    by applying an 'xslt' style-sheet.
Tools for estimating HIV incidence using cross-sectional recency testing data, adjusting for internal and external target populations and supporting subtype-specific parameters. The statistical methodology implemented builds on the framework described in Wang, Duerr, and Gao(2025) <doi:10.1002/sim.70216>.
Tools to download and merge data files on sub-national conflict, violence and protests from <http://www.x-sub.org>.
Implements the bootstrap slope heterogeneity test for panel data 
    based on Blomquist and Westerlund (2015) <doi:10.1007/s00181-015-0978-z>.
    Tests the null hypothesis that slope coefficients are homogeneous across
    cross-sectional units. Provides both standard and adjusted Delta statistics
    with bootstrap p-values. Supports partialling out of control variables and
    cross-sectional averages for dealing with cross-sectional dependence.
Implements panel cointegration tests allowing for structural breaks
    and cross-section dependence following the methodology of Banerjee and
    Carrion-i-Silvestre (2015) <doi:10.1002/jae.2348>. The package provides
    iterative factor-break estimation, individual ADF tests on defactored
    residuals, standardized panel test statistics, and the Bai and Ng (2004)
    <doi:10.1111/j.1468-0262.2004.00528.x> MQ test for identifying common
    stochastic trends. Supports five model specifications with varying
    deterministic components and break structures.
Implements the Cross-Sectionally Augmented Panel Quantile 
    Autoregressive Distributed Lag (CS-PQARDL) model and the Quantile 
    Common Correlated Effects Mean Group (QCCEMG) estimator for panel data 
    with cross-sectional dependence. The package handles unobserved common 
    factors through cross-sectional averages following Pesaran (2006) 
    <doi:10.1111/j.1468-0262.2006.00692.x> and Chudik and Pesaran (2015) 
    <doi:10.1016/j.jeconom.2015.03.007>. Quantile regression for dynamic 
    panels follows Harding, Lamarche, and Pesaran (2018) 
    <doi:10.1016/j.jeconom.2018.07.010>. The ARDL approach to cointegration 
    testing is based on Pesaran, Shin, and Smith (2001) 
    <doi:10.1002/jae.616>.
Implements the Durbin-Hausman panel cointegration tests of 
    Westerlund (2008) <doi:10.1002/jae.963>. The tests are robust to 
    cross-sectional dependence through common factor extraction using 
    principal components. Provides both group-mean (DHg) and panel (DHp) 
    test statistics with automatic factor number selection via information 
    criteria.
The 'xtdml' package implements partially linear panel regression (PLPR) models with high-dimensional confounding variables and an exogenous treatment variable within the double machine learning framework. The package is used to estimate the structural parameter (treatment effect) in static panel data models with fixed effects using the approaches established in Clarke and Polselli (2025) <doi:10.1093/ectj/utaf011>. 'xtdml' is built on the object-oriented package 'DoubleML' (Bach et al., 2024) <doi:10.18637/jss.v108.i03> using the 'mlr3' ecosystem.
Implements fixed effects estimators for time-invariant variables
    in panel data models. Provides three estimation methods: FEVD (Fixed Effects
    Vector Decomposition) from Plumper and Troeger (2007) 
    <doi:10.1093/pan/mpm002>, and FEF (Fixed Effects Filtered) and FEF-IV
    (instrumental variables variant) from Pesaran and Zhou (2018)
    <doi:10.1080/07474938.2016.1222225>. All methods use the correct
    Pesaran-Zhou variance estimators that account for generated regressor
    uncertainty, avoiding the size distortions documented in the literature.
Implements the interactive fixed effects ('IFE') panel estimator of
    Bai (2009) <doi:10.3982/ECTA6135> with analytical standard errors
    ('homoskedastic', 'HC1' robust, and cluster-robust by unit). Supports
    asymptotic bias correction for large panels (Bai 2009) and a dynamic
    extension for predetermined regressors (Moon and Weidner 2017
    <doi:10.1017/S0266466615000328>). Includes information-criterion-based
    factor number selection (Bai and Ng 2002 <doi:10.1111/1468-0262.00273>).
    All computations use base R only with no external dependencies.
Estimation of Panel Quantile Autoregressive Distributed Lag 
    (PQARDL) models that combine panel ARDL methodology with quantile 
    regression. Supports Pooled Mean Group (PMG), Mean Group (MG), and 
    Dynamic Fixed Effects (DFE) estimators across multiple quantiles. 
    Computes long-run cointegrating parameters, error correction term speed 
    of adjustment, half-life of adjustment, and performs Wald tests for 
    parameter equality across quantiles. Based on the econometric frameworks 
    of Pesaran, Shin, and Smith (1999) <doi:10.1080/01621459.1999.10474156>, 
    Cho, Kim, and Shin (2015) <doi:10.1016/j.jeconom.2015.02.030>, and 
    Bildirici and Kayikci (2022) <doi:10.1016/j.energy.2022.124303>.
There are two new network metrics, RWC (random walk centrality) and CBET (counting betweenness). Also available are the normalized versions of those metrics. These measures of centrality and betweenness are particularly useful for the analysis of very dense weighted networks which include loops. Traditional measures do not work as well for those network characteristics. The main reference is DePaolis at al (2022) <doi:10.1007/s41109-022-00519-2>.
Implements the recursively detrended panel unit root tests proposed
    by Westerlund (2015) <doi:10.1016/j.jeconom.2014.09.013>. Two variants are
    provided: the basic t-REC test assuming iid errors, and the robust t-RREC
    test that accounts for serial correlation, cross-sectional dependence, and
    heteroskedasticity via defactoring and BIC-selected lag augmentation. Both
    tests have a standard normal null distribution requiring no mean or variance
    correction. The panel must be strongly balanced.
Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
Based on 'STATA' xtsum command, it is used to compute summary statistics for a panel data set. It generates overall, between-group, and within-group statistics for specified variables in a panel data set, as presented in S. Porter (2023) <https://stephenporter.org/files/xtsum_handout.pdf>, StataCorp (2023) <https://www.stata.com/manuals/xtxtsum.pdf>.
Implements an iterative mean-variance panel regression estimator
    that allows both the mean and variance of the dependent variable to be 
    functions of covariates. The method alternates between estimating a mean 
    equation (using generalized linear models with Gaussian family) and a 
    variance equation (using generalized linear models with Gamma family on 
    squared within-group residuals) until convergence. Based on the methodology 
    in Mooi-Reci and Liao (2025) <doi:10.1093/esr/jcae052>.
This is a collection of some useful functions when dealing with text data. 
    Currently it only contains a very efficient function of decoding HTML entities
    in character vectors by 'Rcpp' routine.
Calculates a number of valuation adjustments including CVA, DVA,
    FBA, FCA, MVA and KVA. A two-way margin agreement has been implemented. For
    the KVA calculation four regulatory frameworks are supported: CEM, (simplified) SA-CCR, OEM
	and IMM. The probability of default is implied through the credit spreads curve.
    The package supports an exposure calculation based on SA-CCR which includes several trade types
    and a simulated path which is currently available only for Interest Rate Swaps. The latest regulatory capital charge methodologies
    have been implementing including BA-CVA & SA-CVA.
Provides tools for reading, parsing and visualizing simulation data stored in 'xvg'/'xpm' file
  formats (commonly generated by 'GROMACS' molecular dynamics software). Streamlines post-processing
  and analysis of molecular dynamics ('MD') simulation outputs, enabling efficient exploration of
  molecular stability and conformational changes. Supports import of trajectory metrics ('RMSD',
  energy, temperature) and creation of publication-ready visualizations through integration with
  'ggplot2'.
Extrema-weighted feature extraction for varying length functional data. Functional data analysis method that performs dimensionality reduction based on predefined features and allows for quantile weighting. Method implemented as presented in van den Boom et al. (2018) <doi:10.1093/bioinformatics/bty120>.
Institutional performance assessment remains a key challenge to a multitude of stakeholders. Existing indicators such as h-type indicators, g-type indicators, and many others do not reflect expertise of institutions that defines their research portfolio. The package offers functionality to compute and visualise two novel indices: the x-index and the xd-index. The x-index evaluates an institution's scholarly expertise within a specific discipline or field, while the xd-index provides a broader assessment of overall scholarly expertise considering an institution's publication pattern and strengths across coarse thematic areas. These indices offer a nuanced understanding of institutional research capabilities, aiding stakeholders in research management and resource allocation decisions. Lathabai, H.H., Nandy, A., and Singh, V.K. (2021) <doi:10.1007/s11192-021-04188-3>. Nandy, A., Lathabai, H.H., and Singh, V.K. (2023) <doi:10.5281/zenodo.8305585>. This package provides the h-, g-, x-, xd-indices, and their variants for use with standard format of Web of Science (WoS) scrapped datasets.
Extremely fast hashing of R objects using 'xxHash'.  R objects are hashed via
    the standard serialization mechanism in R.  Raw byte vectors and strings
    can be handled directly for compatibility with hashes created on 
    other systems.  This implementation is a wrapper around the 'xxHash' 'C'
    library which is available from <https://github.com/Cyan4973/xxHash>.
Tools to analyze sex differences in omics data for complex diseases. It includes functions for differential expression analysis using the 'limma' method <doi:10.1093/nar/gkv007>, interaction testing between sex and disease, pathway enrichment with 'clusterProfiler' <doi:10.1089/omi.2011.0118>, and gene regulatory network (GRN) construction and analysis using 'igraph'. The package enables a reproducible workflow from raw data processing to biological interpretation.
An alternative canonical correlation/redundancy analysis function, with associated print, plot, and summary methods.  A method for generating helio plots is also included.
Procedures to perform consensus clustering starting from a dissimilarity matrix or a data matrix. It's allowed to select if the subsampling has to be by samples or features. In case of computational heavy load, the procedures can run in parallel.
Another implementation of general regression neural network in R
    based on Specht (1991) <DOI:10.1109/72.97934>. It is applicable to the 
    functional approximation or the classification.
Obtain historical and near real time data related to stocks, index 
    and currencies from the Yahoo Finance API. This package is community maintained 
    and is not officially supported by 'Yahoo'. The accuracy of data is only as 
    correct as provided on <https://finance.yahoo.com/>.
Performs nearest neighbor-based imputation using one or more alternative 
    approaches to processing multivariate data. These include methods based on canonical 
    correlation: analysis, canonical correspondence analysis, and a multivariate adaptation 
    of the random forest classification and regression techniques of Leo Breiman and Adele 
    Cutler. Additional methods are also offered. The package includes functions for 
    comparing the results from running alternative techniques, detecting imputation targets 
    that are notably distant from reference observations, detecting and correcting 
    for bias, bootstrapping and building ensemble imputations, and mapping results.
This collection of data exploration tools was developed at
    Yale University for the graphical exploration of complex
    multivariate data; barcode and gpairs now have their own
    packages.  The big.read.table() function provided here may be
    useful for large files when only a subset is needed (but please
    see the note in the help page for this function).
Implements the 'libyaml' 'YAML' 1.1 parser and emitter
    (<https://pyyaml.org/wiki/LibYAML>) for R.
A fast, correct, safe, and ergonomic 'YAML' 1.2 parser and
    generator written in 'Rust'. Convert between 'YAML' and simple 'R'
    objects with full support for multi-document streams, tags, anchors,
    and aliases. Offers opt-in handlers for custom tag behavior and
    round-trips common 'R' data structures. Implements the 'YAML' 1.2.2
    specification from the 'YAML' Language Development Team (2021)
    <https://yaml.org/spec/1.2.2/>. Proudly supported by Posit.
A YAML-based
 mechanism for working with table metadata. Supports
 compact syntax for creating, modifying, viewing, exporting,
 importing, displaying, and plotting metadata coded as column 
 attributes. The 'yamlet' dialect is valid 'YAML' with
 defaults and conventions chosen to improve readability. 
 See ?yamlet, ?decorate, ?modify, ?io_csv, and ?ggplot.decorated.
Setting layout through 'YAML' headers in 'R-Markdown' documents,
    enabling their automatic generation.
    Functions and methods may summarize 'R' objects in automatic reports, for
    instance check-lists and further reports applied to the packages 'taxlist'
    and 'vegtable'.
The generalized construction methods for magic squares, inspired by the ancient Chinese mathematician Yang Hui's classical work "Xu Gu Zhai Qi Suan Fa". These methods can construct 4n-order magic squares and 2(2n+1)-order magic squares.
Tidy tools for quantifying how well model fits to a data set
    such as confusion matrices, class probability curve summaries, and
    regression metrics (e.g., RMSE).
Contains a mixture of functions and data sets referred to in the introductory e-book "YaRrr!: The Pirate's Guide to R". The latest version of the e-book is available for free at <https://bookdown.org/ndphillips/YaRrr/>.
A collection of string functions designed for writing 
    compact and expressive R code. 'yasp' (Yet Another String Package) is simple,
    fast, dependency-free, and written in pure R. The package provides: a
    coherent set of abbreviations for paste() from package 'base' with a
    variety of defaults, such as p() for "paste" and pcc() for "paste and
    collapse with commas"; wrap(), bracket(), and others for wrapping a
    string in flanking characters; unwrap() for removing pairs of characters
    (at any position in a string); and sentence() for cleaning whitespace
    around punctuation and capitalization appropriate for prose sentences.
Provides functions to manage taxonomy when lineages are
    described with strings and ranks separated with special patterns like
    "|*__" or ";*__".
Test of linearity originally proposed by Yatchew (1997) <doi:10.1016/S0165-1765(97)00218-8> and improved by de Chaisemartin & D'Haultfoeuille (2024) <doi:10.2139/ssrn.4284811> to be robust under heteroskedasticity.
Determines the sum of squares of the (2^n)-1 factorial effects in a 2^n factorial experiment using Yates' algorithm.
Nonparametric estimation of discount functions and yield curves from 
    transaction data of coupon paying bonds. 
    Koo, B., La Vecchia, D., & Linton, O. B. (2021) <doi:10.1016/j.jeconom.2020.04.014> 
    describe an application of this package using the Center for Research in 
    Security Prices (CRSP) Bond Data and document its implementation.
Analyze data from behavioral experiments conducted using 'MED-PC' software developed by Med Associates Inc. 
	Includes functions to fit exponential and hyperbolic models for delay discounting tasks, exponential mixtures for 
	inter-response times, and Gaussian plus ramp models for peak procedure data, among others. For more details, refer to Alcala et al. (2023) <doi:10.31234/osf.io/8aq2j>.
Asks Yes-No questions with variable or custom responses.
Simple and efficient access to Yahoo Finance's historical data API <https://finance.yahoo.com/> for querying and retrieval of financial data. The core functionality of the 'yfhist' package abstracts the complexities of interacting with Yahoo Finance APIs, such as session management, crumb and cookie handling, query construction, date validation, and interval management. This abstraction allows users to focus on retrieving data rather than managing API details. Use cases include historical data across a range of security types including equities & ETFs, indices, and other tickers. The package supports flexible query capabilities, including customizable date ranges, multiple time intervals, and automatic data validation. It automatically manages interval-specific limitations, such as lookback periods for intraday data and maximum date ranges for minute-level intervals. The implementation leverages standard HTTP libraries to handle API interactions efficiently and provides support for both R and 'Python' to ensure accessibility for a broad audience.
Download financial market data, company information, financial statements, options data, and more from the unofficial 'Yahoo Finance' API.
Facilitates download of financial data from Yahoo Finance <https://finance.yahoo.com/>, 
 a vast repository of stock price data across multiple financial exchanges. The package offers a local caching system
 and support for parallel computation.
Simple and efficient access to Yahoo Finance's 'screener' API <https://finance.yahoo.com/research-hub/screener/> for querying and retrieval of financial data. The core functionality abstracts the complexities of interacting with Yahoo Finance APIs, such as session management, crumb and cookie handling, query construction, pagination, and JSON payload generation. This abstraction allows users to focus on filtering and retrieving data rather than managing API details. Use cases include screening across a range of security types including equities, mutual funds, ETFs, indices, and futures. The package supports advanced query capabilities, including logical operators, nested filters, and customizable payloads. It automatically handles pagination to ensure efficient retrieval of large datasets by fetching results in batches of up to 250 entries per request. Filters can be dynamically defined to accommodate a wide range of screening needs. The implementation leverages standard HTTP libraries to handle API interactions efficiently and provides support for both R and Python to ensure accessibility for a broad audience.
The purpose of this package is to provide methods to interpret multiple
  linear regression and canonical correlation results including beta weights,structure coefficients, 
  validity coefficients, product measures, relative weights, all-possible-subsets regression,
  dominance analysis, commonality analysis, and adjusted effect sizes.
Modelling the yield curve with some parametric models.
        The models implemented are: 
		Nelson, C.R., and A.F. Siegel (1987) <doi: 10.1086/296409>, 
		Diebold, F.X. and Li, C. (2006) <doi: 10.1016/j.jeconom.2005.03.005> 
		and Svensson, L.E. (1994) <doi: 10.3386/w4871>. 
		The package also includes the data of the term structure of interest rate of Federal Reserve Bank and European Central Bank.
Fits yield curves using Nelson-Siegel (1987)
    <doi:10.1086/296409>, Svensson (1994) <doi:10.3386/w4871>, and cubic
    spline methods. Extracts forward rates, discount factors, and par rates
    from fitted curves. Computes duration and convexity risk measures.
    Computes Z-spread and key rate durations. Provides principal component
    decomposition following Litterman and Scheinkman (1991)
    <doi:10.3905/jfi.1991.692347>, carry and roll-down analysis, and slope
    measures. All methods are pure computation with no
    external dependencies beyond base R; works with yield data from any
    source.
Compute the standard expected years of life lost (YLL),
    as developed by the Global Burden of Disease Study
    (Murray, C.J., Lopez, A.D. and World Health Organization, 1996).
    The YLL is based on comparing the age of death to an external standard life
    expectancy curve. It also computes the average YLL, which highlights premature
    causes of death and brings attention to preventable deaths
    (Aragon et al., 2008).
Convert 'YMD' format number or string to Date efficiently, using Rust's
    standard library. It also provides helper functions to handle Date, e.g., quick
    finding the beginning or end of the given period, adding months to Date, etc.
The Author's personal R Package that contains miscellaneous functions. 
    The current version of package contains miscellaneous functions for brain data 
    to compute Asymmetry Index (AI) and bilateral (L+R) measures and reshape the data.
Write 'YAML' front matter for R Markdown and related
    documents. Work with 'YAML' objects more naturally and write the
    resulting 'YAML' to your clipboard or to 'YAML' files related to your
    project.
Provides a collection of lightweight helper functions (imps) both
  for interactive use and for inclusion within other packages. These include
  functions for minimal input assertions, visualising colour palettes,
  quoting user input, searching rows of a data frame and capturing string
  tokens.
Provides helper functions to perform Bayesian model averaging
    using Markov chain Monte Carlo samples from separate models. Calculates
    weights and obtains draws from the model-averaged posterior for quantities
    of interest specified by the user. Weight calculations can be done using
    marginal likelihoods or log-predictive likelihoods as in Ando, T., & Tsay,
    R. (2010) <doi:10.1016/j.ijforecast.2009.08.001>.
Analyzing performances of cricketers and cricket teams
             based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.
Dataset from the young elite swimmers study.
Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with baseline hazard/odds modeled with Bernstein polynomials. Details about the model can be found in Demarqui et al. (2019) <arXiv:1910.04475>. Model fitting can be carried out via both maximum likelihood and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.
For any spending function specified by the user, this 
    package provides corresponding boundaries for interim testing using
    the adaptively weighted log-rank test developed by Yang and Prentice
    (2010 <doi:10.1111/j.1541-0420.2009.01243.x>). 
    The package uses a re-sampling method to obtain stopping boundaries 
    at the interim looks.The output consists of stopping boundaries 
    and observed values of the test statistics at the interim looks, 
    along with nominal p-values defined as the probability of the test 
    exceeding the specific observed test statistic value or critical 
    value, regardless of the test behavior at other looks. 
    The asymptotic validity of the stopping boundaries is established
    in Yang (2018 <doi:10.1002/sim.7958>).
Inference procedures accommodate a flexible range of hazard ratio patterns with a two-sample semi-parametric model. This model contains the proportional hazards model and the proportional odds model as sub-models, and accommodates non-proportional hazards situations to the extreme of having crossing hazards and crossing survivor functions. Overall, this package has four major functions: 1) the parameter estimation, namely short-term and long-term hazard ratio parameters; 2) 95 percent and 90 percent point-wise confidence intervals and simultaneous confidence bands for the hazard ratio function; 3) p-value of the adaptive weighted log-rank test; 4) p-values of two lack-of-fit tests for the model. See the included "read_me_first.pdf" for brief instructions. In this version (1.1), there is no need to sort the data before applying this package.
Provides covariate-adjusted comparison of two groups of right 
    censored data, where the binary group variable has separate short-term 
    and long-term effects on the hazard function, while effects of covariates 
    such as age, blood pressure, etc. are proportional on the hazard. The model 
    was studied in Yang and Prentice (2015) <doi:10.1002/sim.6453> and it extends 
    the two sample version of the short-term and long-term hazard ratio model
    proposed in Yang and Prentice (2005) <doi:10.1093/biomet/92.1.1>. The model 
    extends the usual Cox proportional hazards model to allow more flexible 
    hazard ratio patterns, such as gradual onset of effect, diminishing effect, 
    and crossing hazard or survival functions. This package provides 
    the following: 1) point estimates and confidence intervals for model 
    parameters; 2) point estimate and confidence interval of the average hazard 
    ratio; and 3) plots of estimated hazard ratio function with point-wise and 
    simultaneous confidence bands.
Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with piecewise exponential baseline distribution. Details about the model can be found in Demarqui and Mayrink (2019) <arXiv:1910.02406>. Model fitting carried out via likelihood-based and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.
An implementation of equilibrium-based yield per recruit
    methods.  Yield per recruit methods can used to estimate the optimal
    yield for a fish population as described by Walters and Martell (2004)
    <isbn:0-691-11544-3>.  The yield can be based on the number of fish
    caught (or harvested) or biomass caught for all fish or just large
    (trophy) individuals.
Provides with parametric risk neutral densities and cumulative densities for futures prices on fixed-income products. It relies on options on Short Term Interest Rate futures contracts or options on government bond futures contracts. It models the price of the underlying asset as a mixture of either two or three lognormal densities. It also offers new functions which provide with risk neutral densities and cumulative densities of the money market rate or the government bond yield inferred from the futures contract's price, using the density of the futures price. The package leverages on the works of Melick, W. R. and Thomas, C. P. (1997) <doi:10.2307/2331318> and B. Bahra (1998) <doi:10.2139/ssrn.77429>.
Simplify working with the 'YouTube Analytics' API <https://developers.google.com/youtube/analytics>. Collect 
    data for your channel including geography, traffic sources, time period, etc.
Simulation and Inference for SDEs and Other Stochastic Processes.
Provides a graphical user interface for the 'yuima' package.
Miscellaneous functions commonly used by 'YuLab-SMU'.
Provides a number of functions to facilitate
  extracting information in 'YAML' fragments from one or 
  multiple files, optionally structuring the information
  in a 'data.tree'. 'YAML' (recursive acronym for "YAML ain't
  Markup Language") is a convention for specifying structured
  data in a format that is both machine- and human-readable.
  'YAML' therefore lends itself well for embedding (meta)data
  in plain text files, such as Markdown files. This principle
  is implemented in 'yum' with minimal dependencies (i.e. only
  the 'yaml' packages, and the 'data.tree' package can be
  used to enable additional functionality).
A fast 'JSON' parser, generator and validator which converts 'JSON', 
    'NDJSON' (Newline Delimited 'JSON') and 'GeoJSON' (Geographic 'JSON') data 
    to/from R objects.  The standard R data types are 
    supported (e.g. logical, numeric, integer) with configurable handling of NULL 
    and NA values. Data frames, atomic vectors and lists are all supported as data 
    containers translated to/from 'JSON'.  'GeoJSON' data is read in as
    'simple features' objects.
    This implementation wraps the 'yyjson' 'C' library which 
    is available from <https://github.com/ibireme/yyjson>.
Provides simple statistics from instruments and observations at sites in the NEON network, and acts as a simple interface for v0 of the National Ecological Observatory Network (NEON) API.
  Statistics are generated for meteorologic and soil-based observations, and are presented for daily, annual, and one-time observations at all available NEON sites.
  Users can also retrieve any dataset publicly hosted by NEON. Metadata for NEON sites and data products can be returned, as well as information on data product availability by site and date. 
  For more information on NEON, please visit <https://www.neonscience.org>. For detailed data product information, please see the NEON data product catalog at <https://data.neonscience.org/data-product-catalog>.
Provides fast and easy access to German census grid data
    from the 2011 and 2022 censuses <https://www.zensus2022.de/>, including a
    wide range of socio-economic indicators at multiple spatial resolutions
    (100m, 1km, 10km). Enables efficient download, processing, and analysis
    of large census datasets covering population, households, families,
    dwellings, and buildings. Harmonized data structures allow direct
    comparison with the 2011 census, supporting temporal and spatial analyses.
    Facilitates conversion of data into common formats for spatial analysis and
    mapping ('terra', 'sf', 'ggplot2').
A suite of statistics for identifying areas of the genome under selective pressure. See Jacobs, Sluckin and Kivisild (2016) <doi:10.1534/genetics.115.185900>.
The 'Zarr' specification is widely used to build libraries for the storage and retrieval of n-dimensional array data from data stores ranging from local file systems to the cloud. This package is a native 'Zarr' implementation in R with support for all required features of 'Zarr' version 3. It is designed to be extensible such that new stores, codecs and extensions can be added easily.
Principled methods for the imputation of zeros, left-censored and missing data in
    compositional data sets (Palarea-Albaladejo and Martin-Fernandez (2015) <doi:10.1016/j.chemolab.2015.02.019>).
Contains the US Census Bureau's 2020 ZCTA to County Relationship 
    File, as well as convenience functions to translate between States, Counties
    and ZIP Code Tabulation Areas (ZCTAs).
An implementation of z-curves - a method for estimating expected discovery 
    and replicability rates on the bases of test-statistics of published studies. The package 
    provides functions for fitting the density, EM, and censored EM version (Bartoš & Schimmack, 2022,
    <doi:10.15626/MP.2021.2720>; Schimmack & Bartoš, 2023, <doi: 10.1371/journal.pone.0290084>),
    as well as the original density z-curve (Brunner & Schimmack, 2020, <doi:10.15626/MP.2018.874>). 
    Furthermore, the package provides summarizing and plotting functions for the fitted z-curve objects. 
    See the aforementioned articles for more information about the z-curves, expected discovery 
    and replicability rates, validation studies, and limitations.
Facilitates making a connection to the 
  'Zendesk' API and executing various queries. You can use it to
  get ticket, ticket metrics, and user data. The 'Zendesk' documentation is 
  available at <https://developer.zendesk.com/rest_api
  /docs/support/introduction>. This package is not supported by 
  'Zendesk' (owner of the software).
Provides a %<-% operator to perform multiple,
    unpacking, and destructuring assignment in R. The
    operator unpacks the right-hand side of an assignment
    into multiple values and assigns these values to
    variables on the left-hand side of the assignment.
Implements the estimation of local (and global) association measures: Lewontin's D, Ducher's Z, pointwise mutual information, normalized pointwise mutual information and chi-squared residuals. The significance of local (and global) association is accessed using p-values estimated by permutations.
Use behavioural variables to compute period, rhythmicity and other circadian parameters.
  Methods include computation of chi square periodograms (Sokolove and Bushell (1978) <DOI:10.1016/0022-5193(78)90022-X>),
  Lomb-Scargle periodograms (Lomb (1976) <DOI:10.1007/BF00648343>, Scargle (1982) <DOI:10.1086/160554>, Ruf (1999) <DOI:10.1076/brhm.30.2.178.1422>),
  and autocorrelation-based periodograms.
Provides an Interface to 'Zenodo' (<https://zenodo.org>) REST API, 
  including management of depositions, attribution of DOIs by 'Zenodo' and 
  upload and download of files.
This package provides an R wrapper for the Zendesk API
Access, download and locally cache files deposited on 'Zenodo' <https://zenodo.org>.
Graphical tools for visualizing high-dimensional data along a
    path of alternating one- and two-dimensional plots. Includes optional
    interactive graphics via 'loon' (which uses 'tcltk' from base R).
    Support is provided for constructing graph structures and, when
    available, plotting them with Bioconductor packages (e.g., 'graph',
    'Rgraphviz'); these are optional and examples/vignettes are skipped if
    they are not installed. For algorithms and further details, see
    <doi:10.18637/jss.v095.i04>.
Fetch statistics about views, downloads and data volume from 'Zenodo' deposits. The package collects a 'Zenodo' (<https://zenodo.org>) deposit file information, respecting the website scrapping policies.
Procedures for calculation, plotting, animation, and approximation of the outputs for fuzzy numbers (see A.I. Ban, L. Coroianu, P. Grzegorzewski "Fuzzy Numbers: Approximations, Ranking and Applications" (2015)) based on the Zadeh's Extension Principle (see de Barros, L.C., Bassanezi, R.C., Lodwick, W.A. (2017) <doi:10.1007/978-3-662-53324-6_2>).
Provides a structured framework for consistent user
    communication and configuration management for package developers.
Uses bootstrap to test zero order correlation being equal to a 
    partial or semi-partial correlation (one or two tailed). Confidence 
    intervals for the parameter (zero order minus partial) can also be
    determined. Implements the bias-corrected and accelerated bootstrap
    method as described in "An Introduction to the Bootstrap" Efron (1983) 
    <0-412-04231-2>.
Implementation of new statistical distributions in (0, 1) interval. Each distribution includes the traditional functions as well as an additional function called the family function, which can be used to estimate parameters using Generalized Additive
    Models for Location, Scale and Shape, GAMLSS by Rigby & Stasinopoulos
    (2005) <doi:10.1111/j.1467-9876.2005.00510.x>.
Functions to compute compositional turnover using zeta-diversity,
    the number of species shared by multiple assemblages. The package includes
    functions to compute zeta-diversity for a specific number of
    assemblages and to compute zeta-diversity for a range of numbers of
    assemblages. It also includes functions to explain how zeta-diversity
    varies with distance and with differences in environmental variables
    between assemblages, using generalised linear models, linear models
    with negative constraints, generalised additive models,shape
    constrained additive models, and I-splines.
The advent of genomic technologies has enabled the generation of two-dimensional or even multi-dimensional high-throughput data, e.g., monitoring multiple changes in gene expression in genome-wide siRNA screens across many different cell types (E Robert McDonald 3rd (2017) <doi: 10.1016/j.cell.2017.07.005> and Tsherniak A (2017) <doi: 10.1016/j.cell.2017.06.010>) or single cell transcriptomics under different experimental conditions. We found that simple computational methods based on a single statistical criterion is no longer adequate for analyzing such multi-dimensional data. We herein introduce 'ZetaSuite', a statistical package initially designed to score hits from two-dimensional RNAi screens.We also illustrate a unique utility of 'ZetaSuite' in analyzing single cell transcriptomics to differentiate rare cells from damaged ones (Vento-Tormo R (2018) <doi: 10.1038/s41586-018-0698-6>). In 'ZetaSuite', we  have the following steps: QC of input datasets, normalization using Z-transformation, Zeta score calculation and hits selection based on defined Screen Strength.
Performs Zoom-Focus Algorithm (ZFA) to optimize testing regions for rare variant association tests in exome sequencing data.
Improve the usage of model fitting functions within a piped
    work flow.
A two-part zero-inflated Beta regression model with random 
    effects (ZIBR) for testing the association between microbial abundance 
    and clinical covariates for longitudinal microbiome data. Eric Z. Chen 
    and Hongzhe Li (2016) <doi:10.1093/bioinformatics/btw308>.
Parameter estimation for zero-inflated discrete Weibull (ZIDW) regression models, the univariate setting, distribution functions, functions to generate randomized quantile residuals a pseudo R2, and plotting of rootograms. For more details, see Kalktawi (2017)  <https://bura.brunel.ac.uk/handle/2438/14476>, Taconeli and Rodrigues de Lara (2022) <doi:10.1080/00949655.2021.2005597>, and Yeh and Young (2025) <doi:10.1080/03610918.2025.2464076>.
The 'Ziggurat' pseudo-random number generator (or PRNG),
 introduced by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>) and
 further improved by Leong et al (2005, <doi:10.18637/jss.v012.i07>), offers
 a lightweight and very fast PRNG for the normal, exponential, and uniform
 distributions. It is provided here in a small zero-dependency package. It can
 be used from R as well as from 'C/C++' code in other packages as is demonstrated
 by four included sample packages using four distinct methods to use the PRNG
 presented here in client package. The implementation is influenced by our
 package 'RcppZiggurat' which offers a comparison among multiple alternative
 implementations but presented here in a lighter-weight implementation that is
 easier to use by other packages. The PRNGs provided are generally faster than
 the ones in base R: on our machine, the relative gains for normal, exponential
 and uniform are on the order of 7.4, 5.2 and 4.7 times faster than base R.
 However, these generators are of potentially lesser quality and shorter period
 so if in doubt use of the base R functions remains the general recommendation.
Provides tools for estimating Zero-Inflated INAR(1) 
    (ZI-INAR(1)) and Hurdle INAR(1) (H-INAR(1)) models using 'Stan'. 
    It allows users to simulate time series data for these models, 
    estimate parameters, and evaluate model fit using various criteria. 
    Functions include model estimation, simulation, and likelihood-based metrics.
Analyze count time series with excess zeros. 
    Two types of statistical models are supported: Markov regression by Yang et al.
    (2013) <doi:10.1016/j.stamet.2013.02.001> and state-space models by Yang et al. 
    (2015) <doi:10.1177/1471082X14535530>. They are also known as observation-driven and 
    parameter-driven models respectively in the time series literature. The functions used for 
    Markov regression or observation-driven models can also be used to fit ordinary regression models 
    with independent data under the zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB) 
    assumption. Besides, the package contains some miscellaneous functions to compute density, distribution, 
    quantile, and generate random numbers from ZIP and ZINB distributions.
Gene‐based association tests to model count data with excessive zeros and rare variants using zero-inflated Poisson/zero-inflated negative Binomial regression framework. This method was originally described by Fan, Sun, and Li in Genetic Epidemiology 46(1):73-86 <doi:10.1002/gepi.22438>.
Generates Realizations of First-Order Integer Valued Autoregressive Processes with Zero-Inflated Innovations (ZINAR(1)) and Estimates its Parameters as described in Garay et al. (2021) <doi:10.1007/978-3-030-82110-4_2>.
Simulation, exploratory data analysis and Bayesian analysis of the p-order Integer-valued Autoregressive (INAR(p)) and Zero-inflated p-order Integer-valued Autoregressive (ZINAR(p)) processes, as described in Garay et al. (2020) <doi:10.1080/00949655.2020.1754819>.
Cross-Platform 'zip' Compression Library. A replacement for
    the 'zip' function, that does not require any additional external
    tools on any platform.
Implementation of zero-inflated Poisson models under Bayesian framework using data augmentation as discussed in Chapter 5 of Zhang (2020) <https://hdl.handle.net/10012/16378>. This package is constructed in accommodating four different scenarios: the general scenario, the scenario with measurement error in responses, the external validation scenario, and the internal validation scenario.
Make working with ZIP codes in R painless with an integrated dataset of U.S. ZIP codes and functions for working with them. 
             Search ZIP codes by multiple geographies, including state, county, city & across time zones. Also included are functions for relating
             ZIP codes to Census data, geocoding & distance calculations.
Estimation methods for zero-inflated Poisson factor analysis (ZIPFA) on sparse data. 
    It provides estimates of coefficients in a new type of zero-inflated regression. 
    It provides a cross-validation method to determine the potential rank of the data in the ZIPFA 
    and conducts zero-inflated Poisson factor analysis based on the determined rank.
Implementation of four extensions of the Zipf distribution: the Marshall-Olkin 
  Extended Zipf (MOEZipf) Pérez-Casany, M., & Casellas, A. (2013) <arXiv:1304.4540>, the Zipf-Poisson Extreme (Zipf-PE), the 
  Zipf-Poisson Stopped Sum (Zipf-PSS) and the Zipf-Polylog distributions. 
  In log-log scale, the two first extensions allow for top-concavity 
  and top-convexity while the third one only allows for top-concavity. 
  All the extensions maintain the linearity associated with the Zipf model in the tail.
Statistical models and utilities for the analysis of word frequency distributions.
	The utilities include functions for loading, manipulating and visualizing word frequency
	data and vocabulary growth curves.  The package also implements several statistical 
	models for the distribution of word frequencies in a population.  (The name of this package 
	derives from the most famous word frequency distribution, Zipf's law.)
We provide a flexible Zero-inflated Poisson-Gamma Model (ZIPG) by connecting both the mean abundance and the variability to different covariates, and build valid statistical inference procedures for both parameter estimation and hypothesis testing. These functions can be used to analyze microbiome count data with zero-inflation and overdispersion. The model is discussed in Jiang et al (2023) <doi:10.1080/01621459.2022.2151447>.
Provides a set of functions for working with American postal codes,
   which are known as ZIP Codes. These include accessing ZIP Code to ZIP Code 
   Tabulation Area (ZCTA) crosswalks, retrieving demographic data for ZCTAs, and 
   tabulating demographic data for three-digit ZCTAs.
Implements Python-style zip for R. Is a more flexible version of cbind.
Permutations tests to identify factor correlated to zero-inflated proportions response. Provide a performance indicator based on Spearman correlation to quantify the part of correlation explained by the selected set of factors. See details for the method at the following preprint e.g.: <https://hal.archives-ouvertes.fr/hal-02936779v3>.
This function produces empirical best linier unbiased predictions (EBLUPs) for Zero-Inflated data and its Relative Standard Error. Small Area Estimation with Zero-Inflated Model (SAE-ZIP) is a model developed for Zero-Inflated data that can lead us to overdispersion situation. To handle this kind of situation, this model is created. The model in this package is based on Small Area Estimation with Zero-Inflated Poisson model proposed by Dian Christien Arisona (2018)<https://repository.ipb.ac.id/handle/123456789/92308>. For the data sample itself, we use combination method between Roberto Benavent and Domingo Morales (2015)<doi:10.1016/j.csda.2015.07.013> and Sabine Krieg, Harm Jan Boonstra and Marc Smeets (2016)<doi:10.1515/jos-2016-0051>.
Assesses evidence for Zipf's Law of Abbreviation in animal vocalisation using IDs, note class and note duration. The package also provides a web plot function for visualisation.
The 'zlib' package for R aims to offer an R-based equivalent of 'Python's' built-in 'zlib' module for data compression and decompression. This package provides a suite of functions for working with 'zlib' compression, including utilities for compressing and decompressing data streams, manipulating compressed files, and working with 'gzip', 'zlib', and 'deflate' formats.
Transformation of laboratory measurements into z or z(log)-value
    based on given or empirical reference limits as proposed in
    Hoffmann et al. 2017 <doi:10.1515/labmed-2016-0087>.
Implements zero-modified versions of the Complex 'Tri-Parametric'
    Pearson distribution for overdispersed count data. The package addresses
    limitations of existing implementations when the parameter b approaches
    zero. It provides distribution functions, maximum likelihood estimation,
    and diagnostic tools for modeling count data with excess zeros. The
    methodology is based on 'Rodriguez-Avi' and coauthors (2003)
    <doi:10.1007/s00362-002-0134-7>.
A collection of utility functions that facilitate looking up
    vector values from a lookup table, annotate values in at table for 
    clearer viewing, and support a safer approach to vector sampling, 
    sequence generation, and aggregation.
Calculate and plot scattering matrix coefficients for plane waves at interface.
Fits beta regression and zero-or-one inflated beta regression and obtains Bayesian Inference of the model via the Markov Chain Monte Carlo approach implemented in JAGS.
Fits Dirichlet regression and zero-and-one inflated Dirichlet regression with Bayesian methods implemented in Stan. These models are sometimes referred to as trinomial mixture models; covariates and overdispersion can optionally be included.
'Zoltar' <https://www.zoltardata.com/> is a website that provides a repository of model forecast results
    in a standardized format and a central location. It supports storing, retrieving, comparing, and analyzing time
    series forecasts for prediction challenges of interest to the modeling community. This package provides functions
    for working with the 'Zoltar' API, including connecting and authenticating, getting meta information (projects,
    models, and forecasts, and truth), and uploading, downloading, and deleting forecast and truth data.
An interface to 'Zonation' software, enabling users to run spatial 
 conservation prioritization workflows in 'R'. It streamlines input preparation, 
 execution, and post-processing, while supporting reproducibility and lowering the 
 entry barrier for learning, teaching, and research in conservation planning. 
 The methods implemented in 'Zonation' are described in Moilanen et al. (2022) <doi:10.1111/2041-210X.13819>.
Functions, documentation and example data to help divide
    geographic space into discrete polygons (zones).
    The package supports new zoning systems that are documented in the
    accompanying paper,
    "ClockBoard: A zoning system for urban analysis",
    by Lovelace et al. (2022) <doi:10.5311/JOSIS.2022.24.172>.
    The functions are motivated by research into the merits of different zoning systems
    (Openshaw, 1977) <doi:10.1068/a090169>. A flexible ClockBoard zoning system is
    provided, which breaks-up space by concentric rings
    and radial lines emanating from a central point.
    By default, the diameter of the rings grow according to the triangular number sequence
    (Ross & Knott, 2019) <doi:10.1080/26375451.2019.1598687> with the first 4 doughnuts
    (or annuli) measuring 1, 3, 6, and 10 km wide.
    These annuli are subdivided into equal segments (12 by default), creating the
    visual impression of a dartboard. Zones are labelled according to
    distance to the centre and angular distance from North, creating a simple
    geographic zoning and labelling system useful for visualising geographic
    phenomena with a clearly demarcated central location such as cities.
Computes a zonohedron from real vector generators.  The package also computes zonogons (2D zonotopes) and zonosegs (1D zonotopes).  An elementary S3 class for matroids is included, which supports matroids with rank 3, 2, and 1.  Optimization methods are taken from Heckbert (1985) <https://www.cs.cmu.edu/~ph/zono.ps.gz>.
An S3 class with methods for totally ordered indexed
             observations. It is particularly aimed at irregular time series
             of numeric vectors/matrices and factors. zoo's key design goals
             are independence of a particular index/date/time class and
             consistency with ts and base R by providing methods to extend
             standard generics.
This tool provides functions to load, segment and classify zooplankton images. 
  The image processing algorithms and the machine learning classifiers in this package are (will be, since these have not been added yet) direct ports of 
  an early 'python' implementation that can be found at <https://github.com/arickGrootveld/ZooID>. The model weights and datasets (also not added yet) 
  that are a part of this package can also be found at Arick Grootveld, Eva R. Kozak, Carmen Franco-Gordo (2023) <doi:10.5281/zenodo.7979996>.
A free (open source) solution for analyzing digital
  images of plankton. In combination with ImageJ, a free image analysis
  system, it processes digital images, measures individuals, trains for
  automatic classification of taxa, and finally, measures plankton samples
  (abundances, total and partial size spectra or biomasses, etc.).
Includes functions and reference data to 
    generate and manipulate log-ratios (also known as log size index (LSI)
    values) from measurements obtained on zooarchaeological material. Log
    ratios are used to compare the relative (rather than the absolute)
    dimensions of animals from archaeological contexts 
    (Meadow 1999, ISBN: 9783896463883).
    zoolog is also able to seamlessly integrate data and references 
    with heterogeneous nomenclature, which is internally managed by a 
    zoolog thesaurus. 
    A preliminary version of the zoolog methods was first used by 
    Trentacoste, Nieto-Espinet, and Valenzuela-Lamas (2018) 
    <doi:10.1371/journal.pone.0208109>.
You can call zm(), when displaying any active plot to enter an
    interactive session to zoom/navigate any plot. The development
    version, as well as binary releases can be found at
    <https://github.com/cbarbu/R-package-zoom>.
Empowers users to fuzzily-merge data frames with millions or tens of millions of rows in minutes with low memory usage.  The package uses the locality sensitive hashing algorithms developed by Datar, Immorlica, Indyk and Mirrokni (2004) <doi:10.1145/997817.997857>, and Broder (1998) <doi:10.1109/SEQUEN.1997.666900> to avoid having to compare every pair of records in each dataset, resulting in fuzzy-merges that finish in linear time.
Implements a grid search algorithm with an adaptive zooming strategy 
    for global optimisation problems with multiple local optima. 
    The method recursively refines the search region around promising grid points, 
    providing reliable initial values for subsequent optimisation procedures. 
    The algorithm is computationally efficient in moderate- to high-dimensional settings.
Provides utilities for processing and analyzing the files that are exported from a recorded 'Zoom' Meeting. This includes analyzing data captured through video cameras and microphones, the text-based chat, and meta-data. You can analyze aspects of the conversation among meeting participants and their emotional expressions throughout the meeting.
Facilitates making a connection to the 'Zoom' API and executing
  various queries. You can use it to get data on 'Zoom' webinars and 'Zoom'
  meetings. The 'Zoom' documentation is available at 
  <https://developers.zoom.us/docs/api/>. This package is 
  not supported by 'Zoom' (owner of the software).
Connects R to 'Zotero' through the 'Better BibTeX' for 'Zotero'
    connector <https://retorque.re/zotero-better-bibtex/>. Provides
    functions to insert in-text citations and bibliography entries
    directly into documents, detect citations already present in
    R Markdown and Quarto files, and synchronise bibliography files.
    Includes an 'RStudio addin' for interactive use.
Combines a forecast of a time series, using the function forecast(), with the dynamic plots from dygraphs.
A tool for calculating z-scores and centiles for weight-for-age, 
    length/height-for-age, weight-for-length/height, BMI-for-age, 
    head circumference-for-age, age circumference-for-age, 
    subscapular skinfold-for-age, triceps skinfold-for-age based on the 
    WHO Child Growth Standards.
Generates well-known integer sequences. 'gmp' package is adopted for computing with arbitrarily large numbers. Every function has hyperlink to its corresponding item in OEIS (The On-Line Encyclopedia of Integer Sequences) in the function help page. For interested readers, see Sloane and Plouffe (1995, ISBN:978-0125586306).
Makes zebra-striped tables (tables with alternating row colors)
    in LaTeX and HTML formats easily from a data.frame, matrix, lm, aov, anova,
    glm, coxph, nls, fitdistr, mytable and cbind.mytable objects.
Utilities for simplifying common statistical operations including
 probability density functions, cumulative distribution functions, 
 Kolmogorov-Smirnov tests, principal component analysis plots, and prediction plots.
Functions for obtaining the density, random variates
             and maximum likelihood estimates of the Zero-truncated Poisson lognormal
             distribution and their mixture distribution.
Read '.xls' and '.sbj' files which are written by the
   Microsoft Windows program 'z-Tree'. The latter is a software for
   developing and carrying out economic experiments
   (see <http://www.ztree.uzh.ch/> for more information).
How fast can you type R functions on your keyboard? Find out by running a 'zty.pe' game: export R functions as instructions to type to destroy opponents vessels.
Stein control variates can be used to improve Monte Carlo estimates of expectations when the derivatives of the log target are available. This package implements a variety of such methods, including zero-variance control variates (ZV-CV, Mira et al. (2013) <doi:10.1007/s11222-012-9344-6>), regularised ZV-CV (South et al., 2023 <doi:10.1214/22-BA1328>), control functionals (CF, Oates et al. (2017) <doi:10.1111/rssb.12185>) and semi-exact control functionals (SECF, South et al., 2022 <doi:10.1093/biomet/asab036>). ZV-CV is a parametric approach that is exact for (low order) polynomial integrands with Gaussian targets. CF is a non-parametric alternative that offers better than the standard Monte Carlo convergence rates. SECF has both a parametric and a non-parametric component and it offers the advantages of both for an additional computational cost. Functions for applying ZV-CV and CF to two estimators for the normalising constant of the posterior distribution in Bayesian statistics are also supplied in this package. The basic requirements for using the package are a set of samples, derivatives and function evaluations.
An efficient implementation of the slope method described by Sen (1968) <doi:10.1080/01621459.1968.10480934> plus implementation of prewhitening approaches to determining trends in climate data described by Zhang, Vincent, Hogg, and Niitsoo (2000) <doi:10.1080/07055900.2000.9649654> and Yue, Pilon, Phinney, and Cavadias (2002) <doi:10.1002/hyp.1095>.
A minor collection of HTTP wrappers for the 'Zamzar File Conversion'
    API. The wrappers makes it easy to utilize the API and thus convert
    between more than 100 different file formats (ranging from audio files,
    images, movie formats, etc., etc.) through an R session.  
    For specifics regarding the API, please see <https://developers.zamzar.com/>.
Functions and datasets for bootstrapping from the
book "Bootstrap Methods and Their Application" by A. C. Davison and
D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S.
Various functions for classification, including k-nearest
neighbour, Learning Vector Quantization and Self-Organizing Maps.
Methods for Cluster analysis.  Much extended the original from
Peter Rousseeuw, Anja Struyf and Mia Hubert,
based on Kaufman and Rousseeuw (1990) "Finding Groups in Data".
Reading and writing data stored by some versions of
'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka',
and for reading and writing some 'dBase' files.
Functions for kernel smoothing (and density estimation)
corresponding to the book:
Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing".
A powerful and elegant high-level data visualization
system inspired by Trellis graphics, with an emphasis on
multivariate data. Lattice is sufficient for typical graphics needs,
and is also flexible enough to handle most nonstandard requirements.
See ?Lattice for an introduction.
Functions and datasets to support Venables and Ripley,
"Modern Applied Statistics with S" (4th edition, 2002).
A rich hierarchy of sparse and dense matrix classes,
including general, symmetric, triangular, and diagonal matrices
with numeric, logical, or pattern entries.  Efficient methods for
operating on such matrices, often wrapping the 'BLAS', 'LAPACK',
and 'SuiteSparse' libraries.
Generalized additive (mixed) models, some of their extensions and
other generalized ridge regression with multiple smoothing
parameter estimation by (Restricted) Marginal Likelihood,
Cross Validation and similar, or using iterated nested Laplace
approximation for fully Bayesian inference. See Wood (2025)
<doi:10.1146/annurev-statistics-112723-034249> for an overview.
Includes a gam() function, a wide variety of smoothers, 'JAGS'
support and distributions beyond the exponential family.
Software for feed-forward neural networks with a single
hidden layer, and for multinomial log-linear models.
Recursive partitioning for classification,
regression and survival trees.  An implementation of most of the
functionality of the 1984 book by Breiman, Friedman, Olshen and Stone.
Contains the core survival analysis routines, including
definition of Surv objects,
Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models,
and parametric accelerated failure time models.
Please send questions and comments regarding pbdR to
RBigData@gmail.com
Please send questions and comments to wccsnow@gmail.com
Please send questions and comments about Rcpp to
rcpp-devel@lists.r-forge.r-project.org
Please send questions and comments regarding RInside to
rcpp-devel@lists.r-forge.r-project.org
Dane R. Van Domelen <vandomed@gmail.com>
Pedro Rafael D. Marinho <pedro.rafael.marinho@gmail.com>
Mark van der Loo <mark.vanderloo@gmail.com>
Lissandro Costa de Sousa <lisandrosousa54@gmail.com>
Renata T C Yokota <renatayokota@gmail.com>
Pedro Rafael Diniz Marinho <pedro.rafael.marinho@gmail.com>
Marcelino De la Cruz <marcelino.delacruz@urjc.es>
Carlos J. Gil Bellosta <cgb@datanalytics.com>
Paul Angelo C. Manlapaz <pacmanlapaz@gmail.com>
Cesar de Oliveira Ferreira Silva <cesaroliveira.f.silva@gmail.com>
Joaquin Alejandro Salinas Angeles <joaquinsa03@gmail.com>
Rodrigo Yudi Palhaci Marubayashi <marubayashi@uel.br>
Jose Roberto Ayala Solares <ichbinjras@gmail.com>
Miguel Angelo Lellis Moreira <miguellellis@hotmail.com>
Mohamed El Fodil Ihaddaden <ihaddaden.fodeil@gmail.com>
Almut E. D. Veraart <a.veraart@imperial.ac.uk>
Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>
Luis D. Verde Arregoitia <luis@liomys.mx>
Débora C. O. Gonçalves <debora_cog@outlook.com>
Rafael H. M. Pereira <rafa.pereira.br@gmail.com>
Robin K. S. Hankin <hankin.robin@gmail.com>
Gabriel F. R. Vasconcelos <gabrielrvsc@yahoo.com.br>
Pierre Lafaye de Micheaux <lafaye@unsw.edu.au>
Paul E. Santos Andrade <paulefrens@gmail.com>
Caspar J van Lissa <c.j.vanlissa@tilburguniversity.edu>
José Mauricio Gómez Julián <isadore.nabi@pm.me>
Edwin Javier Castillo Carreño <edjcastilloca@unal.edu.co>
Jackie Siaw Tze Wong <jw19203@essex.ac.uk>
Luiz F. V. Figueiredo <labmapackage@gmail.com>
Stephanie van der Pas <s.l.vanderpas@amsterdamumc.nl>
Ricardo de Matos Simoes <ricardo_dematossimoes@dfci.harvard.edu>
Ivan Jacob Agaloos Pesigan <r.jeksterslab@gmail.com>
Blondeau Da Silva Stephane <Stephane.Blondeau-Da-Silva@ac-limoges.fr>
Emilio Akira Morones Ishikawa <emiliomorones@gmail.com>
Luiz Antonio de Jesus Rocha <luiz.rocha@unifesp.br>
Anderson Rodrigo da Silva <anderson.agro@hotmail.com>
Ana Belen Nieto Librero <ananieto@usal.es>
Ricardo Puziol de Oliveira <rpuziol.oliveira@gmail.com>
Rafael de Andrade Moral <rafael.deandrademoral@mu.ie>
Dr J. Peter Amin Marquardt <peter@kmarquardt.de>
David Alejandro Martell Juarez <alex91599@gmail.com>
Jianzhao Gao and Xiaodan Fan <gaojz@nankai.edu.cn>
João Paulo dos Santos Pereira Barbosa <joao.31582129@gmail.com>
Rahim Alhamzawi  (University of Al-Qadisiyah) <rahim.alhamzawi@qu.edu.iq>
Juan Emilio Martinez Manjon <juanemartinez999@hotmail.com>
José Carlos Soage González <jsoage@uvigo.es>
Rodrigo M. R. de Medeiros <rodrigo.matheus@ufrn.br>
Dr. S. Vishnu Shankar <S.vishnushankar55@gmail.com>
Francisco H. C. de Alencar <hildemardealencar@gmail.com>
Ari Purwanto Sarwo Prasojo <ari.prasojo18@gmail.com>
Kwadwo Daddy Nyame Owusu Boakye <kwadwo.owusuboakye@outlook.com>
Ivo Van Walle Developer <ivo.van.walle@gmail.com>
Jorge L. C. Musaja <musajajorge@gmail.com>
Ahmad Hakeem Abdul Wahab <hakeemwahab00@gmail.com>
Claucio Antonio Rank Filho <claucio.filho@hitechnologies.com.br>
Luis Alfonso Perez Martos <lapm0001@gmail.com>
G. C. Livingston Jr <Glen.LivingstonJr@newcastle.edu.au>
L. A. van der Ark <L.A.vanderArk@uva.nl>
Geert Roelof van der Ploeg <g.r.ploeg@uva.nl>
Jorge Ubirajara Pedreira Junior <jorge.ubirajara@ufba.br>
Francesca Marta Lilja Di Lascio <marta.dilascio@unibz.it>
M. A. J. Zondervan-Zwijnenburg <m.zondervan@vilans.nl>
Joyce Moonen - van Loon <j.moonen@maastrichtuniversity.nl>
K. Gerald van den Boogaart <support@boogaart.de>
José Manuel Monroy Kuhn <nolozz@gmail.com>
José Mauricio Gómez Julián <isadorenabi@pm.me>
Wim Van der Elst <Wim.vanderelst@gmail.com>
Erick G.G. de Paz <giles.erick@colpos.mx>
Falco Joannes Bargagli Stoffi <fbargaglistoffi@hsph.harvard.edu>
Raul de Paula Pires <rauldepaulapires@gmail.com>
Nelson Alirio Cruz Gutierrez <nelson-alirio.cruz@uib.es>
Jonas M. B. Haslbeck <jonas.haslbeck@gmail.com>
James A. Fellows Yates <jfy133@gmail.com>
Raoul P. P. P. Grasman <rgrasman@uva.nl>
J. Antonio Guzmán Q. <antguz06@gmail.com>
Wagner Martins dos Santos <wagnnerms97@gmail.com>
Professor Dr. Mohammad Shahidul Islam <shahed.stat@gmail.com>
Mathew William Armitage Fok <quiksilver67213@yahoo.com>
Pedro Abraham Montoya Calzada <pedroabraham.montoya@gmail.com>
Victor Manuel Almaraz Valle <almarazkrae@gmail.com>
Carl A. B. Pearson <carl.pearson@lshtm.ac.uk>
Eduardo L. T. Conceicao <mail@eduardoconceicao.org>
Kevin Allan Sales Rodrigues <kevin.asr@outlook.com>
Ricardo Daniel Marques Salgado <ricardodansalgado@gmail.com>
Jonas Gregorio de Souza <jonas.gregorio@gmail.com>
Alec James van Rassel <alec.van-rassel.1@ulaval.ca>
Sean A. S. Anderson <sean.as.anderson@gmail.com>
Marcelino de la Cruz Rot <marcelino.delacruz@urjc.es>
Emilio L. Sáenz Guillén <Emilio.Saenz-Guillen@citystgeorges.ac.uk>
Pedro H. C. Sant'Anna <pedrohcgs@gmail.com>
Md. Mahadi Hassan Nayem <mhnayem.cu.stat@outlook.com>
Don van den Bergh <donvdbergh@hotmail.com>
Roberto de la Banda <dualScale@gmail.com>
Kaique dos S. Alves <kaiquedsalves@gmail.com>
Hector Roux de Bezieux <hector.rouxdebezieux@berkeley.edu>
Sidney da Silva Pereira Bissoli <sbissoli76@gmail.com>
Dr. Ranjit Kumar Paul <ranjitstat@gmail.com>
Silvia María Franco Anaya <sfrana@unileon.es>
Ardo van den Hout <Ardo.vandenHout@ucl.ac.uk>
Matheus H. J. Saldanha <mhjsaldanha@gmail.com>
Jalmar M. F. Carrasco <carrasco.jalmar@ufba.br>
Willyan Junior Adorian Bandeira <bandeira.wjab@gmail.com>
Justin A. G. Hubbard <justin.hubbard@mail.utoronto.ca>
Hendrik van der Wurp <vanderwurp@statistik.tu-dortmund.de>
Jesús María Méndez Pérez <jesus.mendez@ticarum.es>
Manuel Oviedo de la Fuente <manuel.oviedo@udc.es>
Diego Andrés Pérez Ruiz <diego.perezruiz@manchester.ac.uk>
Caíque de Oliveira de Souza <forestgrowthsoftware@gmail.com>
Clayton Vieira Fraga Filho <forestgrowthsoftware@gmail.com>
Borja Latorre (Core Team) <borja.latorre@csic.es>
Alberson da Silva Miranda <albersonmiranda@hotmail.com>
Nina M. D. Schiettekatte <nina.schiettekatte@gmail.com>
Agnese Maria Di Brisco <agnese.dibrisco@unimib.it>
A. J. Muñoz-Pajares Developer <ajesusmp@ugr.es>
Joao Everthon da Silva Ribeiro <everthonribeiro10@gmail.com>
"Vincent ten Cate, PhD" <vincent10kd@gmail.com>
Carlos Henrique Trigo Nasser Felix <c214344@dac.unicamp.br>
Venkata Siva Reddy Naga <venkatasivareddy003@gmail.com>
Emilio L. Sáenz Guillén
<Emilio.Saenz-Guillen@citystgeorges.ac.uk>
Helgem de Souza Ribeiro Martins <helgem.souza@gmail.com>
S M Mashrur Arafin Ayon <mashrur399@gmail.com>
Shaiful Anuar Abu Bakar <saab@um.edu.my>
Niels van der Velden <n.s.j.vandervelden@gmail.com>
Juan Pablo Ruiz Nicolini <juanpabloruiznicolini@gmail.com>
Paulo Justiniano Ribeiro Jr <paulojus@ufpr.br>
Javier De La Hoz Maestre <jdelahozmaestre@gmail.com>
Teun van den Brand <tahvdbrand@gmail.com>
Andy Man Yeung Tai <andy.tai@stat.ubc.ca>
Vincent T van Hees <v.vanhees@accelting.com>
Xavier Fernández i Marín <xavier.fim@gmail.com>
Caspar J. van Lissa <c.j.vanlissa@tilburguniversity.edu>
Othman S. I. Mohammed <admin@leopard.ly>
Joseph Emile Honour Percival <ipercival@gmail.com>
Anders Gonçalves da Silva <andersgs@gmail.com>
Gualberto Segundo Agamez Montalvo <gsagamez@dema.ufc.br>
Per August Jarval Moen <pamoen@math.uio.no>
Oscar Alejandro Sialer Gallo <alejandro.sialer.gallo@gmail.com>
Bastos Fernando de Souza <fernando.bastos@ufv.br>
Andre Luis Fernandes dos Santos <andrvet@alumni.usp.br>
Antonio Pedro Duarte Silva <psilva@ucp.pt>
Martijn van de Pol <martijn@myscience.eu>
Rafael de Andrade Moral <rafael_moral@yahoo.com.br>
Jose Mauricio Gomez Julian <isadorenabi@pm.me>
"Stefan Rass, on behalf of the Austrian Institute of Technology" <stefan.rass@jku.at>
Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>
Sai Thein Than Tun <theinthantun.sai@gmail.com>
Marcelino de la Cruz <marcelino.delacruz@urjc.es>
Muditha L. Bodawatte Gedara <muditha.lakmali.1993@gmail.com>
Luiz Eduardo S. Gomes <gomes.leduardo@gmail.com>
Eufrasio de A. Lima Neto <eufrasio@de.ufpb.br>
Luã Braga de Oliveira <luabragadeoliveira@gmail.com>
Luiz Henrique Keng Queiroz Junior <keng@ufg.br>
Paul Efren Santos Andrade <paulefrens@gmail.com>
Tri Ha Minh Nguyen <tringuyen_2023@depauw.edu>
Kleber Morais de Sousa <kleberfinancas@gmail.com>
Braylin Alexander Jiménez Reynoso <braylinjr1511@gmail.com>
Yves Ismael Ngounou Bakam <yvesngounou20@gmail.com>
Silvaneo dos Santos Jr. <silvaneojunior@utexas.edu>
John R. J. Thompson <john.thompson@ubc.ca>
Weverton C. F. Trindade <wevertonf1993@gmail.com>
Maria del Mar Quiroga <mar.quiroga@unimelb.edu.au>
Thiago de Paula Oliveira <thiago.paula.oliveira@alumni.usp.br>
Carlos Javier Hellin Asensio <carlos.hellin@uah.es>
João Paulo dos Santos Vieira-Alencar <joaopaulo.valencar@gmail.com>
Carlos Abimael Sarmiento Sanchez <cass9918@hotmail.com>
Víctor Manuel Almaraz Valle <almarazkrae@gmail.com>
Rosineide Fernando da Paz <rfpaz2@gmail.com>
"Antoine Tremblay, Statistics Canada" <trea26@gmail.com>
Rune Haubo Bojesen Christensen <Rune.Haubo@gmail.com>
Vito M. R. Muggeo <vito.muggeo@unipa.it>
Sergio Andrés Cabrera Miranda <sergio05acm@gmail.com>
Mauricio van den Berg <mauricio.vandenberg@thekids.org.au>
Lauren L. Hulsman Hanna <Lauren.Hanna@ndsu.edu>
Fernando Ferraz do Nascimento <fernandofn@ufpi.edu.br>
Caspar J. Van Lissa <c.j.vanlissa@gmail.com>
João Victor Gomes de Araujo Santana <jvg.santana@gmail.com>
Stephen L R Ellison <s.ellison@lgcgroup.com>
Héctor Manuel Sánchez Castellanos <sanchez.hmsc@berkeley.edu>
Bruno André Rodrigues coelho <bruno@brodrigues.co>
A. Jonathan R. Godfrey <a.j.godfrey@massey.ac.nz>
Bert van der Veen <bert_van_der_veen@hotmail.com>
Ludwig Kian Soon Hoon <ldwgkshoon@gmail.com>
Noah William Trelawny Hellen <noahhellen@gmail.com>
Krishna Harsha K H <khkrishnaharsha123@gmail.com>
L. Andries van der Ark <L.A.vanderArk@uva.nl>
Olivier Percie du Sert <olivier.perciedusert@mail.mcgill.ca>
Salvador Jesús Fernández Bejarano <salvador.fernandez@vliz.be>
Jose Luis Vicente Villardon <villardon@usal.es>
Chak Kwong (Tommy) Cheng <ccheng46@uic.edu>
Mark A. van de Wiel <mark.vdwiel@amsterdamumc.nl>
Hannah De los Santos <hdelossantos653@gmail.com>
Sebastian J. Teran Hidalgo <sebastianteranhidalgo@gmail.com>
Eliot J B McIntire <eliot.mcintire@canada.ca>
Don van den Bergh <d.vandenbergh@uva.nl>
Juan A. Arias Lopez <iguanamarina@protonmail.com>
Nelson de O. Quesado Filho <nquesado@gmail.com>
Maria Jose Ginzo Villamayor <mariajose.ginzo@usc.es>
Pedro Augusto Borges Santos <pabsantos21@gmail.com>
João Pedro Melani Saraiva <jpsaraiva2002@gmail.com>
Carlos de la Calle-Arroyo <carlos.calle.arroyo@gmail.com>
Pedro Nascimento de Lima <plima@rand.org>
Rune Haubo Bojesen Christensen <rune.haubo@gmail.com>
Matthias Braun FKA Nistler <m_nistler@web.de>
Joao Pedro Oliveira dos Santos <joaopsantos@pm.me>
Bruno do Rosario Petrucci <petrucci@iastate.edu>
F. Marta L. Di Lascio <marta.dilascio@unibz.it>
"Australian e-Health Research Centre, CSIRO" <pathling@csiro.au>
Gabriel Henrique de Oliveira Caetano <gabrielhoc@gmail.com>
Juan Pablo Vargas Perez <j.pablovargas340@gmail.com>
Luna Luisa Sanchez Reyes <sanchez.reyes.luna@gmail.com>
Wouter van der Bijl <wouter@zoology.ubc.ca>
Rodrigo Augusto Santinelo Pereira <raspereira@usp.br>
Joaquin Bienvenido Ordieres Mere <j.ordieres@upm.es>
Dr. Himadri Shekhar Roy <himadriiasri@gmail.com>
Marieke van der Maaten-Theunissen <marieke.theunissen@tu-dresden.de>
Wessel N. van Wieringen <w.vanwieringen@vumc.nl>
Iago Augusto de Carvalho <iago.carvalho@unifal-mg.edu.br>
Paul van der Laken <paulvanderlaken@gmail.com>
Mijael Rodrigo Vargas Godoy <mirovago@gmail.com>
Thaís de Bessa Gontijo de Oliveira <thais.bgo@gmail.com>
Juan Carlos Gonçalves Dosantos <juan.carlos.goncalves@udc.es>
Blondeau Da Silva Stephane <blondeaudasilva@xlim.fr>
Robbie C.M. van Aert <R.C.M.vanAert@tilburguniversity.edu>
Carlos J. Gil Bellosta <gilbellosta@gmail.com>
Jose Sergio Case de Oliveira <js_cdo@hotmail.com>
Peter J. van der Most <p.j.van.der.most@umcg.nl>
Wagner Santos de Lima <wagnersantos.ufs@hotmail.com>
Juan Pablo Acuña González <22253567@uagro.mx>
USMR CHU de Bordeaux <astreinte.usmr@chu-bordeaux.fr>
Achmad Fauzi Bagus F <fauzi.pandya@gmail.com>
Manuel A. Mosquera Rodríguez <mamrguez@uvigo.es>
Katherine A. L. Valeriano <katandreina@gmail.com>
Jarrod van der Wal <jarvanderwal@gmail.com>
Santos Henrique Brant Dias <santoshbdias@gmail.com>
Christian Alexander Mongeau Ospina <christian+rpkg-repec@mongeau.net>
"Michael Barr, ACAS, MAAA, CPCU" <mike@bikeactuary.com>
Peter van den Berg <peter_v_d_berg@hotmail.com>
Christopher R P Brown <c.r.brown@uq.edu.au>
Jonnathan Augusto Landi Bermeo <jonnathan.landi@outlook.com>
Sander H. van Delden <plantmind@proton.me>
Jose Miguel Cotes Torres <jmcotes@unal.edu.co>
Lucas Sebastião de Paula <lucas@ime.eb.br>
Zainab Subhi Mahmood Hawrami <zaianbsubhi@gmail.com>
Dennis Alexis Valin Dittrich <davd@economicscience.net>
Maria del Carmen Calatrava Moreno
<mc.calatrava.moreno@gmail.com>
Sergio Daniel Frutos Galarza <sergio_dan88@hotmail.com>
Md Riaz Ahmed Khan <mdriazahmed.khan@jacks.sdstate.edu>
Unai Pérez - Goya <unai.perez@unavarra.es>
Mohammad Hadi Foroughmand Araabi <foroughmand@gmail.com>
Arthur Igor da Fonseca-Freire <arthur.igorr@gmail.com>
Ridson Al Farizal P <ridsonalfarizal15@gmail.com>
Mr. Ankit Kumar Singh <ankitsinghvns32@gmail.com>
Juan Luis Herrera Cortijo <juan.luis.herrera.cortijo@gmail.com>
Anh Phan Truong Quynh <anhptq@oucru.org>
Lucas van der Meer <luukvandermeer@live.nl>
M. Yoga Satria Utama <221709801@stis.ac.id>
Niels J. de Winter <niels.de.winter@vub.be>
Simon E. H. Smart <simon.smart@cantab.net>
Jose Mauricio Gomez Julian <isadore.nabi@pm.me>
Douglas Kiarelly Godoy de Araujo <dkg.araujo@gmail.com>
Ivonaldo S. da Silva-Júnior <ivosilvestresjr@gmail.com>
Julia de Paula Soares Valente <juliadepaulasoaresvalente@gmail.com>
Jose Manuel Vera Oteo <vera.josemanuel@gmail.com>
Martha Patricia Bohorquez Castañeda <mpbohorquezc@unal.edu.co>
Sy Han (Steven) Chiou <schiou@utdallas.edu>
Dr. Owais Ali Wani <owaisaliwani@skuastkashmir.ac.in>
Fernando de Souza Bastos <fernando.bastos@ufv.br>
Stephen A Sefick Jr. <ssefick@gmail.com>
Wim Van Der Elst <wim.vanderelst@gmail.com>
Cesaire J. K. Fouodo <cesaire.kuetefouodo@uni-luebeck.de>
Vinicius Quintas Souto Maior <vinicius@de.ufpe.br>
Jesús María Rodríguez Rodríguez <jesusmro@gmail.com>
Gabriel Henrique Oliveira Assuncao <gabrielhenryoliver@hotmail.com>
K. Gerald van den Boogaart <boogaart@math.tu-freiberg.de>
Caspar J. Van Lissa <c.j.vanlissa@tilburguniversity.edu>
Clarke JM van Steenderen <vsteenderen@gmail.com>
G H Harish Nayak <harishnayak626@gmail.com>
Silvestre Garcia de Jalon <s.garciadejalon@gmail.com>
Antonio Fabio Di Narzo <antonio.fabio@gmail.com>
Álvaro de Prado Saborido <alvarodepradosaborido@gmail.com>
Henrique Jose de Paula Alves <jpahenrique@gmail.com>
Angel Luis Robles Fernández <a.l.robles.fernandez@gmail.com>
Oscar Alberto Quijano Xacur <oscar.quijano@use.startmail.com>
André F. B. Menezes <andrefelipemaringa@gmail.com>
Taryn B. T. Athey <taryn.athey@gmail.com>
Adriano Zanin Zambom Developer <adriano.zambom@gmail.com>
Andrew J. Sanchez Meador <andrew.sanchezmeador@nau.edu>
Giulio Valentino Dalla Riva <me@gvdallariva.net>
Joerg grosse Schlarmann (aka Produnis) <schlarmann@produnis.de>
Olivier M. F. Martin <oliviermfmartin@tutanota.com>
Tharso Augustus Rossiter Araújo Monteiro <tharso.augustus@ufpe.br>
1. School of Mathematical & Statistical Sciences, Clemson
University, Clemson, South Carolina, USA 2. Department of
Mathematics & Statistics, University of Agriculture Faisalabad,
Faisalabad, Pakistan
Package 'rjags' requires JAGS executabe file (compatiable
version) should be already installed.
The optmatch package, which is useful for running many of the
provided functions, may be downloaded from Github at
<https://github.com/markmfredrickson/optmatch> if not available
on CRAN. The rrelaxiv package, which provides an alternative
solver for the underlying network flow problems, carries an
academic license and is not available on CRAN, but may be
downloaded from Github at
<https://github.com/josherrickson/rrelaxiv/>.
Maintainers are not available to give advice on using a package
they did not author.
1. Asian Development Bank (ADB), Islamabad, Pakistan. 2. Benazir
Income Support Programme (BISP), Islamabad, Pakistan. 3.
Department of Mathematics and Statistics, University of
Agriculture Faisalabad, Faisalabad-Pakistan.
This is the CRAN version of the package.  Due to limitations of
that platform it does not support the changepoint analysis of
the spacing.  The full definitive version of the package is
available at
https://www.primachvis.com/data/Dimodal_latest.tar.gz
One minimum cost flow problem may have several or many solutions
that are equivalent in providing the same minimum total or mean
cost. Minor differences between computers or implementations
may have the minor consequence of altering which equivalent
solution is produced. The optmatch package, which is useful for
running many of the provided functions, may be downloaded from
Github at <https://github.com/markmfredrickson/optmatch> if not
available on CRAN. The rrelaxiv package, which provides an
alternative solver for the underlying network flow problems,
carries an academic license and is not available on CRAN, but
may be downloaded from Github at
<https://github.com/josherrickson/rrelaxiv/>.
This publication was prepared for NCES under Contract No.
ED-IES-12-D-0002/0004 with the American Institutes for
Research. Mention of trade names, commercial products, or
organizations does not imply endorsement by the U.S.
Government.
School of Mathematical and Statistical Sciences, Clemson
University, Clemson, South Carolina, USA.
Ver. 1.0: The author obtained financial resources as part of
financing the doctoral scholarship from the Polish National
Science Centre (DEC-2018/28/T/HS4/00095). Ver. 2.0: The
research was supported by the program ''Excellence Initiative -
Research University (IDUB)'' through the project
BOB-IDUB-622-89/2021 - Nowe Idee POB III IDUB, 01/IDUB/2019/94
at the University of Warsaw, Poland.
1. Asian Development Bank (ADB), Islamabad, Pakistan. 2. Benazir
Income Support Programme (BISP), Islamabad, Pakistan. 3.
Department of Mathematics and Statistics, University of
Agriculture Faisalabad, Pakistan.
Package includes self-contained 'llama.cpp' implementation
(~56MB) for complete functionality without external
dependencies.
This publication was prepared for NCES under Contract No.
ED-IES-12-D-0002 with the American Institutes for Research.
Mention of trade names, commercial products, or organizations
does not imply endorsement by the U.S. Government.
This update fixes bugs noted because of global variables not
being recognised as global variables in some environments.
This update was performed to align with a planned ggplot2 update
Research funded by the Polish National Science Centre grant under
the contract number DEC-2015/19/N/HS4/00205.
Few parts are still preliminary and might be changed in the near
future. And more functions will be add as easier tools to
higher efficiency in analyzing.
While reporting issues on github start subject line with
[cran-package]
The authors are grateful to Mikhail Kanevski, Federico Amato and
Luciano Telesca for many fruitful discussions about the use and
the application of Fisher-Shannon method.
This software comes with NO warranty! It is NOT intended to be
used in clinical applications! For evaluation only!
research product of the RISCOPE project (ANR, project
No.16CE04-0011) <https://perso.math.univ-toulouse.fr/riscope/>.
Development followed an iterative human-machine collaboration
where all algorithmic design, statistical methodologies, and
biological validation logic were conceptualized, tested, and
iteratively refined by Richard A. Feiss through repeated cycles
of running experimental data, evaluating analytical outputs,
and selecting among candidate algorithms and approaches. AI
systems ('Anthropic Claude' and 'OpenAI GPT') served as coding
assistants and analytical sounding boards under continuous
human direction. The selection of statistical methods,
evaluation of biological plausibility, and all final
methodology decisions were made by the human author. AI systems
did not independently originate algorithms, statistical
approaches, or scientific methodologies.
Department of Genetics and Plant Breeding, University of
Agricultural Sciecnes, Dharwad.
Package 'R2jags' requires JAGS executable file installed
The authors are grateful to Mikhail Kanevski, Michael
Leuenberger, Carmen D. Vega Orozco and Fabian Guignard for many
fruitful discussions about the use of intrinsic dimension in
data mining.
Because IPEDS requirements may change from year to year, having
the most recent version of this package is highly recommended.
Old versions can be found as GitHub branches. The package can
also be used to convert any correctly-prepared data into a
key-value pair format for any survey (IPEDS or non-IPEDS).
This package includes code from https://github.com/kudelalab/PSD
by kudelalab licensed under the MIT License.
Please, cite this package as: Marina Saez (2021). KarsTS: An
Interface For Microclimate Time Series Analysis. R package
version 2.4.1.
Includes modified Python code from the RSRM project
(<https://github.com/intell-sci-comput/RSRM>) under the MIT
License.
Department of Statistics, Bahauddin Zakariya University, Multan,
Pakistan.
Department of Statistics, Bahauddin Zakariya University, Multan,
Pakistan
The originale code was in matlab, see details below.
The developer version of 'keras' should be used, rather than the
CRAN version. The latter will cause tests to fail on an initial
run, but work on subsequent tries. To avoid this, use
devtools::install_github("rstudio/keras"). The user also must
have an installation of 'Python 3'.
The current version of this library (main version number: 4) has
been partly supported by eSSENCE, a national strategic research
program in e-Science. A previous version of the library (main
version number: 3) was developed as part of the European
Union's Horizon 2020 research and innovation programme under
grant agreement No. 727040 (Virt-EU). The package uses
functions from Howard Hinnant's date and time library
<https://github.com/HowardHinnant/date> and Boost; the code
from these libraries has been included in our source package.
For convenience, the package includes the necessary header files
for the Eigen distribution. (This is all that is needed to use
that functionality.) You can use an alternative installation of
Eigen on your system or the one we provide. The license for the
Eigen code is very permissive and allows us to distribute it
with this package. See <http://eigen.tuxfamily.org/index.php?
title=Main_Page> and also the License section on that page.
The APT samplers within this package were adapted from MCMC
samplers provided in the NIMBLE package
(https://github.com/nimble-dev/nimble) and developed by the
cited members of the NIMBLE Development Team. The adaptations
for APT included in this package were the work of the package
developer. Many thanks to the NIMBLE Development Team for their
support during the development of this package.
Department of Mathematics and Statistics, University of
Agriculture Faisalabad, Faisalabad-Pakistan.
Research funded by the grant of the National Science Centre,
Poland, under the contract number DEC-2018/31/B/HS4/02021.
The package 'MSnbase' is used for parsing and processing mzTab
files. While its non-portability limits usage on some
platforms, it is essential for enabling analysis and
integration of mzTab data in 'PepMapViz'. However, if the input
file is not in mzTab format, 'MSnbase' is not required, and the
package can function without it.
This package makes use of the 'pikchr' source code created by
Richard Hipp (<https://pikchr.org>).
Building the package requires R >= 4.6.0 for \bibshow{} et al.
conceptual foundation and significant code structure inherited
from the 'prioritylasso' package.
This package makes use of the 'RapidFuzz' source code (v3.3.3)
created by Max Bachmann and Adam Cohen
(<https://github.com/rapidfuzz/rapidfuzz-cpp>).
Package is in active development; please report errors and
suggestions to rchlumsk@uwaterloo.ca.
NOTICE regarding the transfer of data from Retrosheet: The
information used here was obtained free of charge from and is
copyrighted by Retrosheet. Interested parties may contact
Retrosheet at "www.retrosheet.org".
When loading, both MuMIn and rstatix are imported. Since rstatix
internally depends on broom, this may trigger a warning about
S3 method overwrites, specifically for nobs.fitdistr and
nobs.multinom. These warnings are harmless and do not affect
functionality.
See http://www.json.org/JSON_checker/test.zip for tests. We now
use code from the libjson project
(http://libjson.sourceforge.net).
Free to use for non-Norwegian institutions, otherwise see
LICENSE.
The development of this package was supported by Carlos
Jaramillo, Center for Tropical Paleoecology and Archaeology at
Smithsonian Tropical Research Institute.
This publication was prepared for NCES under Contract No.
ED-IES-12-D-0009/0005 with Sanametrix and Westat. Mention of
trade names, commercial products, or organizations does not
imply endorsement by the U.S. Government.
The GPU computing version can be found soon, on following url
https://sites.google.com/site/mohamedlaibwebpage/Software.
This package is developed as part of ongoing Ph.D. (Agricultural
Statistics) thesis research work of first author at ICAR-Indian
Agricultural Statistics Research Institute, New Delhi, India.
This package is developed as part of ongoing Ph.D (Agricultural
Statistics) thesis research work of first author at ICAR-Indian
Agricultural Statistics Research Institute, New Delhi, India.
1. School of Mathematical & Statistical Sciences, Clemson
University, Clemson, South Carolina, USA 2. Department of
Mathematics and Statistics, University of Agriculture
Faisalabad, Faisalabad, Pakistan
School of Mathematical & Statistical Sciences, Clemson
University, Clemson, South Carolina, USA
The author acknowledges financial support from Sao Paulo Research
Foundation (FAPESP) grant 2016/18599-4
This is experimental software distributed free of charge and
comes with no warranty!  Exercise professional caution.
Package TSE works directly from the data set – no hand
calculations required.  Just upload a properly structured data
set (see TESTNUMB and its documentation), properly input column
names (see examples in the functions documentation), and run
your functions.
'TSEind' is a companion package to 'TSE'. Both calculate TSE for
your surveys, but use 'TSEind' if your surveys and the "gold
standard" survey have independent samples, and use 'TSE' if
your surveys and the "gold standard" survey have paired
samples.
'TSEwgt' is a companion package to 'TSE'. Each package calculates
TSE, but the former for multiple, different surveys, and the
latter for a single survey under multiple, different weighting
schemes.
Note: The included dataset is licensed under "DL-DE-BY-2.0." See
the dataset documentation for details.
School of Mathematical and Statistical Sciences, Clemson
University, Clemson, South Carolina, USA. Department of
Mathematics and Statistics, University of Agriculture
Faisalabad, Faisalabad-Pakistan.
This publication was prepared for NCES under Contract No.
ED-IES-12-D-0002 with American Institutes for Research. Mention
of trade names, commercial products, or organizations does not
imply endorsement by the U.S. government.
2022-11-15 06:15:38 UTC; Kosuke Kashiwabara
2026-05-11 14:44:03 UTC; Lennart Oelschläger
2026-03-06 03:54:00 UTC; Nino Jay Talingting
2025-04-29 16:29:10 UTC; Javaria Ahamd Khan
2025-09-19 16:04:18 UTC; George Karabatsos
2020-09-22 06:18:07 UTC; Benjamin Schlegel
2025-10-06 08:08:22 UTC; Lennart Oelschläger
2023-01-18 00:21:38 UTC; Sidharth Macherla
2024-09-08 09:19:25 UTC; Pavlos Pantatosakis
2023-05-17 21:39:10 UTC; Andreas Kuehnapfel
2021-11-28 13:38:57 UTC; Javaria Ahamd Khan
2022-09-20 14:28:28 UTC; Javaria Ahamd Khan
2025-09-11 18:35:59 UTC; Sebastian Weirich
2026-02-18 15:08:27 UTC; Kittisakdi Choomalee
2020-07-14 07:43:10 UTC; Bernardo Sousa Pinto
2026-05-05 12:39:25 UTC; Lennart Oelschläger
2024-06-17 04:42:11 UTC; Carlos Perez Carmona
2026-01-08 09:50:35 UTC; Friedemann von Lampe
2023-06-11 18:14:04 UTC; Jonas Christoffer
2026-01-28 21:35:50 UTC; Eleanor Pullenayegum
2026-05-16 15:45:22 UTC; Masayoshi Takahashi
2020-01-08 09:11:00 UTC; Nadezda Spiridovska
2021-04-16 08:59:10 UTC; Ilias Moutsopoulos
2025-06-10 17:17:10 UTC; Lennart Oelschläger
2026-02-03 07:48:07 UTC; BPS Prov Jawa Timur
2026-05-07 15:40:47 UTC; Lennart Oelschläger
2026-04-23 04:52:59 UTC; Nino Jay Talingting
2021-07-12 03:13:21 UTC; Guillaume Boucher
2025-06-10 16:29:13 UTC; Lennart Oelschläger
2018-04-29 13:45:20 UTC; Alberto Vico Moreno
2026-02-05 23:33:21 UTC; Christian Million
2020-05-07 11:07:40 UTC; Kanhaiiya Agrawal
2026-04-09 17:16:41 UTC; Nino Jay Talingting
2020-06-08 13:17:19 UTC; Kanhaiiya Agrawal
2025-08-25 17:51:29 UTC; Lennart Oelschläger
2026-02-20 08:14:35 UTC; BPS Prov Jawa Timur
2019-08-02 17:03:10 UTC; Bernardo Sousa Pinto
2017-08-15 05:32:43 UTC; Aurnov Chattopadhyay
2024-03-27 21:47:34 UTC; Atanu Bhattacharjee
2026-05-12 15:52:33 UTC; Lennart Oelschläger
2022-01-08 14:42:05 UTC; Sandeep Patakamuri
2026-03-02 20:31:13 UTC; Eric Bruce Jamieson
2026-05-07 15:43:18 UTC; Lennart Oelschläger
kubectl (optional, for Kubernetes backend), SLURM
(optional, sbatch/scontrol/sacct/squeue for SLURM backend),
Posit Workbench (optional, for Workbench backend)
pkg-config, cmake, gsl, jpeg, gdal, geos, proj,
udunits-2, openssl, libcurl, jags
OfficeToPDF -
https://github.com/cognidox/OfficeToPDF, pandoc (>= 1.14) -
https://pandoc.org
Image Magick (for reading non PPM format), dcraw
(for reading RAW images).
ADMIXTOOLS suite of command-line utilities for
population genetics. See
<https://github.com/dreichlab/admixtools> for the most recent
installation instructions and further information.
Alfresco Content Repository (Community or
Enterprise)
Python (>= 3.6.0), (Python) Altair (>= 4.2.0),
vega_datasets (>= 0.9.0). To use image functions for MacOS: X11
ImageMagick (http://imagemagick.org) or
GraphicsMagick (http://www.graphicsmagick.org) or LyX
(http://www.lyx.org) for saveGIF(); (PDF)LaTeX for saveLatex();
SWF Tools (http://swftools.org) for saveSWF(); FFmpeg
(http://ffmpeg.org) or avconv (https://libav.org/avconv.html)
for saveVideo()
Rendering the vignette requires pandoc
(<https://pandoc.org/>).
Rendering the document template requires pandoc (>=
2.0; https://pandoc.org) and for PDFs a TeX distribution, such
as TinyTeX (>= 0.12; https://yihui.org/tinytex/)
Cargo (Rust's package manager), rustc >= 1.67, xz
Cargo (Rust's package manager), rustc, OpenSSL
libarchive: libarchive-dev (deb), libarchive-devel
(rpm), libarchive (homebrew), libarchive_dev (csw)
Cargo (Rust's package manager), rustc >= 1.70
C++20; for AWS S3 support on Linux, libcurl and
openssl (optional); cmake >= 3.26 (build-time only, and only
for full source build)
Cargo (Rust's package manager), rustc (>= 1.78.0)
'automerge-c', or Cargo (Rust's package manager),
rustc >= 1.85 and CMake >= 3.25 to build from package sources.
Quarto command line tools
(https://github.com/quarto-dev/quarto-cli).
Python (>= 3.8); TensorFlow (>= 2.10); Keras;
TensorFlow Addons
FFmpeg (>= 3.2); with at least libx264 and lame
(mp3) drivers. MacOS Homebrew: ffmpeg. Debian/Ubuntu:
libavfilter-dev. Fedora/RHEL: either ffmpeg-devel from
https://rpmfusion.org (preferred), or libavfilter-free-devel
which is a more limited version available on Fedora/EPEL9.
C++17, GNU make, FFmpeg (>= 4.4) with
libavcodec/libavformat, libvulkan-dev (optional, for GPU
encoding on Linux), Vulkan SDK (optional, for GPU encoding on
Windows)
AWS Java SDK (see README.md for more details)
Cargo (Rust's package manager), rustc >= 1.65.0, xz
Cargo (Rust's package manager), rustc, xz
JAGS (>= 4.3.0) (see
http://mcmc-jags.sourceforge.net)
GDAL (>= 2.2.3): gdal-bin (deb), libgdal-dev (deb)
or gdal-devel (rmp), GEOS (>= 3.4.0), PROJ (>= 4.9.3):
libproj-dev (deb), sqlite3, ImageMagick++: imagemagick (deb),
libmagic-dev (deb), libmagick++-dev (deb) or
ImageMagick-c++-devel (rpm) ImageMagick
(http://imagemagick.org) or GraphicsMagick
(http://www.graphicsmagick.org) or LyX (http://www.lyx.org) for
saveGIF(); (PDF)LaTeX for saveLatex(); SWF Tools
(http://swftools.org) for saveSWF(); FFmpeg (http://ffmpeg.org)
or avconv (https://libav.org/avconv.html) for saveVideo()
Java (>= 21.0), TornadoVM (if you want GPU
optimization)
Microsoft Access driver on Windows for Access
backends; mdbtools on Unix-like systems
Python (>= 3.6), 'BayesInference' python library.
pandoc (>= 1.12.3) for building vignettes
Preferred genomic operations engine: 'BEDTools',
'BEDOPS' and 'Tabix (>= 1.3)'.
Python (>= 3.8); BERTopic and Python packages:
sentence-transformers, umap-learn, hdbscan, scikit-learn
JAGS >=4.3.0 <https://mcmc-jags.sourceforge.io>,
Java JDK >=1.4 <https://www.java.com/en/download/manual.jsp>
GNU make, pandoc (>=1.12.3, needed for vignettes)
C++17, Optional CBLAS (detected at compile time)
grpc/protobuf headers and compilers. For example
libprotobuf-dev libgrpc++-dev protobuf-compiler-grpc (Debian)
or protobuf-devel grpc-devel grpc-plugins (Fedora/RHEL)
Julia (>= 1.7), Bigsimr.jl, Distributions.jl
A few functions from package 'bigsnpr' wrap
existing software such as 'PLINK'
<www.cog-genomics.org/plink2>. Functions are provided to
download these software. Note that these external software
might not work for some operating systems (e.g. 'PLINK' might
not work on Solaris).
'monobit' for reading/writing additional bitmap
font formats.
Hugo (<https://gohugo.io>) and Pandoc
(<https://pandoc.org>)
blosc: blosc-devel (rpm) or libblosc-dev (deb)
pandoc (>= 1.12.3, needed for vignettes)
'Microsoft Visual Code', 'Rtools' on 'Windows',
'gdb' or 'lldb' depending on which OS
Rtools (suitable for the installed R) for Windows,
Xcode for Mac
FFTW (>=3.3.1); possible package: fftw-devel (rpm),
libfftw3-dev (deb) or fftw (brew).
Cargo (Rust's package manager), rustc >= 1.80.0, xz
Python and numpyro are needed for Bayesian
inference computations; python (>= 3.8) with header files and
shared library; numpyro (= v0.12.1;
https://https://num.pyro.ai/en/latest/index.html); arviz (=
v0.15.1; https://https://python.arviz.org/en/stable/)
C17, C++17, GNU make, pkg-config, libvulkan-dev
(Linux) or LunarG 'Vulkan' 'SDK' (Windows, macOS), libglfw3-dev
(Linux) or glfw via Homebrew (macOS), ffmpeg (optional, for
cgv_record_*). Optional configure flags: --with-vulkan /
--without-vulkan, --with-simd for SSE4.1 + PCLMUL fpng.
Google Chrome or other Chromium-based browser.
chromium: chromium (rpm) or chromium-browser (deb)
Julia (>= 1.9), Circuitscape.jl, Omniscape.jl
gsl (with development libraries libgsl-dev)
Python (>= 3.9) with the 'midasverse-citest-api'
package
Cargo (Rust's package manager), rustc (>= 1.70.0),
and GNU Make
pandoc (to create a clinical data review report)
pandoc (for export clin DT to a file - inclusion of
list of interactive plots/objects with knitr)
xclip (https://github.com/astrand/xclip) or xsel
(http://www.vergenet.net/~conrad/software/xsel/) for accessing
the X11 clipboard, or wl-clipboard
(https://github.com/bugaevc/wl-clipboard) for systems using
Wayland.
ZeroMQ (libzmq) >= 4.3.0 (optional; otherwise
bundled)
MOSEK (http://www.mosek.com) and MOSEK License for
use of Rmosek
libcurl: libcurl-devel (rpm) or
libcurl4-openssl-dev (deb).
ImageMagick++: ImageMagick-c++-devel (rpm) or
libmagick++-dev (deb)
awscli: apt install -y awscli (deb), aws-configure:
aws configure (deb)
Requires GDAL >= 3.11 with BLOSC support See
<https://pepijn-devries.github.io/CopernicusMarine/articles/blosc.html>
Python (>= 3.7), copernicusmarine Python library
pdfcrop (part of TexLive) is required to rebuild
the vignettes.
Java (>= 7.0); Stanford CoreNLP
<http://nlp.stanford.edu/ software/corenlp.shtml> (>= 3.5.2)
On Windows, Rtools45 (R 4.5.x) or Rtools44 (R
4.4.x) is recommended so the 'bash' shell tool is available;
minimal installs fall back to a 'cmd' tool. 'git' is required
for the git_status, git_diff, and git_log tools (install Git
for Windows, or 'pacman -Sy git' from an Rtools shell).
libjpeg ( deb: libjpeg-dev, rpm: libjpeg-devel,
brew: libjpeg )
Intel MKL (optional for optimized BLAS/LAPACK
performance)
libcurl (>= 7.73): libcurl-devel (rpm) or
libcurl4-openssl-dev (deb)
pandoc (>= 2.0; https://pandoc.org), git, whoami
none, one or more of JAGS (>= 3.0.0), WinBUGS (>=
1.4), OpenBUGS (>= 3.2.2), Stan
A version of Fortran supporting the LOG_GAMMA
Intrinsic and the ieee_arithmetic module.
Java (>= 7.0): openjdk-11-jdk (deb),
java-11-openjdk.x86_64 (rpm), openjdk@11 (brew)
fontconfig or zlib (only needed for platforms other
than modern OSX and Windows)
OpenMP (optional, for parallel execution)
Julia (>= 1.6), DifferentialEquations.jl,
ModelingToolkit.jl
libpq >= 9.0: libpq-dev (deb) or postgresql-devel
(rpm)
Python (>= 3.8.0); PyTorch (https://pytorch.org/);
NumPy (https://numpy.org/); SciPy (https://scipy.org/); sklearn
(https://scikit-learn.org/stable/);
LibreOffice (<https://www.libreoffice.org/>)
required to extract data from .doc files or perform .pptx
conversion.
OpenMP, CUDA Toolkit (optional, for GPU
acceleration)
C++17, GNU make, OpenSSL (optional, for HTTPS)
Requires the OpenMP library for parallel computing.
If the OpenMP library is not available, the code is executed
sequentially and a warning is printed.
poppler-utils (pdftotext) for PDF text extraction
The package required the jq command line library.
Please check https://stedolan.github.io/jq/download/ for
download instructions.
Python (>= 2.7 or >= 3.5) and elex package
The function render() requires Pandoc
(http://pandoc.org). To use PGP/GnuPG encryption requires gpg.
Pandoc (for DOCX/HTML conversion when using
rmarkdown)
PROJ (>= 6, https://proj.org/download.html), GDAL
(>= 3, https://gdal.org/download.html), NetCDF (>= 4,
https://www.unidata.ucar.edu/software/netcdf/).
JAGS (>= 4.0.0). For installation instructions, see
http://mcmc-jags.sourceforge.net/
ProtoBuf libraries and compiler version 3.3.0 or
later; On Debian/Ubuntu these can be installed as
libprotoc-dev, libprotobuf-dev and protobuf-compiler, while on
Fedora/CentOS protobuf-devel and protobuf-compiler are needed.
Optional 'LibTorch' backend; install via
torch::install_torch().
apt-get-pip: apt-get install -y python3-pip (deb),
python3-pip: python3 -m pip install -U pip (deb), numpy: pip3
install -U numpy (deb), cv2: pip3 install -U opencv-python
(deb), matplotlib: pip3 install -U matplotlib (deb), skimage:
pip3 install -U scikit-image (deb), libarmadillo: apt-get
install -y libarmadillo-dev (deb), libblas: apt-get install -y
libblas-dev (deb), liblapack: apt-get install -y liblapack-dev
(deb), libarpack++2: apt-get install -y libarpack++2-dev (deb),
gfortran: apt-get install -y gfortran (deb)
fftw3 (libfftw3-dev (deb), or fftw-devel (rpm))
Cargo (Rust's package manager), rustc >= 1.84, xz
fluidsynth: fluidsynth-devel (rpm) or
libfluidsynth-dev (deb). On Linux you also need a soundfont
provided by 'fluid-soundfont-gm' (Fedora) or 'sf3-soundfont-gm'
(Debian/Ubuntu)
CmdStan
(https://mc-stan.org/users/interfaces/cmdstan), pandoc (>=
1.12.3), pandoc-citeproc
Cargo (Rust's package manager), rustc >= 1.77.2
GNU Scientific Library (GSL). Note: users should
have GSL installed.
Cargo (Rust's package manager) >= 1.85, rustc >=
1.85
libuv: libuv-devel (rpm) or libuv1-dev (deb).
Alternatively to build the vendored libuv 'cmake' is required.
GNU make.
(license-free) MATLAB Runtime (MCR) V 9.12, Java
(>=8)
Python (>= 3.8), difflib, fuzzywuzzy ( >=0.15.0 ),
python-Levenshtein ( >=0.12.0 ). Detailed installation
instructions can be found in the README file.
Debian or Ubuntu system with access to Goto Blas,
Intel MKL, Atlas development build as well as a Nvidia GPU with
CUDA support
C++17, GDAL (>= 3.1.0, built against GEOS)
C++17, GNU make, pandoc (>=1.12.3, needed for
vignettes), OpenCL shared library (provided by an SDK such as
AMD/NVIDIA)
Quarto command line tool
(<https://github.com/quarto-dev/quarto-cli>).
libarmadillo: apt-get install -y libarmadillo-dev
(deb)
MongoDB (>= 3.4.0), Python (>= 2.7). Installation
instructions and links can be found in the README file.
libgit2 (>= 1.0): libgit2-devel (rpm) or
libgit2-dev (deb)
Cargo (Rust's package manager), rustc >= 1.70.0
C++17, GNU make, libvulkan-dev, glslc (optional,
for GPU on Linux), 'Vulkan' 'SDK' (optional, for GPU on
Windows)
GNU make, MeCab (libmecab-dev (deb), mecab-devel
(rpm))
libgit2 (>= 1.0) and its dependencies libssh2 and
openssl header and libraries.
pandoc (>= 1.12.3) - http://pandoc.org, tcltk
(optional)
Optional OpenCL support. If available, GPU
acceleration will be used; otherwise, computation runs on CPU.
Java (>= 22.0); wgpu-native >= 0.19.0 (optional,
for GPU acceleration, see
https://github.com/gfx-rs/wgpu-native)
Python (>= 3.6) with header files and shared
library; H2O4GPU (https://github.com/h2oai/h2o4gpu)
V8 engine version 6+ is needed for modern JS and
WASM support. On Debian / Ubuntu install either libv8-dev or
libnode-dev, on Fedora use v8-devel.
Cargo (Rust's package manager), rustc >= 1.75
GNU make, zlib: zlib1g-dev (deb), zlib-devel (rpm)
CPU with AVX/SSE4.2 (optional for better
performance)
Cargo (Rust's package manager), rustc >= 1.56.0
Apache Hadoop >= 2.7.2
(https://hadoop.apache.org/releases.html#Download); Obsolete:
Hadoop core >= 0.19.1 and <= 1.0.3 or CDH3
(https://www.cloudera.com); standard unix tools (e.g., chmod)
LaTeX packages: adjustbox, array, calc, caption,
colortbl, fontspec, graphicx, hhline, hyperref, multirow,
siunitx, tabularx, threeparttable, ulem, wrapfig
Julia (>= 1.0) and Interpretable AI System Image
(>= 1.0.0)
ImageMagick (http://imagemagick.org) or
GraphicsMagick (http://www.graphicsmagick.org)
A C library with the fesetround/fegetround
functions.
libxml2 (optional), glpk (>= 4.57, optional)
fftw3, libtiff, libbz2, libdeflate, libjpeg,
liblzma, libwebp, libzstd, X11, zlib
Impala driver to support a 'DBI'-compatible R
interface
Complete functionality necessitates Amazon Corretto
(win), and default-jre, pandoc, libxml2-dev,
libpoppler-cpp-dev, libmagick++-dev, optipng, libtesseract-dev,
libleptonica-dev, tesseract-ocr-eng (deb)
pandoc (to export an interactive summary table to a
file)
jupyter, jupyter_kernel_test (Python package for
testing)
libjq: jq-devel (rpm) or libjq-dev (deb)
libarmadillo: apt-get install -y libarmadillo-dev
(deb), libblas: apt-get install -y libblas-dev (deb),
liblapack: apt-get install -y liblapack-dev (deb),
libarpack++2: apt-get install -y libarpack++2-dev (deb),
gfortran: apt-get install -y gfortran (deb)
Optional: libsecret on Linux (libsecret-1-dev on
Debian/Ubuntu, libsecret-devel on Fedora/CentOS)
MOSEK (http://www.mosek.com) and MOSEK license.
Package vignettes based on R Markdown v2 or
reStructuredText require Pandoc (http://pandoc.org). The
function rst2pdf() requires rst2pdf
(https://github.com/rst2pdf/rst2pdf).
procps (linux), ps (macos), wmic (windows)
ImageJ (>=1.48), ij.jar (see
http://imagej.nih.gov/ij/), Java (>=1.6.0)
ledger (>= 3.1), hledger (>= 1.2), beanquery
GNU make (optional), libxml2 (optional), glpk (>=
4.57, optional)
Python (>= 3.10) with packages: torch,
transformers, pandas, numpy
C++17, libcurl (optional, for model downloading)
Python (>= 3.10) with jax, numpy, numpyro
(optional; for NumPyro backend via reticulate)
A system with zoneinfo data (e.g.
/usr/share/zoneinfo). On Windows the zoneinfo included with R
is used.
Python 3.x with following modules: PyGMO, NumPy,
and cloudpickle
ADMB version 11 <http://admb-project.org/> for
use.admb=TRUE; see readme.txt
external tool (installed via empi.install()
function). The package uses the implementation of the Matching
Pursuit algorithm by Piotr T. Różański, available at
https://github.com/develancer/empi.
On a Unix-alike, one of the C functions
mach_absolute_time (macOS), clock_gettime or gethrtime. If none
of these is found, the obsolescent POSIX function gettimeofday
will be tried.
NLopt library (optional, for high-performance BMDD
mode)
memory (>= 4GB) Ubuntu: build-essential,
libxml2-dev, libssl-dev, libcurl4-openssl-dev Windows: Rtools
(>= 3.5)
'Redatam' runtime engine (see https://redatam.org),
The dynamic binary library is downloaded from
<https://redatam-core.s3.us-west-2.amazonaws.com> during the
build step. Currently supported platforms are Windows and Linux
(both for x86-64 processors only)
Cargo ('Rust' package manager), rustc (>= 1.56.0,
optional)
TensorFlow (https://www.tensorflow.org), Keras
(https://keras.io), TensorFlow Probability
(https://www.tensorflow.org/probability)
A C++17 compiler. Version 8 or later of GCC will be
fine.
gdal (optional), geos (optional), proj (optional),
udunits (optional), gsl (optional), gmp (optional), glu
(optional), jags (optional), mpfr (optional), openmpi
(optional)
MiXBLUP (optional; used for multi-trait genomic
evaluations); blupf90-family (optional; used for multi-trait
genomic evaluations)
JAGS (>= 4.0.0) (see
https://mcmc-jags.sourceforge.io)
FSL (FMRIB Software Library, available at
https://fsl.fmrib.ox.ac.uk/fsl/docs/#/install/index)
libcurl: libcurl-devel (rpm) or
libcurl4-openssl-dev (deb)
A valid account MUST be registered with Microsoft's
Cognitive Services website
<https://www.microsoft.com/cognitive-services/> in order to
obtain a (free) API key. Without an API key, this package will
not work properly.
'libnng' >= 1.11 and 'libmbedtls' >= 2.5, or
'cmake' to compile NNG and/or Mbed TLS included in package
sources
pandoc, jupyter, jupyter nbconvert ("nbconvert"
python package), pywin32 (on windows)
neo4j (>=3 AND <=5) <https://neo4j.com/>
neo4j - http://www.neo4j.com, cypher-shell -
https://github.com/neo4j/cypher-shell/releases
Python (>= 3.0.0), Neptune (https://neptune.ai/)
cmake (>= 3.2.0) which is used only on Linux or
macOS systems when no system build of nlopt (>= 2.7.0) can be
found.
NetLogo (>= 5.3.1), Java (>= 11), pandoc, OpenSSL,
udunits-2, PROJ.4, GEOS, GDAL, libxml2
python3-dev: apt-get install -y python3-dev (deb),
python3-pip: apt-get install -y python3-pip (deb), numpy: pip3
install numpy (deb), scipy: pip3 install scipy (deb), nmslib:
pip3 install --no-binary :all: nmslib (deb)
JAGS (http://mcmc-jags.sourceforge.net/) for
analysis of Bayesian hierarchical models
A chromium based browser, required by "webshot2"
<https://rstudio.github.io/webshot2/>
GNU make, An ODBC3 driver manager and drivers.
odiff (>= 3.0.0) -
https://github.com/dmtrKovalenko/odiff
GNU make, pandoc (>= 1.12.3), pngquant, C++17
OpenCV 3 or newer: libopencv-dev (Debian, Ubuntu)
or opencv-devel (Fedora). The QR code detector requires at
least libopencv 4.5.2.
libarmadillo: apt-get install -y libarmadillo-dev
(deb), libblas: apt-get install -y libblas-dev (deb),
liblapack: apt-get install -y liblapack-dev (deb),
libarpack++2: apt-get install -y libarpack++2-dev (deb),
gfortran: apt-get install -y gfortran (deb), libjpeg-dev:
apt-get install -y libjpeg-dev (deb), libpng-dev: apt-get
install -y libpng-dev (deb), libfftw3-dev: apt-get install -y
libfftw3-dev (deb), libtiff5-dev: apt-get install -y
libtiff5-dev (deb)
Cargo (Rust's package manager) >= 1.70, rustc >=
1.70
Tesseract >= 5.0.0, libtesseract-dev (deb),
tesseract-devel (rpm), libleptonica-dev (deb), leptonica-devel
(rpm), tesseract-ocr-eng (deb), libpoppler-cpp-dev (deb),
poppler-cpp-devel (rpm), poppler-data (rpm/deb), libxml2-dev
(deb), libxml2-devel (rpm)
OSRM backend binaries (>= v5.27.0)
<https://github.com/Project-OSRM/osrm-backend>; package
downloads binaries automatically if not found
To use the Localhost of OSRM, you need to build
OSRM
<https://github.com/Project-OSRM/osrm-backend/wiki/Building-OSRM>
locally
cmake, protobuf-compiler, libprotobuf, libcurl,
zlib, GNU make
pandoc (https://johnmacfarlane.net/pandoc) for
exporting markdown files to other formats.
For multipoint linkage analysis, 'MERLIN'
(http://csg.sph.umich.edu/abecasis/merlin/index.html).
MERLIN (https://csg.sph.umich.edu/abecasis/merlin/)
for multipoint linkage analysis.
The 'Japanese.Rnw' vignette requires uplatex and
dvipdfmx.
OpenMPI (>= 1.5.4) on Linux, Mac, and FreeBSD.
MS-MPI (Microsoft MPI v7.1 (SDK) and Microsoft HPC Pack 2012 R2
MS-MPI Redistributable Package) on Windows.
'OpenMPI' (>= 1.5.4) on Solaris, Linux, Mac, and
FreeBSD. 'MS-MPI' (Microsoft HPC Pack 2012 R2 MS-MPI
Redistributable Package) on Windows.
Linux, Mac OSX, and Windows, or 'ZeroMQ' library >=
4.0.4. Solaris 10 needs 'ZeroMQ' library 4.0.7 and 'OpenCSW'.
Poppler C++ API: libpoppler-cpp-dev (deb) or
poppler-cpp-devel (rpm), and poppler-data (rpm/deb) package.
MERLIN (https://csg.sph.umich.edu/abecasis/merlin/)
for calculations involving multiple linked markers.
pandoc (for vault_export()), git (for
vault_commit())
OpenSSL library and headers (openssl-dev or
similar)
aria2: apt-get install -y aria2 (deb), gdal-bin:
apt-get install -y gdal-bin (deb), libgdal-dev: apt-get install
-y libgdal-dev (deb)
libssh >= 0.6.0 (the original, not libssh2)
For Windows users, Rtools (see
https://cran.r-project.org/bin/windows/Rtools/).
PROJ (>= 6, https://proj.org/download.html), GDAL
(>= 3, https://gdal.org/en/latest/download.html), NetCDF(>= 4,
https://www.unidata.ucar.edu/software/netcdf/).
pandoc (>= 1.12.3) -
http://johnmacfarlane.net/pandoc
JAGS (>= 4.0.0) (see
https://mcmc-jags.sourceforge.io/)
A POSIX system. Currently Linux and OS X are known
to work. GNU make.
proj 4.4.6 or higher (https://proj.org/)
pandoc (http://pandoc.org) for building Vignettes
and output reports as HTML
'python3' needs to built for the same architecture
R is built for (32 or 64 bit).
Python (>= 3.7), pip (for installing Python
packages), pytrends, pandas, requests
'QGIS' latest or long-term release currently
supported according to the 'QGIS' release schedule
(<https://www.qgis.org/en/site/getinvolved/development/roadmap.html>).
Older 'QGIS' releases are not officially supported, but may
work since 'QGIS' 3.16.
Chromium-based browser (e.g., Chrome, Chromium, or
Brave)
OpenBugs for functions bugs() and openbugs() or
WinBUGS 1.4 for function bugs()
freetype2, libpng, libtiff, libjpeg, libwebp,
libwebpmux
package manual and Vignettes require pandoc (>=
1.14) http://pandoc.org)
python >= 2.6, by default rasciidoc uses a system
installation of asciidoc. If a system installation of asciidoc
is not available, it downloads the sources from
(<http://gitlab.com/asciidoc>). GNU source-highlight is
recommended.
Python and boto3 >= 1.14.0
(https://aws.amazon.com/sdk-for-python)
fftw3 (libfftw3-dev (deb), or fftw-devel (rpm)),
pkg-config
Needs a running BaseX server instance. The testuser
with credentials ('Test'/'testBasex') should have admin rights.
A valid Bloomberg installation. The API headers and
dynamic library are downloaded from
<https://github.com/Rblp/blp> during the build step. See
<https://bloomberg.github.io/blpapi-docs/cpp/3.24.6> as well as
<https://www.bloomberg.com/professional/support/api-library/>
for API documentation. Currently supported platforms are
Windows and Linux (both for x86-64 processors only) as well as
macOS (for arm64 only).  Other os-cpu pairings are not
supported by Bloomberg and can therefore not be fully supported
here.
Cargo (Rust's package manager), rustc >= 1.71.1
MOSEK (http://www.mosek.com) and MOSEK License for
use of Rmosek,
GMP (GNU MP bignum library from
<https://gmplib.org/>)
A 64-bit POSIX OS such as Linux or OS X with IANA
time zone data in /usr/share/zoneinfo. On Windows the zoneinfo
included with R is used; and time parsing support is enabled
via a backport of std::get_time from the LLVM libc++ library.
GNU make, pcre2 (>= 10.00), GLib (>= 2.0.0). On
Windows, no prior installations are necessary, as pre-built
(i.e. cross-compiled) binaries of required libraries are
downloaded from a GitHub repository
(<https://github.com/PolMine/libcl>) during installation. On
macOS, static libraries of Glib are downloaded
(<https://github.com/PolMine/libglib>) if Glib is not present.
A POSIX system. Currently Linux and macOS are known
to work.
MeCab 0.996 or higher for Japanese (libmecab-dev
(deb), mecab-devel (rpm)), mecab-ko 0.999
(https://github.com/Pusnow/mecab-ko-msvc) for Korean
GNU make, Intel TBB, Windows: cmd.exe and
cscript.exe, Solaris: g++ is required
C++17, cmake >= 3.24.0, hdf5, git, patch, gnumake,
hwloc, GNU make
An available hiredis library (eg via package
libhiredis-dev on Debian/Ubuntu, hiredis-devel on
Fedora/RedHat, or directly from source from
<https://github.com/redis/hiredis>) can be used but version
1.0.2 is also included and built on demand if needed. The
optional 'rredis' package can be installed from the 'ghrr'
'drat' repo for additional illustrations and tests.
Python (>= 3.7), retriever (>= 3.0.0) (version must
be listed to patch to allow parsing)
xclip (https://github.com/astrand/xclip) or xsel
(http://www.vergenet.net/~conrad/software/xsel/) for accessing
the X11 clipboard
Windows 10 or later, 'Rtools44' or later
(https://cran.r-project.org/bin/windows/Rtools/), Microsoft
'WebView2' Runtime
(https://developer.microsoft.com/microsoft-edge/webview2/)
GNU GSL for the GSL random-number generators
GNU make, cmake, zlib, libbz2, liblzma, libcurl,
openssl (development headers)
HDF5 (>= 1.8.13), little-endian platform
'Redatam' runtime engine (see https://redatam.org),
The dynamic binary library is downloaded from
<https://redatam-core.s3.us-west-2.amazonaws.com> during the
build step. Currently supported platforms are Windows, Linux
and macOS.
'REDUCE' <http://www.reduce-algebra.com>. At least
one of the 'CSL' or 'PSL' dialects must be installed in order
to use the package. Tested with 'REDUCE' releases 6860 and 6558
for both 'CSL' and 'PSL' on Linux, and 6558 and 6339 for 'CSL'
on MacOS
Julia (>= 1.6) for optional high-performance
backend, Python (>= 3.8) with TensorFlow for deep learning
methods
Subversion for install_svn, git for install_git
Presentations written in (R)Markdown require Pandoc
(http://pandoc.org).
'unrar' (Linux/macOS) or '7-Zip' (Windows) to work
with '.rar' files.
Rust 'cargo'; the crate 'libR-sys' must compile
without error
Python (>= 3.7), rgf_python, scikit-learn (>=
0.18.0), scipy, numpy. Detailed installation instructions for
each operating system can be found in the README file.
OpenGL and GLU Library (Required for display in R.
See "Installing OpenGL support" in README.md. Not needed if
only browser displays using rglwidget() are wanted.), zlib
(optional), libpng (>=1.2.9, optional), FreeType (optional),
pandoc (>=1.14, needed for vignettes), LaTeX needed for
optional latex3d() examples.
GLPK library package (e.g., libglpk-dev on
Debian/Ubuntu)
Maxima (https://sourceforge.net/projects/maxima/,
tested with versions 5.42.0 - 5.46.0), needs to be on PATH
Python (>= 3.8), TensorFlow (>= 2.16), Keras (>=
3.0), scikit-learn
iRODS C++ HTTP API 0.2.0
(<https://github.com/irods/irods_client_http_api>)
Java JDK 1.2 or higher (for JRI/REngine JDK 1.4 or
higher), GNU make
Julia (>= 1.10.8) with the following packages
installed: 'JuliaBUGS.jl', 'LogDensityProblemsAD.jl',
'ReverseDiff.jl', 'AdvancedHMC.jl', 'AbstractMCMC.jl',
'LogDensityProblems.jl', 'MCMCChains.jl', 'RCall.jl',
'Suppressor.jl'.
libmariadb-client-lgpl-dev or libmariadb-dev or
libmysqlclient-dev, with libssl-dev (deb),
mariadb-connector-c-devel or mariadb-devel (rpm),
mariadb-connector-c or mysql-connector-c (brew)
notepad.exe, mark32.exe or mark64.exe on Windows
and only mark on Linux (>= 11.2) (see README.txt in package
directory)
pandoc (>=2.11.3 with 'commonmark_x' processing and
'sourcepos' extension, needed for 'rmarkdown' formats).
Python (>= 3.9) with the 'midasverse-midas-api'
package
gmp (>= 4.2.3), mpfr (>= 3.2.0), pdfcrop (part of
TexLive) is required to rebuild the vignettes.
libmariadb-client-dev | libmariadb-client-lgpl-dev
| libmysqlclient-dev (deb), mariadb-devel (rpm), mariadb |
mysql-connector-c (brew), mysql56_dev (csw)
The tools to run 'R CMD SHLIB' on 'Fortran' code.
The used 'Fortran' compiler must support pointer initialization
which is a feature of the 2008 standard.
roger-base (for interface functions only)
GNU Make, GCC Compiler Suite (C and Fortran)
curl Oracle Instant Client or Oracle Database
Client
Cargo (Rust's package manager), rustc >= 1.75.0,
libclang-dev (for RocksDB bindings), libsnappy-dev (for RocksDB
compression)
Poppler Glib interface headers and libraries
(<http://poppler.freedesktop.org/>) [Debian/Ubuntu:
libpoppler-glib-dev, Fedora: poppler-glib-devel]
GNU make, Windows: cmd.exe and cscript.exe
ProtoBuf libraries and compiler version 3.3.0 or
later; On Debian/Ubuntu these can be installed as
libprotoc-dev, libprotobuf-dev and protobuf-compiler, while on
Fedora/CentOS protobuf-devel and protobuf-compiler are needed.
A modern compiler is required as well.
A user API key (which one can request from the
website at <http://www.pushbullet.com>), and one or more
devices to push messages to which may be any one of an (Android
or iOS) phone, a (Chrome or Firefox, or Opera or Safari)
browser or the (Windows or Mac) desktop application provided
the corresponding Pushbullet 'app' has been installed on any
one of these.
QuantLib library (>= 1.25) from
https://quantlib.org, Boost library from https://www.boost.org
Cargo (Rust's package manager), rustc >= 1.84.1
GNU make, pandoc (>= 1.12.3), pandoc-citeproc
GNU make, CMake (>= 3.20), pandoc, libarchive,
libregex, libexpat, liblzma, libzstd, liblz4, libz2, libz,
libbcrypt, libutf8proc
Cargo (Rust's package manager), rustc >= 1.65.0
ZeroMQ >= 3.0.0: libzmq3-dev (deb) or zeromq-devel
(rpm)
Cargo (Rust's package manager), rustc (>= 1.85.1)
python (>= 3.4.0), SASPy, java (>= 7) required for
IOM access method
GNU make, curl or wget (for downloading vocabulary
files during installation)
GLPK library, including -dev or -devel part
zlib headers and libraries, GNU make, optionally
also bzip2 and POSIX-compliant regex functions.
(PDF)LaTeX (https://www.latex-project.org/) with
'pdfpages' package for studentGrowthPlot option in visualizeSGP
to bind together student growth plots into school catalogs
POSIX shared memory (optional), memory-mapped files
pandoc is required for generating reproducible
reports
torch backend, for installation guide see
https://cran.r-project.org/web/packages/torch/vignettes/installation.html
Pandoc (http://pandoc.org) needs to installed and
available in the search path.
'SLiM' is a forward simulation software for
population genetics and evolutionary biology. See
<https://messerlab.org/slim/> for installation instructions and
further information. The 'Python' coalescent framework
'msprime' and the 'tskit' module can by installed by following
the instructions at <https://tskit.dev/>.
Slurm command line programs (sacct, squeue)
For playing sounds, a command line system tool for
playing wav-files is required.
Cargo (Rust's package manager), rustc >= 1.78.0
Python (>= 3.6.0), ssw-py (>= 1.0.0). Detailed
installation instructions can be found in the README file.
C++17, arrow package with gzip codec, StarPU
LilyPond v2.22.1-2+ (needed for rendering sheet
music or writing MIDI files)
Tcl/Tk (>= 8.5), Tktable (>= 2.9, optional)
C++20, A terminal emulator supporting the Terminal
Graphics Protocol
(<https://sw.kovidgoyal.net/kitty/graphics-protocol/>) or
Sixel.
Tesseract >= 3.03 (libtesseract-dev /
tesseract-devel) and Leptonica (libleptonica-dev /
leptonica-devel). On Debian you need to install the English
training data separately (tesseract-ocr-eng)
pandoc (>= 1.12.3) suggested for using wordreg
function; LaTeX packages tikz, booktabs, dcolumn, rotating,
thumbpdf, longtable, paralist for the vignette
TensorFlow >= 1.13.0 (https://www.tensorflow.org/)
and TensorFlow IO >= 0.4.0 (https://github.com/tensorflow/io)
PhantomJS (https://phantomjs.org), pandoc (>=
1.12.3) - https://pandoc.org.
A C++17 compiler is required; on macOS compilation
version 11.0 or later is required. Optionally cmake (only when
TileDB source build selected), curl (only when TileDB source
build selected)), and git (only when TileDB source build
selected); on x86_64 and M1 platforms pre-built TileDB Embedded
libraries are available at GitHub and are used if no TileDB
installation is detected, and no other option to build or
download was specified by the user.
Python (>= 2.7), python-gdal library (For Windows,
gdal installed via OSGeo4W <https://trac.osgeo.org/osgeo4w/>
recommended) clipboard
Tcl/Tk (>= 8.6). To read and write other formats
than PPM/PGM, PNG and GIF it is required the 'tkImg' for
'Tcl/Tk' (https://sourceforge.net/projects/tkimg/), or the
debian 'libtk-img' package (Ubuntu) or the RPM 'tkimg' package
(Fedora or openSUSE).
LibTorch (https://pytorch.org/); Only x86_64
platforms are currently supported except for ARM system running
macOS.
under Linux, fftwtools needs libfftw3-dev
PROJ (>= 6, https://proj.org/download.html), GDAL
(>= 3, https://gdal.org/download.html), NetCDF(>= 4,
https://www.unidata.ucar.edu/software/netcdf/).
Typst command line tool
(<https://github.com/typst/typst>) or Quarto command line tool
(<https://github.com/quarto-dev/quarto-cli>).
udunits (>= 2) from
https://www.unidata.ucar.edu/software/udunits/
Cairo (optional, for raster output), libtiff
(optional, for TIFF output), libpng, zlib
PARI/GP >= 2.3.0 [strongly recommended for
logkda()]
Cargo (Rust's package manager), rustc >= 1.81
On Linux you can build against libv8-dev (Debian)
or v8-devel (Fedora). We also provide static libv8 binaries for
most platforms, see the README for details.
libcurl: libcurl-devel (rpm) or
libcurl4-openssl-dev (deb), GNU make.
virtuoso-opensource (Linux). For Mac & Windows,
this package can automate Virtuoso installation.
fftw3, GNU make, sox, Ghostscript, libsndfile, GDAL
'libfswatch', or 'cmake' to compile from package
sources
PhantomJS for taking screenshots, ImageMagick or
GraphicsMagick and OptiPNG for manipulating images.
Python (>= 3.9), weightederm Python package
Java (>= 5.0); WordNet database files (direct
download:
<https://wordnetcode.princeton.edu/3.0/WNdb-3.0.tar.gz>; Debian
and Fedora package: wordnet)
Fortran sources included in `tools/x13as_html`
require a Fortran compiler
libxml2: libxml2-dev (deb), libxml2-devel (rpm)
'ghostscript' or 'pdftk' for editing pdf bookmarks
and/or documentation info entries. 'exiftool' for editing pdf
documentation info entries and/or xmp metadata.
libxslt: libxslt1-dev (deb), libxslt-devel (rpm)
Cargo (Rust's package manager), rustc >= 1.70.0, xz
Cargo (>= 1.56) (Rust's package manager), rustc (>=
1.70)
Accessibility Enhancements to Popular R Shiny Functions
Artless Automatic or Artful Multivariate Matching for
Observational Studies
Reliability and Scoring Routines for the Approach-Avoidance Task
Apps Based Activities for Communicating and Understanding
Statistics
Batch Execution of R Programs on 'Kubernetes', 'SLURM', and
'Posit Workbench'
Tools for Approximate Bayesian Computation (ABC)
Data Only: Tools for Approximate Bayesian Computation (ABC)
Array Based CpG Region Analysis Pipeline
Summary Scores of the Adolescent Brain Cognitive Development
(ABCD) Study
Empirical Likelihood-Based Approximate Bayesian Computation
Implementation of Artificial Bee Colony (ABC) Optimization
Approximate Bayesian Computation via Random Forests
Asymptotically Bias-Corrected Regularized Linear Discriminant
Analysis
Adaptive Bootstrap Inference for Mediation Analysis with
Enhanced Statistical Power
Databases Used Routinely by the Brazilian Jurimetrics
Association
Useful Tools for Jurimetrical Analysis Used by the Brazilian
Jurimetrics Association
Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models
Augmented Bayesian Model Selection for Regression Models
Modelling Multivariate Data with Additive Bayesian Networks
'LiDAR' Terrain Analysis and Change Detection from Above
The Abnormal Blood Profile Score to Detect Blood Doping
Quality-of-Life Solver for "Measuring Quality of Life under
Spatial Frictions"
Interactive Feature-Based Analysis of AIRR-Seq Data
Variable Selection in Nonparametric Models using B-Splines
R Interface to the A/B Street Transport System Simulation
Software
An R-Shiny Application for Creating Visual Abstracts
Survival Analysis using Time Dependent Covariate for Animal
Breeding
High-Dimensional Principal Fitted Components and Abundant
Regression
Ansari-Bradley Test with Arbitrarily Missing Data
Inferring Directional Conservative Causal Core Gene Networks
Colour Plots with Palettes from Academic Institutions
Access the Twitter Academic Research Product Track V2 API
Endpoint
A Canonical Correlation Analysis with Inferential Guaranties
Predict Energy Expenditure from Accelerometer Data
Functions for Processing Accelerometer Data
Missing Value Imputation for Accelerometer Data
The Acute COPD Exacerbation Prediction Tool (ACCEPT)
Creation and Evaluation of Acceptance Sampling Plans
Acceptance-Rejection Method for Generating Pseudo-Random
Observations
Command Line Tools to Produce Accessible Documents using 'R
Markdown'
Improving the Accessibility of 'rmarkdown' Documents
Accrual Plots and Predictions for Clinical Trials
Natural Abundance Correction of Mass Spectrometer Data
Query the Attentional Control Data Collection or the Truth
Effect Database
Tools for Autoregressive Conditional Duration Models
Analysis of Correlated High-Dimensional Expression (ACE) Data
Optimal Bayesian Experimental Design using the ACE Algorithm
Análisis Computacional de Eventos de Protesta
ACE and AVAS for Selecting Multiple Regression Transformations
ACE Kin Pair Data Simulations and Model Fitting
Estimating Dynamic Heritability and Twin Model Comparison
Robust Estimation of the ACF from the M-Periodogram
Modeling Achievement Gap Trajectories with Hierarchical
Penalized Splines
Automated Retrieval of ACLED Conflict Event Data
Autocorrelated Conditioned Latin Hypercube Sampling
Variant Effect Calibration to ACMG/AMP Evidence Strength
Affymetrix SNP Probe-Summarization using Non-Negative Matrix
Factorization
Modelling Dependence with Multivariate Archimax (or any
User-Defined Continuous) Copulas
Exclusion-Based Parentage Assignment Using Multilocus Genotype
Data
A Tool for Semi-Automating the Statistical Disclosure Control of
Research Outputs
Algorithmic Complexity for Short Strings
Data Only: Algorithmic Complexity of Short Strings (Computed via
Coding Theorem Method)
ACSS, Corresponding INSS, and GLP Algorithms
A Companion Package for the Book "A Course in Statistics with R"
Asymptotic Classification Theory for Cognitive Diagnosis
Extract Circadian Rhythms Metrics from Actigraphy Data
Activity Fragmentation Metrics Extracted from Minute Level
Activity Data
Autocorrelation Tools Featured for Time Series
Generate Activity Counts from Raw Accelerometer Data
A 'Shiny' App to Analyze Accelerometer-Measured Daily Physical
Behavior Data
Utilities for Parsing and Plotting Activities
Finding Cancer Driver Proteins with Enriched Mutations in
Post-Translational Modification Sites
A Driver Discovery Tool for Cancer Whole Genomes
Integrative Pathway Enrichment Analysis of Multivariate Omics
Data
Activity Index Calculation using Raw 'Accelerometry' Data
Advanced Processing and Chart Generation from activPAL Events
Files
Read in Activity Data and Plot Actograms
Actuarial Functions and Heavy Tailed Distributions
Handling Single-Level and Hierarchically Structured Risk Factors
using Credibility and Random Effects Models
Computation of Actuarial Measures Using Bell G Family
Create Actuarial Experience Studies: Prepare Data, Summarize
Results, and Create Reports
A Package for Displaying Visual Scenes as They May Appear to an
Animal with Lower Acuity
Optimal Out-of-Sample Forecast Evaluation and Testing under
Stationarity
Acute Chronic Workload Ratio Calculation
The R Package Ada for Stochastic Boosting
Applies Multiclass AdaBoost.M1, SAMME and Bagging
Estimator of the Adherer Average Causal Effect
Discrete and Global Optimization Routines
Archetypoid Algorithms and Anomaly Detection
Adaptive Nature-Inspired Algorithms for Hybrid Genetic
Optimization
Adaptive Sparse Regression for Block Missing Multimodal Data
Ada-Plot and Uda-Plot for Assessing Distributional Attributes
and Normality
Adaptive Dynamics and Community Matrix Model Projections
Adaptive Approaches for Signal Detection in Pharmacovigilance
Bayesian Adaptive Designs for Diagnostic Trials
Adaptive Bioequivalence Design for In-Vitro Permeation Tests
Implementation of a Generic Adaptive Monte Carlo Markov Chain
Sampler
Automated Deconvolution Augmentation of Profiles for Tissue
Specific Cells
Design of Experiments and Factorial Plans Utilities
Adaptive Sampling for Positive Unlabeled and Label Noise
Learning
Adaptive Smoothing Spline (AdaSS) Estimator for the
Function-on-Function Linear Regression
'Arrow' Database Connectivity ('ADBC') Driver Manager
'Arrow' Database Connectivity ('ADBC') 'PostgreSQL' Driver
'Arrow' Database Connectivity ('ADBC') 'SQLite' Driver
'DBI' Compliant Database Access Using 'ADBC'
Binomial and Multinomial Additive Hazard Models
Fit Additive Hazards Models for Survival Analysis
Discover and Install Useful RStudio Addins
'RStudio' Addins for Show Outline of a R Markdown/'LaTeX'
Project
Additivity Tests in the Two Way Anova with Single Sub-Class
Numbers
Analysis of Accelerated Destructive Degradation Test Data
Analysis of Ecological Data: Exploratory and Euclidean Methods
in Environmental Sciences
Exploratory Analysis of Genetic and Genomic Data
An S4 Lattice-Based Package for the Representation of
Multivariate Data
Analysis of Habitat Selection by Animals
Group Lasso and Elastic Net Solver for Generalized Linear Models
Exploratory Analyses for the Phylogenetic Comparative Method
A 'shiny' Application for the (Audio-)Visualization of Adverse
Event Profiles
Adequacy of Probabilistic Models and General Purpose
Optimization
Estimation in Optimal Adaptive Two-Stage Designs
Get Adform Ads Data via the 'Windsor.ai' API
Assess Medication Adherence from Pharmaceutical Claims Data
Adjacency-Constrained Clustering of a Block-Diagonal Similarity
Matrix
Constructing Adjacency Matrices Based on Spatial and Feature
Similarity
Computing Sensitivity at a Fix Value of Specificity and Vice
Versa as Well as Bootstrap Metrics for ROC Curves
Parameter and Adjusted Probability Estimation for Right-Censored
Data
Remove Automated and Repeated Downloads from 'RStudio' 'CRAN'
Download Logs
Confounder-Adjusted Survival Curves and Cumulative Incidence
Functions
Accident and Development Period Adjusted Linear Pools for
Actuarial Stochastic Reserving
Utility Functions and Development Tools for the Admiral Package
Family
Metabolism Extension Package for ADaM in 'R' Asset Library
Neuroscience Extension Package for ADaM in 'R' Asset Library
Oncology Extension Package for ADaM in 'R' Asset Library
Pediatrics Extension Package for ADaM in 'R' Asset Library
Vaccine Extension Package for ADaM in 'R' Asset Library
Adaptive Mixture of Student-t Distributions
Package Admix for Admixture (aka Contamination) Models
An Interface for Running 'ADMIXTOOLS' Analyses
Algorithms using Alternating Direction Method of Multipliers
Alternating Direction Method of Multipliers to Solve Dense
Dubmatrix Problem
Estimate and Manipulate Age-Depth Models
No-U-Turn MCMC Sampling for 'ADMB' Models
Adoption Probability, Triers and Users Rate of a New Product
Use Least Squares Polynomial Regression and Statistical Testing
to Improve Savitzky-Golay
Ad-Plot and Ud-Plot for Visualizing Distributional Properties
and Normality
Design and Analysis of Locally or Globally Efficient Adaptive
Designs
Estimating, Visualizing, and Testing Average Dose-Response
Functions
Adaptive Double Sparse Iterative Hard Thresholding
Classical Model Fitting of Adsorption Isotherms
Cross-Validation Methods for Adsorption Isotherm Models
Bayesian Estimation of Adsorption Isotherms via MCMC
Upper Clopper-Pearson Confidence Limits for Burn-in Studies
under Additional Available Information
Solving 1D Advection Bi-Flux Diffusion Equation
Interactive R Tutorials to Accompany Field (2016), "An Adventure
in Statistics"
'shiny' Application for Adverse Event Analysis of 'OnCore' Data
Automatic Direct Variable Selection via Interrupted Coefficient
Estimation
Wavelet Analysis of Genomic Data from Admixed Populations
Automated and Early Detection of Disease Outbreaks
Change Point Analysis in ARIMA Forecasting
Automated and Early Detection of Seasonal Epidemic Onset and
Burden Levels
Download Australian Energy Market Operator Data
Statistical Modelling for Asymmetric Exponential Power
Distribution
A Computational Tool for Aerobiological Data
Estimating Reservoir Evaporation via Aerodynamic Approach
Estimate Aerosol Particle Collection Through Sample Lines
Tools for Text Analysis of Aesop's Fables
Produce Charts Following UK Government Analysis Function
Guidance
Government Analysis Function Recommended Accessible Colour
Palette
Diagnosis Performance Using Attributable Fraction
Accelerated Functional Failure Time Model with
Error-Contaminated Survival Times
A Finer Way to Render 3D Illustrated Objects in 'grid' Using
Affine Transformations
Raster Georeferencing, Grid Affine Transforms, Cell Abstraction
Check Validity of Greek AFM and PA Numbers
Functions for Atomic Force Microscope Force-Distance Curves
Analysis
Tools for Modelling of Animal Flight Performance
Toolkit for Regression Analysis of Kazakhstan Banking Sector
Data
Africa Macroeconomic Monitor Database API
Create Spreadsheet Publications Following Best Practice
Accelerated Failure Time Model with Generalized Estimating
Equations
Accelerated Failure Time for High Dimensional Data with MCMC
Estimating Penalized AFT Models via Coordinate Descent
R-Squared Measure under Accelerated Failure Time (AFT) Models
Semiparametric Accelerated Failure Time Model
Model Diagnostics for Accelerated Failure Time Models
Toolbox for Downloading and Extracting Copernicus AgERA5 Data
Calculate 'ActiGraph' Counts from Accelerometer Data
Age Band Decomposition Method for Tree Ring Standardization
Model Fine-Scale Age-Structured Population Data using
Open-Source Data
Inferring Age-Dependent Disease Topic from Diagnosis Data
Collection of Functions for Working with Age Intervals
Agnostic Fay-Herriot Model for Small Area Statistics
Aggregate Numeric, Date and Categorical Variables
Utilities for Aggregating Probabilistic Forecasts
Relationship Matrices for Diploid and Autopolyploid Species
Adaptive Gauss Hermite Quadrature for Bayesian Inference
Aggregation Operators and Preordered Sets
Recurrent Event Analysis Planning for Robust Andersen-Gill Model
Agreement Interval of Two Measurement Methods
Bayesian State-Space Aggregation of Brazilian Presidential Polls
Statistical Procedures for Agricultural Research
Visualization of Design of Experiments from the 'agricolae'
Package
Agricultural Crop Diversification Indices Analysis
Data Quality Checks and Statistical Assumption Testing for
Agricultural Experiments
Linear and Nonlinear Regression for Agricultural Data
Tutorial Analysis of Some Agricultural Experiments
Utilities for Data Analysis in Agriculture
Evapotranspiration and Energy Fluxes Spatial Analysis
Calculate Concentration and Dispersion in Ordered Rating Scales
Data Visualization and Statistical Tools for Agroindustrial
Experiments
Experimental Statistics and Graphics for Agricultural Sciences
Regression Analysis Linear and Nonlinear for Agriculture
Stability Analysis for Agricultural Research
Data Analysis of Pesticide Application Technology
Crosswalk Municipality and District Statistics in Germany
An R Implementation of the 'Align-GVGD' Method
Regularization for Semiparametric Additive Hazards Regression
Functions and Data for the Book 'Applied Hierarchical Modeling
in Ecology' Vols 1 and 2
An Implementation of the Artificial Hydrocarbon Networks
Fast Searching for Multiple Keywords in Multiple Texts
Consistency in the Analytic Hierarchy Process
Hybrid Method for Multiple Criteria Decision-Making (MCDM)
Flexible Parametric Accelerated Hazards Models
Build, Predict and Analyse Artificial Intelligence Models
Longitudinal Bias Auditing for Sequential Decision Systems
Testing for Compositional Pathologies in Datasets
Model Selection and Multimodel Inference Based on (Q)AIC(c)
Differential Item Functioning for AI-Scored Assessments
Access the 'Anthropic Economic Index' Dataset
Axon Integrity Evaluation System for Microscopy Images
Read AIFF Files and Convert to WAVE Format
Experimental Evaluation of Algorithm-Assisted Human
Decision-Making
Irish Weather Observing Stations Hourly Records for 2017
AI Assistant to Write and Understand R Code
Download Mexico City Pollution, Wind, and Temperature Data
Exposure Model to Air Pollutants Based on Mobility and Daily
Activities
Suite of GR Hydrological Models for Precipitation-Runoff
Modelling
Hydro-Meteorological Catchments Datasets for the 'airGR'
Packages
Ensemble-Based Data Assimilation with GR Hydrological Models
'airGR' Integrated Water Resource Management
Teaching Hydrological Modelling with the GR Rainfall-Runoff
Models ('Shiny' Interface Included)
Retrieve 'AirNow' Air Quality Observations and Forecasts
Analysis of Cost Allocation for Airport Problems
Convenience Tools for Working with Airport Data
Air Quality Measurements in Spain from 2011 to 2018
AIRR Data Representation Reference Library
Feature Screening via Adaptive Iterative Ridge (Air-HOLP and
Air-OLS)
Visualization of Simulated Datasets with Multiple Simulation
Input Dimensions
Evaluation of Algorithm Collections Using Item Response Theory
AI Screening Tools in R for Systematic Reviewing
Unified Interface for AI Model Providers
Additive Isotonic Proportional Hazards Model
Interpolation of Irregularly and Regularly Spaced Data
Functional Utilities for Data Processing
Immunoglobulin Clonal Lineage and Diversity Analysis
Download, Merge, and Process Redistricting Data
Adaptive Lasso for the Cox Regression with Interval Censored and
Possibly Left Truncated Data
PARAFAC Analysis of Fluorescence Excitation-Emission Matrices
Minimalist Theme and Vignette Kit for 'pkgdown' and R Markdown
Estimating Length-Based Indicators for Fish Stock
Quantile Regression Using Asymmetric Laplace Distribution
Adjusted Limited Dependent Variable Mixture Models
Interpretable Machine Learning and Statistical Inference with
Accumulated Local Effects (ALE)
Dynamic Model of Ammonia Emission from Field-Applied Manure
Connectivity to 'Alfresco' Content Management Repositories
Downloading Time Series from ALFRED Database for Various
Vintages
Tools to Query the 'Algaebase' Online Database, Standardize
Phytoplankton Taxonomic Data, and Perform Functional Group
Classifications
Implement an Address Search Auto Completion Menu on 'Shiny' Text
Inputs Using the 'Algolia Places' 'Javascript' Library
Allows you to Easily Interact with the Algorithmia Platform
Estimate Invasive and Alien Species (IAS) Introduction Rates
A Modified DTW Algorithm for Stratigraphic Time Series Alignment
Multiple Group Item Response Theory Alignment Helpers for
'lavaan' and 'mirt'
Pre-Processing XY Data from Experimental Methods
Acknowledge all Contributors to a Project
Allele Imputation and Haplotype Reconstruction from Pedigree
Databases
Identifying Unique Multilocus Genotypes where Genotyping Error
and Missing Data may be Present
Allele Retention, Inbreeding, and Demography
Predict and Visualize Population-Level Changes in Allele
Frequencies in Response to Climate Change
Calculating Multiple Performance Metrics of a Prediction Model
Acute Lymphoblastic Leukemia Maintenance Therapy Analysis
Exact Optimal Allocation Algorithms for Stratified Sampling
Interface for 'All of Us' Researcher Workbench
Removing Allometric Effects of Body Size in Morphological
Analysis
ALLelic Spectrum of Pleiotropy Informed Correlated Effects
Datasets from the Survival TV Series Alone
Model Classifier for Binary Classification
Fit GLM's with High-Dimensional k-Way Fixed Effects
Algorithms for High-Throughput Sequencing of Antigen-Specific T
Cells
Generalization of the Convex Hull of a Sample of Points in the
Plane
Set Alpha Based on Sample Size Using Bayes Factors
Obtain Alpha-Outlier Regions for Well-Known Probability
Distributions
Partition/Decomposition of Breeding Values by Paths of
Information
Implementation of the 3D Alpha-Shape for the Reconstruction of
3D Sets from a Point Cloud
Comprehensive R Wrapper for 'Alphavantage Financial Data' API
Lightweight Interface to the Alpha Vantage API
Bayesian Estimation for Alpha-Mixture Survival Models
Adaptive Lasso Quantile Regression with Fixed Effects
Data to Accompany Applied Linear Regression 4th Edition
Multivariate Curve Resolution Alternating Least Squares
(MCR-ALS)
Accelerated line search algorithm for simultaneous orthogonal
transformation of several positive definite symmetric matrices
to nearly diagonal form
Aggregated Latent Space Index for Binary, Ordinal, and
Continuous Data
Package Documentation Websites with 'Quarto', 'Docsify',
'Docute', or 'MkDocs'
Detection of Altered Protein Quantitative Relationships
Provides an Interface to the NREL Alternate Fuels Locator
Alternative Estimators to Adjusted R-Squared
Accessing and Analyzing Large-Scale Environmental Data
Alternating Manifold Proximal Gradient Method for Sparse PCA
An Interface to the 'AutoNavi Maps' API Geocoding Services
Thin Wrapper for Mapping Library 'AMap'('Gaode')
Get Amazon Ads Data via the 'Windsor.ai' API
Get Amazon S3 Data via the 'Windsor.ai' API
Get Amazon Sp Data via the 'Windsor.ai' API
Simulation and Estimation of Ambit Processes
Generate LaTeX Code for Auto-Multiple-Choice (AMC)
Geometric Analysis of Configurations in High-Dimensional Spaces
Anomaly Detection with Normal Probability Functions
Additive and Multiplicative Effects Models for Networks and
Relational Data
Analyze Multiple Exposure Realizations in Association Studies
American Politics-Inspired Color Palette Generator
Checks for Various Computing Environments
Compute the Adjusted Market Inefficiency Measure
Implement the AMIS Algorithm for Infectious Disease Models
Bayesian Ammi Model for Continuous Data with or without Additive
and Dominance Effect
Automated Moderated Nonlinear Factor Analysis Using 'M-plus'
Tractable Parametric Odds-Based Regression Models
Statistical Test for the Multivariate Point Null Hypotheses
Data Management Tools for Pharmacometrics
Flexible Simulation Utilities for Pharmacometric Modeling
An Algorithm for Automatic Peak Detection in Noisy Periodic and
Quasi-Periodic Signals
Shiny Apps to Support Capacity Building on Harvest Control Rules
Statistical Analysis of Amplicon Data of the Same Sample to
Identify Artefacts
Clinical Scores Calculator for Healthcare
Adaptive Multilevel Splitting for Option Simulation and Pricing
Targeted Differential and Global Enrichment Analysis of
Taxonomic Rank by Shared Asvs
Simple and Canonical Correspondence Analysis
Exploratory Data Analysis, Group Comparison Tools, and Other
Procedures
Analogue and Weighted Averaging Methods for Palaeoecology
Functions for Analysis of fMRI Datasets Stored in the ANALYZE or
'NIFTI' Format
Data Analysis and Automated R Notebook Generation
(Pre-)Clinical NCA in a Dynamic Shiny App
Construct Natural-Language Lists with Internationalization
Optimisation of the Analysis of AND-OR Decision Trees
Asynchronous Disk-Based Representation of Massive Data
Simulate a Bus Route Creel Survey of Anglers
Imports Log Files from Angstrom Engineering Thermal Evaporator
Tools for 'ROMS' the Regional Ocean Modeling System
Inferring Dominance Hierarchies and Estimating Uncertainty
Analyse Animal Sequential Behaviour and Communication
A Web-Based Graphics Device for Animated Visualisations
A Gallery of Animations in Statistics and Utilities to Create
Animations
Visualizing Changes in Performance Measures and Demographic
Affiliations using Animation
R Bindings to the 'Anime.js' Animation Library
Animated Interactive Grammar of Graphics
A Collection of ML Tools for Conservation Research
Animation of Multiple Trajectories with Uncertainty
Statistical Network Analysis of Animal Social Networks
Animate Shiny and R Markdown Content when it Comes into View
Read and Analyze 'Anki' Flashcard Databases
Compute High Dimensional Orthant Probabilities
Artificial Neural Networks for Anomaly Detection
Annotated Matrix: Matrices with Persistent Row and Column
Annotations
Annotate the Gene Symbols for Probes in Expression Array
Extract Subsequences from GenBank Annotations
Image Annotation and Polygon Outlining using Free Drawing
A Non-Parametric Statistical Test to Compare Clustering
Structures
Analysis of Moderation, Statistical Power, and Optimal Design
for Studies Detecting Difference and Equivalence
Analyses of Proportions using Anscombe Transform
Interactive Document for Working with Analysis of Variance
Create Datasets with Identical Summary Statistics
Functions and Data for the Book "Applied Nonparametric
Statistical Methods", 5th Edition
Import, Manipulate and Explore the Results of an 'Antares'
Simulation
Functional Guilds, Invasion Status, Endemism, and Rarity of Ants
Antedependence Models for Longitudinal Data
Computation of the WHO Child Growth Standards
Computation of the WHO 2007 References for School-Age Children
and Adolescents (5 to 19 Years)
An R Package for the Mean Measure of Divergence (MMD)
Statistical Methods for Anthropometric Data
Delineating Inter- And Intra-Antibody Repertoire Evolution
Antibody Titer Analysis of Vaccinated Patients
Extract Text from Microsoft Word Documents
Unified Simulation of Isomorphisms Between Ant Colony
Intelligence and Machine Learning
Sleep Quality and Anxiety in Confinement
Query 'nycflights13'-Like Air Travel Data for Given Years and
Airports
Install and Load Any Package from CRAN, Bioconductor or Github
Anything to 'POSIXct' or 'Date' Converter
Bootstrapping in Different One-Way and Two-Way ANOVA
Analysis of Overdispersed Data using S3 Methods
Data from the 'Access to Opportunities Project (AOP)'
A-Optimal Block Designs for Comparing Test Treatments with
Controls
Inference in the Balanced One-Way ANOVA Model with Random Factor
Classic, Nonparametric and Bayesian One-Way Analysis of Variance
Panel
Format Outputs of Statistical Tests According to APA Guidelines
Facilitate Writing Documents in American Psychological
Association Style, Seventh Edition
Visualization of Clonal Expansion for Single Cell Immune
Profiles
Create American Psychological Association (APA) Style Tables
Create R Markdown Text for Results in the Style of the American
Psychological Association (APA)
American Psychological Association Thesis Templates for R
Markdown
Resolving Plant Taxon Names Using the Australian Plant Census
Analysis of Unreplicated Orthogonal Experiments using All
Possible Comparisons
A New Age-Period-Cohort Model for Describing and Investigating
Inter-Cohort Differences and Life Course Dynamics
Nonparametric Interaction Tests in Balanced Two-Way ANOVA Models
Routines for Descriptive and Model-Based APC Analysis
An Implementation of the Additive Polynomial Design Matrix
Phylogenetic Methods for Multiple Gene Data
Create Interactive Chart with the JavaScript 'ApexCharts'
Library
Multiple Testing Approach using Average Power Function (APF) and
Bayes FDR Robust Estimation
Analysis with Profile Hidden Markov Models
Statistical Inference and Prediction of Annotations in
Phylogenetic Trees
Functions and Data Sets for the Book "A Progressive Introduction
to Linear Models"
Auto-Adaptive Parentage Inference Software Tolerant to Missing
Parents
Interface to 'episensr' for Sensitivity Analysis of
Epidemiological Results
Additive Partial Linear Models with Symmetric Autoregressive
Errors
Datasets from Hosmer, Lemeshow and Sturdivant, "Applied Logistic
Regression" (3rd Ed., 2013)
Use 'Aplos NCA API' for Pharmacokinetic Analysis
Decorate a 'ggplot' with Associated Information
Another Plot Package: 'Bagplots', 'Iconplots', 'Summaryplots',
Slider Functions and Others
Automated Population Pharmacokinetic Dataset Assembly
Prioritize and Delete Erroneous Taxa in a Large Phylogenetic
Tree
Tools for Choice Model Estimation and Application
Assessment of Predictions for an Ordinal Response
Interface to 'AppEEARS' NASA Web Services
Adjusted Prediction Model Performance Estimation
Get Apple Search Ads Data via the 'Windsor.ai' API
A Compilation of Applicability Domain Methods
Functions and Data Sets for 'Applied Predictive Modeling'
Utilities for the Application of a Polygenic Score to a VCF
Amyloid Propensity Prediction Neural Network
Bias-Aware Evidence Synthesis in Systematic Reviews
Code and Obtain Customized Planned Comparisons with 'appRiori'
Bayesian Prediction of Complex Computer Codes
Approximately Optimal Fine Balance Matching with Multiple Groups
Approximate and Exact Optimal Transport Methods
Get Data from 'Appsflyer' via the 'Windsor.ai' API
Datasets from Draper and Smith "Applied Regression Analysis"
(3rd Ed., 1998)
Amdahl's Profiler, Directed Optimization Made Easy
Structural Scenario Analysis for Bayesian Structural Vector
Autoregression Models
Analysing Prediction Stability of Non-Deterministic Prediction
Models
Inspect, Read, Edit and Run 'APSIM' "Next Generation" and
'APSIM' Classic
Air Pollution Tolerance Index (APTI) Calculator
Visualize Population Pyramids Aggregated by Age
Display Air Quality Model Output and Monitoring Data
Estimation and Prediction of Wet Season Calendar and Soil Water
Balance for Agriculture
A Comprehensive R Tool for Zootechnical Metrics
Integrated Development Toolbox for Aquatic Chemical Model
Generation
Access to Aquo domaintables from R (Dutch)
Rigorous Data Reduction and Error Propagation of Ar40 / Ar39
Data
Fitting Univariate Censored Linear Regression Model with
Autoregressive Errors
Geocoding with the 'ArcGIS' REST API Service
A Robust Interface to ArcGIS 'Geocoding Services'
Search for POIs using ArcGIS 'Places Service'
Post-Processing of Markov Chain Monte Carlo Simulations for
Chronological Modelling
Example Datasets from Archaeological Research
Spatial Analysis in Archaeology from Refitting Fragments
Spatial Analysis in Archaeology from Refitting Fragments (GUI)
Visualisation, Exploration, and Web Communication of
Archaeological Spatial Data
Finds the Archetypal Analysis of a Data Frame
An Archetype for Data Mining and Data Science Projects
Plant Root System Architecture Analysis Using DART and RSML
Files
Visualising Variant Set Association Test Results
Spatial Weight Construction for Archipelagic Geographies
Active Recovery of a Constrained and Hidden Set by Stepwise
Uncertainty Reduction Strategy
Multi-Format Archive and Compression Support
Retrieve Archived Web Pages from the 'Internet Archive'
Tools for Storing, Restoring and Searching for R Objects
Autoregressive Cokriging Models for Multifidelity Codes
Adaptive Regularization using Cubics for Optimization
Process ArcGIS Protocol Buffer FeatureCollections
Processing and Physical Activity Summaries of Minute Level
Activity Data
Adjusted Risk Differences via Specifically Penalized Likelihood
Annual Regional Database of the European Commission (ARDECO)
ARDL, ECM and Bounds-Test for Cointegration
Linear and Nonlinear Autoregressive Distributed Lag Models:
General-to-Specific Approach
Comprehensive ARDL: Panel, Bootstrap and Fourier Methods
Calculate Area of Triangles and Polygons
Plot Stacked Areas and Confidence Bands as Filled Polygons
Arena for the Exploration and Comparison of any ML Models
Fractional ARIMA (and Other Long Memory) Time Series Modeling
Access Argentinian Data via APIs and Curated Datasets
Access and Import WMS and WFS Data from Argentine Organizations
Argmin Inference over a Discrete Candidate Set
Accurate Estimation of Influenza Epidemics using Google Search
Data
Automatic Regression for Governing Equations (ARGOS)
Command Line Optional and Positional Argument Parser
Random Variate Generator for the Argus Distribution
Adaptable Regularized Hotelling's T^2 Test for High-Dimensional
Data
Efficient Computations of Standard Clustering Comparison
Measures
Comprehensive Statistical Tools for Agricultural Research
Hybrid ARIMA-GARCH and Two Specially Designed ML-Based Models
Likelihood Based Inference for ARIMA Modeling
Time Series Forecasting using ARIMA-ANN Hybrid Model
Archive and Unarchive Databases Using Flat Files
Exploring Social Network Structures Through Friendship-Driven
Community Detection with Association Rules Mining
Data Analysis Using Regression and Multilevel/Hierarchical
Models
Adaptive Rejection Metropolis Sampling (ARMS) via 'Rcpp'
Analysis of Large Affymetrix Microarray Data Sets
A Probe-Level Data File Format Used by 'aroma.affymetrix'
[deprecated]
Copy-Number Analysis of Large Microarray Data Sets
Core Methods and Classes Used by 'aroma.*' Packages Part of the
Aroma Framework
Geometric Morphometric Methods and Virtual Anthropology Tools
Tools for Simulating Direct Behavioral Observation Recording
Procedures Based on Alternating Renewal Processes
Fast Generators and Iterators for Permutations, Combinations,
Integer Partitions and Compositions
Apply a Function to a Margin of an Array
An Arsenal of 'R' Functions for Large-Scale Statistical
Summaries
Automatic Replication Tools for Meta-Analysis
To Insert Title, Divider, and Block of Comments
Adaptive and Robust Pipeline for Transfer Learning
Mining Association Rules and Frequent Itemsets
Classification Based on Association Rules
Mining NB-Frequent Itemsets and NB-Precise Rules
Visualizing Association Rules and Frequent Itemsets
Management and Processing of Autonomous Recording Unit (ARU)
Data
Five Novel Stochastic Regression Models with Arvind-Distributed
Errors and Effects
Data Sets for "Applied Survival Analysis Using R""
A Collection of Statistical Tools for Biologists
Export R Objects to Several Markup Languages
Create 'Ascii' Screen Casts from R Scripts
Reads Fixed-Width ASCII Data Files (.txt or .dat) that Have
Accompanying Setup Files (.sps or .sas)
Simulate the Spread of Ascochyta Blight in Chickpea
Simulations for Adaptive Seamless Designs
Interface to the Australian Statistical Geography Standard
Methods for Adaptive Shrinkage, using Empirical Bayes
Password Entry Utilities for R, Git, and SSH
Interface to the Algorithm Selection Benchmark Library
Optimal Convex M-Estimation for Linear Regression via Antitonic
Score Matching
Linkage Map Construction using the MSTmap Algorithm
Functions for the Book "Applied Statistical Modeling for
Ecologists"
Predicting and Classifying Patient Phenotypes with Multi-Omics
Data
Algorithm Portfolio Selection with Machine Learning
Animal Social Network Inference and Permutations for Ecologists
Functions for Estimating Centrographic Statistics
A General Framework for Multivariate Analysis with Optimal
Scaling
Analysis of Symmetry of Parasitic Infections
Spline Regression with Adaptive Knot Selection
Augments 'ASReml-R' in Fitting Mixed Models and Packages
Generally in Exploring Prediction Differences
Applied Singular Spectrum Analysis (ASSA)
Korean National Assembly Data for Political Science Education
Verbose Assertions for Tabular Data (Data.frames and
Data.tables)
Visualisation and Verification of Health Economic Decision
Models
Simple Assertions for Beautiful and Customisable Error Messages
Assertive Programming for R Analysis Pipelines
Assessment Tools for Regression Models with Discrete and
Semicontinuous Outcomes
Optimal Pricing of Assets with Fixed Expiry Date
Population Assignment using Genetic, Non-Genetic or Integrated
Data in a Machine Learning Framework
Infer Geographic Origin from Isotopic Data
A Suite of R Functions Implementing Spline Smoothing Techniques
Adaptive Subgroup Selection in Group Sequential Trials
Measuring Association with Recursive Binning
A User-Friendly 'shiny' Application for Exploring Associations
and Visual Patterns
Implements New and Existing Association Indices for Constructing
Animal Social Networks
Calculate the Assortativity Coefficient of Weighted and Binary
Networks
'shiny' Application for Statistical Test Assumption Checking and
Guidance
A Computational Tool for Astrochronology
Astronomy: Time and Position Functions, Misc. Utilities
R Bindings to the 'Astronomy Engine' C Library
Applied Statistical Time Series Analysis
Adaptive SURE Thresholding Using Side Information
Stochastic Volatility Models with or without Leverage
Data on Asylum and Resettlement for the UK
Asymmetric Second Order Rotatable Designs (AsymmetricSORDs)
Multidimensional Scaling of Asymmetric Proximities
Asymmetry Measures for Probability Density Functions
A Simple R Package for Classical Parametric Statistical Tests
and Confidence Intervals in Large Samples
Estimate Asymptomatic Cases via Capture/Recapture Methods
Regression Analysis of Sparse Asynchronous Longitudinal Data
Create Tables for Reporting Clinical Trials
Automatic Time Series Analysis and Forecasting using the Ata
Method
Bounding Treatment Effects by Limited Information Pooling
Estimating ATE with Misclassified Outcomes and Mismeasured
Covariates
Average Treatment Effects with Measurement Error and Variable
Selection for Confounders
Advanced Sports Performance Analysis for 'Strava' Data
Download Air Quality and Meteorological Information of Chile
Download and Tidy Australian Taxation Office Data
Tools to Handle and Publish Metadata as 'Atom' XML Format
Alert Time Quality - Evaluating Timely Epidemic Metrics
Wrapper for the 'AT' Protocol Behind 'Bluesky'
Correcting for Attenuation Due to Measurement Error
Threshold Independent Performance Measures for Probabilistic
Classifiers
Standard Conform Pure Tone Audiometry (PTA) Plots
Model Audit - Verification, Validation, and Error Analysis
Automatic Dynamic Regression using Extreme Gradient Boosting
Analysis of Data with Mixed Measurement Error and
Misclassification in Covariates
eBird Data Extraction and Processing in R
Area Under Minimum of False Positives and Negatives
Creates a Neighbourhood Using Locality Sensitive Hashing for
Gaussian Projections
TERN AusPlots Australian Ecosystem Monitoring Data
Provides Datasets About Australian Politicians
Approximate Unconditional and Permutation Tests
Author Metadata Management and Manuscript Front Matter
Automatic Variable Reduction Using Principal Component Analysis
Neural Network–Based Model Selection and Forecasting
Learning to Rank Bagging Workflows with Metalearning
Automated Covariate Selection Using HDPS Algorithm
Automatic Database Normalisation for Data Frames
An Interface to the 'AutoDesk' 'API' Platform
Automated Stacked Ensemble Classifier for Severe Class Imbalance
Automatic Construction of Forced-Choice Tests
AI-Driven Anomaly Detection for Data Quality
Automate the Creation of Generalized Additive Models (GAMs)
Auto-GO: Reproducible, Robust and High Quality Ontology
Enrichment Visualizations
Automatic Plotting and Theming of Many Graphs
Semi-Automatic Grading of R and Rmd Scripts
Automated Generation of Data-Informed GLM Models in Task-Based
fMRI Data Analysis
Multiple Heat Maps for Projected Coordinates
Automatic Generation of @importFrom Tags
Automagically Document and Install Packages Necessary to Run R
Code
Record Linkage Based on an Entropy-Maximizing Classifier
R Bindings for 'Automerge' 'CRDT' Library
Automated Mendelian Randomization Workflows and Visualizations
Auto-Generate Changelog using Conventional Commits
Development of Visualization Tools for Protein Sequence
Creating Echarts Visualizations as Easy as Possible
Automatic Linear and Logistic Regression and Survival Analysis
Minimum Distance Estimation in Autoregressive Model
An Interpretable Machine Learning-Based Automatic Clinical Score
Generator
Fully Automatic Generation of Scorecards
Retrieve Disease-Related Genes from Public Sources
Automatic Transformation of an 'R' Function into a 'shiny' App
Slide Automation for Tables, Listings and Figures
Builds Stepwise GLMs via Train and Test Approach
Variational Autoencoders for Heterogeneous Tabular Data
Automated Functions for Basic Statistical Tests
An R Port of the 'ImageJ' Plugin 'Auto Threshold'
A Novel Automatic Shifted Log Transformation
Automatic Model Selection and Prediction for Univariate Time
Series
Auto Visual Inference with Computer Vision Models
Perform the Weighted Multiplier Method on Trees
Survey Analysis with Auxiliary Discretized Variables
LASSO Auxiliary Variable Selection and Auxiliary Vector
Diagnostics
'AV1' Video Encoding for Biological Microscopy Data
Check if the Title of a Package is Available, Appropriate and
Interesting
Calculation of Average Population Attributable Fractions and
Confidence Intervals
Access to the List of Bird Species of Peru
A Variable Selection using Genetic Algorithms
A Computational Biologist’s Toolkit To Get Data From 'avidaDB'
Access and Work with the 'AviList' Global Avian Checklist
Calculate the Inertial Properties of a Flying Bird
Adaptation of Virtual Twins Method from Jared Foster
Safe Anytime Valid Inference for Linear Models
A Global Dataset of Anthropogenic Extinct Birds and their
Traits: Phylogeny Builder
Anytime-Valid Sequential Estimation of Monte-Carlo p-Values
Stratigraphic Data Processing and Section Plots
Query the USDA NWCC Air and Water Database REST API
Convert Dates to Arbitrary Week Definitions
Get Data from 'Awin' via the 'Windsor.ai' API
Amazon 'Kinesis' Consumer Application for Stream Processing
Communicating with AWS EC2 and ECS using AWS REST APIs
'AWS Key Management Service' Client Package
Data Processing of SMN Hi-Res Weather Forecast from 'AWS'
Class and Methods Definitions for Packages 'aws', 'adimpro',
'fmri', 'dwi'
Analyzing Zero-Inflated and Zero-Altered Data
Logging in 'R' and Post to 'Azure Log Analytics' Workspace
Credential Chain for Seamless 'OAuth 2.0' Authentication to
'Azure Services'
Include Azure Application Insights in Shiny Apps
Authentication Services for Azure Active Directory
Interface to 'Container Instances', 'Docker Registry' and
'Kubernetes' in 'Azure'
Interface to the 'Azure Cosmos DB' 'NoSQL' Database Service
Interface to 'Kusto'/'Azure Data Explorer'
Interface to the 'Azure Machine Learning' 'SDK'
Interface to the Table Storage Service in 'Azure'
Interface to Azure Computer Vision Services
Interface to Azure Virtual Machine Instance Metadata
Bayesian Estimation and Validation for Small-N Designs with
Rater Bias
Gene Orthologs for Model Organisms in a Tidy Data Format
Use 'nlmixr2' to Interact with Open Source and Commercial
Software
Talking to 'Docker' and 'Singularity' Containers
Parse Output from 'BabyTime' Application
Bayesian Analysis of Computer Code Output (BACCO)
Data Collection from the Central Bank of Brazil
Access Data from Brazilian Central Bank: IFdata, Active
Institutions, Balance Sheets and Normative Acts
Bayesian Classification and Information Sharing (BaCIS) Tool for
the Design of Multi-Group Phase II Clinical Trials
Reimplementations of Functions Introduced Since R-3.0.0
Exploring Portfolio-Based Conjectures About Financial
Instruments
Bayesian Analysis of Cancer Latency with Auxiliary Variable
Augmentation
Bayesian Context Trees for Discrete Sequence Data
Bayesian Estimation and Forecasting of Age-Specific Rates
Robust Explainable Outlier Detection Based on OutlierTree
Bagging Bandwidth Selection in Kernel Density and Regression
Estimation
A Binary Regression Adaptive Goodness-of-Fit Test (BAGofT)
Filter Covariance and Correlation Matrices with
Bootstrapped-Averaged Hierarchical Ansatz
Bayes Factors for Informative Hypotheses
Analyze and Compare Nucleotide Recoding RNA Sequencing Datasets
Balance Check for Multiple Covariates in Matched Observational
Studies
Balanced and Spatially Balanced Sampling
Bayesian Hierarchical Modeling for Label-Free Proteomics
Statistical Inference and Sure Independence Screening via Ball
Statistics
Expression RNA-Seq Data Analysis Based on Linear Mixed Model
Pathwise Estimation of Covariate Balancing Propensity Scores
Functions and Datasets for "Bayesian Methods: A Social and
Behavioral Sciences Approach"
High Dimensional Bayesian Mediation Analysis
Bayesian Meta-Analysis of Diagnostic Test Data
Bayesian Additive Models for Location, Scale, and Shape (and
Beyond)
Species Distribution Models as a Function of Biotic, Abiotic and
Movement Factors (BAM)
Analysis and Visualization of Macroevolutionary Dynamics on
Phylogenetic Trees
Bayesian Age-Period-Cohort Modeling and Prediction
Bayesian Analysis of the Network Autocorrelation Model
Functions for Simple a/B Split Test and Multi-Armed Bandit
Analysis
Bandit-Based Experiments and Policy Evaluation
Compute Upper Prediction Bounds on the FDP in Competition-Based
Setups
Automated Standardized Assignment of the Banff Classification
Provides Ready to Use Shapefiles for Geographical Map of
Bangladesh
Make Banner Comments with a Consistent Format
Batch Effect Removal and Addon Normalization (in Phenotype
Prediction using Gene Data)
Babson Analytics and Quantitative Methods Tools
Label Creation for Tracking and Collecting Data from Biological
Samples
Species Identification using DNA Barcodes
A Bayesian Repulsive Biclustering Model for Periodontal Data
Covariance-Based Ellipses and Annotation Tools for Ordination
Plots
Calculate Bark Beetle Phenology Using Different Models
Causal Inference using Bayesian Additive Regression Trees
Bayesian Additive Regression Trees for Confounder Selection
Visualization of BART and BARP using SHAP
Bayesian Variable Selection and Model Averaging using Bayesian
Adaptive Sampling
Bayesian Variable Selection with Shrinking and Diffusing Priors
Convert Regression Between Base Function and 'rms' Package
Fast and URL-Safe Base64 Encoder and Decoder
Utilities for Streamlined Data Import, Imputation and Modelling
Infrastructure for Computing with Basis Functions
Baseline Nowcasting for Right-Truncated Epidemiological Data
Baseline Models for Classification and Regression
Convert Files that Use 'palmerpenguins' to Work with 'datasets'
Basic Sequence Processing Tool for Biological Data
Base-Rate Item Evaluation and Typicality Scoring Using Large
Language Models
Basis Expansions for Regression Modeling
Estimation of Seed Germination Base Temperature in Thermal
Modelling
Plot Simple Features with 'base' Sensibilities
Trace Plots, Density Plots and Chain Comparisons for MCMC
Samples
Recovering a Basic Space from Issue Scales
Construct Rich Tables for Output to 'HTML'/'Excel'
Retrieval and Processing of the Spanish National Forest
Inventory
Classification of RNA Sequences using Complex Network Theory
Classification of RNA Sequences using Complex Network and
Information Theory
Bayesian Model to Archaeological Faunal Skeletal Profiles
Analysis and Visualization of Basketball Data
Bayesian Basket Trial Design and Analysis
Analytical Calculation of Basket Trial Operating Characteristics
Utility-Based Optimization for Basket Trial Designs
Simulation-Based Calculation of Basket Trial Operating
Characteristics
Wrapper Package for Several Basket Trial R Packages
Age-Specific Bayesian Survival Trajectory Analysis from
Incomplete Census or Capture-Recapture/Recovery Data
Managing Packages Removal and Installation
Batching Routines in Parallel and Passing Command-Line Arguments
to R
Statistical Experiments on Batch Computing Clusters
Downloads and Organizes Financial Data for Multiple Tickers
Consistent Batch Means Estimation of Monte Carlo Standard Errors
Semi-Supervised Bayesian Mixture Models Incorporating Batch
Correction
Convert Categorical Representations of Logicals to Actual
Logicals
Real-Time PCR Data Sets by Batsch et al. (2008)
Bayesian Adaptive Trial Simulator Software (BATSS) for
Generalised Linear Models
An R Package for Data Reduction by Battery Reduction
Bayesian Analysis of Clumped Isotope Datasets
Bayesian Estimation and Optimisation of Expected False Discovery
Rate
User Friendly Bayesian Data Analysis for Psychology
Bayesian Estimation of the Additive Main Effects and
Multiplicative Interaction Model
Bayesian Inference in the Analysis of Variance via Markov Chain
Monte Carlo in Gaussian Mixture Models
Bayesian Estimation of Mixtures of Multivariate Bernoulli
Distributions
An Implementation of Rubin's (1981) Bayesian Bootstrap
Bayesian Estimation using Bernstein Polynomial Fits Rate Matrix
Estimate Brain Networks and Connectivity with Population-Derived
Priors
Bayesian Methods for Change Point Analysis
Power Calculations and Bayesian Analysis of Count Distributions
and FECRT Data using MCMC
A Bayesian Approach for Clustering Constant-Wise Change-Point
Data
Bayesian Analysis of Censored Regression Models Under Scale
Mixture of Skew Normal Distributions
Two Arm Bayesian Clinical Trial Design with and Without
Historical Control Data
Bayesian Cure Rate Modeling for Time-to-Event Data
Methods and Tools for Bayesian Dynamic Conditional Correlation
GARCH(1,1) Model
Density Deconvolution Using Bayesian Semiparametric Methods
Bayesian Single-Arm Design with Survival Endpoints
Bayesian Dynamic Factor Analysis (DFA) with 'Stan'
Comprehensive Bayesian Model Diagnostics and Comparison Tools
Bayesian Decreasingly Informative Priors for Early Termination
Phase II Trials
Implementation of the Bayesian Discount Prior Approach for
Clinical Trials
Bayesian Smoothing of Remote Sensing Image Classification
Estimating the Degrees of Freedom of the Student's
t-Distribution under a Bayesian Framework
Computation of Bayes Factors for Common Designs
Bayesian Dynamic Borrowing with Flexible Baseline Hazard
Function
Implementation of Bayesian Neural Networks
Spatial Bayesian Methods for Task Functional MRI Studies
Bayesian Estimation of the GARCH(1,1) Model with Student-t
Innovations
Bayesian Causal Mediation Analysis using 'Stan'
Bayesian Modeling via Frequentist Goodness-of-Fit
Efficient Implementation of Gaussian Process in Bayesian
Hierarchical Models
Fast Bayesian Gaussian Process Regression Fitting
Estimate Fish Growth Using MCMC Analysis
Bayesian Grouped Weighted Quantile Sum Regression
Bayesian Dynamic Energy Budget Modelling
Bayesian Methods for Economic Data Disaggregation
Bayesian Parameter Estimation and Forecasting for
Epidemiological Models
Bayesian Gamma Regression: Joint Mean and Shape Modeling
Bayesian Lasso Regression and Tools for the Lasso Distribution
Predict Brain Asymmetry Based on Handedness and Dichotic
Listening
Simulate, Evaluate, and Analyze Dose Finding Trials with
Bayesian MCPMod
Bayesian Nonlinear Ornstein-Uhlenbeck Models with Stochastic
Volatility
Simulate and Analyse Bayesian Platform Trial with Time Trend
Sample Size and Power for Comparing Inequality Constrained
Hypotheses
Bayesian Quantitative Decision-Making Framework for Binary and
Continuous Endpoints
Plot Positive and Negative Predictive Values for Medical Tests
Bayesian Surprise for De-Biasing Thematic Maps
General-Purpose MCMC and SMC Samplers and Tools for Bayesian
Statistics
Bayesian t Regression for Modeling Mean and Scale Parameters
MCMC Estimation of Bayesian Vectorautoregressions
Bayesian Analyses for One- and Two-Sample Inference and
Regression Methods
Bayesian Methods for Image Segmentation using a Potts Model
Bayesian Analysis of List Experiments with Prior Information
Efficient Sampling for Gaussian Linear Regression with Arbitrary
Priors
Adjust Longitudinal Regression Models Using Bayesian Methodology
Bayesian Preference Learning with the Mallows Rank Model
Nested Sequential Monte Carlo for the Bayesian Mallows Model
Bayesian Post-Estimation on the Mean Scale
Bayesian Random-Effects Meta-Analysis and Meta-Regression
Bayesian Mixture Survival Models using Additive
Mixture-of-Weibull Hazards, with Lasso Shrinkage and
Stratification
A Multistate Life Table (MSLT) Methodology Based on Bayesian
Approach
Non-Parametric Bayesian Analyses of Animal Movement
Fitting Bayesian Marginal Structural Models for Longitudinal
Observational Data
A Bayesian No-Effect- Concentration (NEC) Algorithm
Bayesian Analysis of Non-Stationary Gaussian Process Models
Bayesian Prediction of Event Times for Blinded Randomized
Controlled Trials
Variable Selection in a Hierarchical Bayesian Model for a Hazard
Function
Bayesian Sample Size and Precision Considerations for Risk
Prediction Models
Bayesian Inference for Presence-Only Data
Bayesian Causal Inference for Periodontal Diseases in
Longitudinal Studies
Generate Postestimation Quantities for Bayesian MCMC Estimation
Sample Size and Power Calculation for Bayesian Testing with
Bayes Factor
Bayesian Power Prior Design for Survival Data
Fast Projection Direction for Multivariate Changepoint Detection
Bayesian Quantile Regression Models for Complex Survey Data
Analysis
Bayesian Regression Models with Global-Local Shrinkage Priors
Bayesian Regression for Dynamic Treatment Regimes
Bayesian Analysis of Replication Studies
Bayes Factors for Hierarchical Linear Models with Continuous
Predictors
Datasets and Supplemental Functions from Bayes Rules! Book
Bayesian Variable Selection Using Simplified Shotgun Stochastic
Search with Screening (S5)
Bayes Linear Estimators for Finite Population
Different Models of Posterior Distributions of Adjusted Odds
Ratio
Integrated Interface of Bayesian Single Index Models using
'nimble'
Bayesian Seemingly Unrelated Regression Models in
High-Dimensional Settings
Bayesian Survival Regression with Flexible Error and Random
Effects Distributions
Bayesian Survival Analysis for Right Censored Data
Bayesian Survival Models for High-Dimensional Data
Effect Size Targeted Bayesian Two-Sample t-Tests via Markov
Chain Monte Carlo in Gaussian Mixture Models
Understand and Describe Bayesian Models and Posterior
Distributions
Bayesian Analysis of Item-Level Twin Data
Bayes Factors, Model Choice and Variable Selection in Linear
Models
Visually Learning the Graphical Structure of Bayesian Networks
and Performing MCMC with 'Stan'
Creating Volcano Plots from Bayesian Model Posteriors
Bayesian Change-Point Detection for Process Monitoring with
Fault Detection
R Utilities Accompanying the Software Package BayesX
Distribution of the 'BayesX' C++ Sources
Bayesian Zero-Inflated Bernoulli Regression Model
Global Bayesian Foraminifera Core Top Calibration
Bayesian Shrinkage Estimators for Precision Matrices in Gaussian
Graphical Models
Chronological Bayesian Models Integrating Optically Stimulated
Luminescence and Radiocarbon Age Dating
Bayesian Multidimensional Scaling and Choice of Dimension
Computation of Bayes Factors for Common Biomedical Designs
Bayesian Fitting of Ornstein-Uhlenbeck Models to Phylogenies
Bayesian Stability Analysis of Genotype by Environment
Interaction (GEI)
On Bayesian Analysis of Threshold Autoregressive Models
Solving and Optimizing Large-Scale Nonlinear Systems
Identification of Bull and Bear States of the Market
Bayesian Estimation of Incoherent Neutron Scattering Backgrounds
Benthic Biotic Indices Calculation from Composition Data
Miscellaneous Helper Functions for B. Bischl
Bayesian Model for Genotyping using RNA-Seq
Tools for General Maximum Likelihood Estimation
Create Simple Predictive Models on Bayesian Belief Networks
Bessel and Beta Regressions via Expectation-Maximization
Algorithm for Continuous Bounded Data
Blinded Sample Size Re-Estimation for Binary Endpoints
Gene Regulatory Network Inference with Bc3net
Block Coordinate Ascent with One-Step Generalized Rosen
Algorithm
Bias Corrected Bootstrap Confidence Intervals
Bias-Corrected Bayesian Classification with Selected Features
Calculation of Option Prices Based on a Universal Solution
Bayesian Consensus Clustering for Multiple Longitudinal Features
Bivariate Distributions via Conditional Specification
Bayesian Structure and Causal Learning of Gaussian Directed
Graphs
Search and Retrieve Data from the BC Data Catalogue
The Bayesian Causal Effect Estimation Algorithm
Causal Inference using Bayesian Causal Forests
Semiparametric Bivariate Correlated Frailty Models Fit
Bivariate Correlated Frailty Models with Varied Variances
Bias-Corrected Estimates for Generalized Linear Models for
Dependent Data
Clinical Trial Calculation Based on BCHM Design
Map Layers and Spatial Utilities for British Columbia
Mixed Effect Model with the Box-Cox Transformation
Behavioral Change Point Analysis of Animal Movement
Bias-Corrected Methods for Estimating the ROC Surface of
Continuous Diagnostic Tests
'Blowfish' Key Derivation and Password Hashing
Box-Cox Symmetric Regression for Non-Negative Data
Cross-Validation for the SVD (Bi-Cross-Validation)
Gathering Monthly Banking Sector Data from BDDK of Turkey
Darwinizer: Darwin Core (DwC) Field Names Standardization
Efficient Determination of Sample Size in Balanced Design of
Experiments
Efficient Block Designs for 3-Level Factorial Experiments in
Block Size 3
Bayesian Structure Learning in Graphical Models using
Birth-Death MCMC
Bayesian Distributed Lag Interaction Models
Bayesian Distributed Lag Non-Linear Models (B-DLNM)
Transparent and Reproducible Artificial Data Generation
Inference and Design for Predictive Values in Diagnostic Tests
Bayesian Detection of Potential Risk Using Inference on Blinded
Safety Data
Remove Weekends and Holidays from ggplot2 Axes
Routines for Block Diagonal Symmetric Matrices
Block Structure Detection Using Singular Vectors
Bayesian Inference for Discrete Weibull Regression
Biometric Exploratory Analysis Creation House
Analysis of Multiplex Cytometric Bead Assays
Fast Bayesian Inference in Large Gaussian Graphical Models
Visualization via Beanplots (Like Boxplot/Stripchart/Violin
Plot)
Bayesian Estimation of Change-Points in the Slope of
Multivariate Time-Series
Bayesian Evaluation, Analysis, and Simulation Software Tools for
Trials
Bayesian Model Averaging of Covariate Adjusted Negative-Binomial
Dose-Response
Quantifies Effects of Geo/Eco Distance on Genetic
Differentiation
Extract Genotypes from a PLINK .bed File
Genomic Region Processing using Tools Such as 'BEDTools',
'BEDOPS' and 'Tabix'
Binary Endpoint Estimation with Covariate Adjustment
General Unified Threshold Model of Survival for Bees using
Bayesian Inference
Easily Play Notification Sounds on any Platform
The Bee Swarm Plot, an Alternative to Stripchart
Tools for Behavior Change Researchers and Professionals
Canonical Data Structure for Behavioural Data
Multivariate Conditional Volatility Modelling and Forecasting
Download Historical Data from the Belgrade Stock Exchange
Boltzmann Entropy of a Landscape Gradient
Likelihood Method for Evaluating Bioequivalence
Count Regression Models Based on the Bell Distribution
Access the Bangladesh Environmental Mobility Panel Dataset
28 Benchmark Densities from Berlinet/Devroye (1994)
Benchmark and Frontier Analysis Using DEA and SFA
Bayesian Estimation of Nonlinear Data (BEND)
Benford Analysis for Data Validation and Forensic Analytics
Statistical Tests for Evaluating Conformity to Benford's Law
Bayesian Estimation of Naloxone Kit Number Under-Reporting
Bent-Cable Regression for Independent Data or Autoregressive
Time Series
Bayesian Estimation for Quantile Regression Mixed Models
Bayesian Exponential Random Graph Models
Compute and Summarize Core Forest Metrics from Field Data
Bayesian Inference and Model Selection for Stochastic Epidemics
Function Collection Related to Plotting and Hydrology
Best Subset Selection in Linear, Logistic and CoxPH Models
Computations and Approximations for Bessel Functions
Best Subset GLM and Regression Utilities
Generating Bootstrap Estimation Distributions of HR Data
Bayesian Estimation of Intervention Effects
Burden Estimate of Common Communicable Diseases in Settlements
of Displaced Populations
Beta Autoregressive Moving Average Models
Mini Games from Adventures of Beta and Bit
A Family of Beta Mixture Models for Clustering Beta-Valued DNA
Methylation Data
Confidence Intervals for Standardized Regression Coefficients
Functions for Working with Two- And Four-Parameter Beta
Probability Distributions and Psychometric Analysis of
Classifications
Partitioning Beta Diversity into Turnover and Nestedness
Components
Calculate Power and Sample Size with Beta Regression
Taxonomic Uncertainty on Multivariate Analyses of Ecological
Data
Beta Regression for Interval-Censored Scale-Derived Outcomes
Robust Confidence Intervals for Standardized Regression
Coefficients
Betas-Select in Structural Equation Models and Linear Models
Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH
Models
Better Statistics for OLS and Binomial Logistic Regression
Bayesian Evaluation of Variant Involvement in Mendelian Disease
Visualize and Parse the Output of 'BeXY'
Compare the Goodness of Fit of Benford's and Blondeau Da Silva's
Digit Distributions to a Given Dataset
Bayesian Spectral Inference for Time Series
Bayes Factor Design for Two-Arm Binomial Trials
Operating Characteristics for the Bayesian Optimal Interval
Design with Back Filling
Backfill Bayesian Optimal Interval Design Using Efficacy and
Toxicity
Buttler-Fickel Distance and R2 for Mixed-Scale Cluster Analysis
Flexible Bayes Factor Testing of Scientific Expectations
Power and Sample Size Calculations for Bayes Factor Analysis
Get Data from the Swiss Federal Statistical Office
Plot Maps from Switzerland by Swiss Federal Statistical Office
Bayesian Framework for Computational Modeling
A Suite of Packages for Analysis of Big Genomic Data
Bimodal GEV Distribution with Location Parameter
Binary Generalized Extreme Value Additive Models
Bell-G and Complementary Bell-G Family of Distributions
Bayesian Genomic Linear Models Applied to GE Genome Selection
Bayesian Estimation of Generalized Graded Unfolding Model
Parameters
Example BGM Files for the Atlantis Ecosystem Model
An R Package for Extended Behavior Genetics Analysis
Bayesian Analysis of Networks of Binary and/or Ordinal Variables
Markov Beta and Gamma Processes for Modeling Hazard Rates
Estimate the Burden of Healthcare-Associated Infections
Bayesian Hierarchical Models for Basket Trials
Bayesian Hierarchical Multi-Subject Multiscale Analysis of
Functional MRI (fMRI) Data
Bayesian Hierarchical Poisson Models for Multiple Grouped
Outcomes with Clustering
Structural Bayesian Vector Autoregression Models
Blinding Assessment Indexes for Randomized, Controlled, Clinical
Trials
A GUI to Correct Measurement Bias in DNA Methylation Analyses
Create Different Types of Bibliometric Networks
Document-Level Matching Between Bibliographic Datasets
Integrative Inference of De Novo Cis-Regulatory Modules
Bayesian Inference for Directed Acyclic Graphs
Efficient Estimation of Bid-Ask Spreads from Open, High, Low,
and Close Prices
Calculates the Bidimensional Regression Between Two 2D
Configurations
Work with 'BIDS' (Brain Imaging Data Structure) Projects
A Brain Imaging Data Structure ('BIDS') Parser
Behavioral Insight Design: A Toolkit for Integrating Behavioral
Science in UI/UX Design
Tools for Accessing the Botanical Information and Ecology
Network Database
Tools for Survey Statistics in Educational Assessment
Branch-Level Inference Framework for Recognizing Optimal Shifts
in Traits
'BLAS' and 'LAPACK' Routines for Native R Matrices and
'big.matrix' Objects
Utilities for 'big.matrix' Objects from Package 'bigmemory'
Approximate k-Nearest Neighbour Search for 'bigmemory' Matrices
with Annoy
Perform Boolean Operations on Large Numbers
Flexibly Format Dates and Times to a Given Locale
Distances for Machine Learning and Statistics in the Context of
Big Data
Secure and Intuitive Access to 'BigDataPE' 'API' Datasets
Title: Scalable Statistical Computing with HDF5-Backed Matrices
Case-Cotrol Analysis of Multi-Allelic Loci
Scalable Bayesian Disease Mapping Models for High-Dimensional
Data
Fit, Simulate, and Diagnose Hierarchical Exponential-Family
Models for Big Networks
Exact Search and Graph Construction for 'bigmemory' Matrices
Biochemically Intuitive Generalized Loewe Model
Extending Lasso Model Fitting to Big Data
Physical and Physiological Ecosystem Properties from Eddy
Covariance Data
Bounded Memory Linear and Generalized Linear Models
Making Optimal Matching Size-Scalable Using Optimal Calipers
Manage Massive Matrices with Shared Memory and Memory-Mapped
Files
A Shared Resource Interface for Bigmemory Project Packages
Arbitrary-Precision Integer and Floating-Point Mathematics
Principal Component Analysis for 'bigmemory' Matrices
Partial Least Squares for Cox Models with Big Matrices
Partial Least Squares Regression Models with Big Matrices
Big Quadratic Inverse Covariance Estimation
Breeding Insight Genomics Functions for Polyploid and Diploid
Species
Generalized Linear Models (GLM) for Large Data Sets
An Interface to Google's 'BigQuery' 'API'
An Interface to Google's 'BigQuery Storage' API
Fast Generation of High-Dimensional Random Vectors
Statistical Tools for Filebacked Big Matrices
Big Survival Analysis Using Stochastic Gradient Descent
Table, Apply, and Split Functionality for Matrix and
'big.matrix' Objects
Nonparametric Analysis of Bivariate Gap Time with Competing
Risks
Sparse Estimation of Large Time Series Models
Dimension Reduction Methods for Multivariate Time Series
Co-Clustering Adjusted Rand Index and Bikm1 Procedure for
Contingency and Binary Data-Sets
Contains Data of Billboard Hot 100 Songs
Create Interactive Chart with the JavaScript 'Billboard' Library
Hierarchical Probit Estimation for Dichotomized Data
Threshold Cut Point of Probability for a Binary Classifier Model
Creates, Merges, and Reads Binary Dosage Files
Variable Selection for Binary Data Using the EM Algorithm
Mean and Scale-Factor Modeling of Under- And Over-Dispersed
Binary Data
Fit and Predict a Gaussian Process Model with (Time-Series)
Binary Response
Reinforcement Learning Tools for Two-Alternative Forced Choice
Tasks
Estimate the Correlation Between Two Irregular Time Series
Multi-Class Discriminant Analysis using Binary Predictors
Methods for Analyzing Binned Income Data
Estimates Parameters of Functions Driving Binomial Random
Variables
Get Bing Ads Data via the 'Windsor.ai' API
Evaluation and Experimental Design for Binomial Group Testing
Calculate Boundaries and Conditional Power for Single Arm Group
Sequential Test with Binary Endpoint
Processes Binary Data Obtained from Fragment Analysis (Such as
AFLPs, ISSRs, and RFLPs)
Data Generation with Binary and Continuous Non-Normal Components
Simultaneous Generation of Multivariate Binary and Normal
Variates
Binomial Confidence Intervals for Several Parameterizations
Confidence Intervals for a Binomial Proportion
Calculates the Statistical Significance of a Trend in a Set of
Measurements
Concurrent Generation of Binary, Ordinal and Continuous Data
Depth-Dependent Binocular Visual Fields Simulation
Cut Numeric Values into Evenly Distributed Groups
Piecewise Smooth Regression by Bootstrapped Binary Segmentation
Efficient Implementation of Binary Segmentation
Exact Binary Sequential Designs and Analysis
Bayesian Inference for Neyman-Scott Point Processes
Data Preprocessing, Binning for Classification and Regression
Bayesian BIN (Bias, Information, Noise) Model of Forecasting
Predict Environmental Conditions from Biological Observations
Analyse Audio Recordings and Automatically Extract Animal
Vocalizations
Access Data Dependencies Installed Through 'Biobricks.ai'
Access the Bioconductor Project Package Repository
Create and Manipulate BioCompute Objects
Package for Community Ecology and Suitability Analysis
'shiny' Application for Biological Dosimetry
Multilevel Modeling of Dendroclimatical Fluctuations
Process Biogas Data and Predict Biogas Production
Biological Graph Signal Processing for Spatial Data Analysis
Mathematical Modelling of (Dynamic) Microbial Inactivation
Leakage-Safe Modeling and Auditing for Genomic and Clinical Data
Create Hyperlinks to Biological Databases and Resources
Biologically Explainable Machine Learning Framework
Estimating Aboveground Biomass and Its Uncertainty in Tropical
Forests
Functions to Assist Design and Analysis of Agronomic Experiments
Ensemble Platform for Species Distribution Modeling
Bioinformatics Modeling with Recursion and Autoencoder-Based
Ensemble
Biomarker Prognostic Enrichment Tool for Time-to-Event Trial
Extracting Insights from Biological Images
An R Package for Biomarkers Analysis in Precision Medicine
Biological Analysis and Visualization of Weather Radar Data
From Biological Sequences and Simulations to Correlation
Analysis
From Biological Sequences to Multidimensional Scaling
Biodiversity Index Calculation and Bootstrap Confidence Interval
Estimation
Distributional Data Analysis Techniques for Biosensor Data
A Toolbox for Manipulating Biological Sequences
Tools for Electromyogram Signals (EMG) Analysis
Bioacoustic Basic Operations with Decibels and the Passive Sonar
Equation
Biomarker Selection in Penalized Regression Models
Utility Functions, Datasets and Extended Examples for Survival
Analysis
Biostatistics and Clinical Data Analysis
Practical Functions for Biostatistics Beginners
Nested Data Summary, Adverse Events and REDCap
Standardized Processing and Analysis of Thermal Imaging Data in
Animal Studies
Calculation of Freshwater Biotic Indices
Tools to Use and Explore the 'BioTIME' Database
Tools for Biometry and Applied Statistics in Agricultural
Science
Image Processing Tools for Barnes Maze Experiments
Create Area-Proportional Venn Diagrams from Biological Lists
Visualizing the Elements Within Bio-Sequences
A Curated Collection of Biodiversity and Species Datasets and
Utilities
Visualising Bipartite Networks and Calculating Some (Ecological)
Indices
Partition Bipartite Network into Non-Overlapping Biclusters by
Optimizing Bipartite Modularity
Bayesian Individual Patient Data Meta-Analysis using 'JAGS'
Construct Reactive Calibrated Axes Biplots
Bootstrap on Classical Biplots and Clustering Disjoint Biplot
Logistic Biplot Estimation Using Machine Learning Algorithms
Ranking Nodes in Bipartite and Weighted Networks
Create Palettes from the Colors of the World's Birds
Sniffing Emergence and Trajectories in Academic Papers and
Patents
Bayesian Instrumental Regression for Disparity Estimation
Deep Learning for Automated (Bird) Sound Identification
Methods to Analyse Ring Re-Encounter Data
Migration Traffic Rate Calculation Package for 'Birdscan MR1'
Radars
The R Package for "The Basics of Item Response Theory Using R"
Programmatic Access to Bank for International Settlements Data
Tools and Palettes for Bivariate Thematic Mapping
Download Data from the Bank for International Settlements (BIS)
Statistical Tools for Bivariate Spatial Dependence Analysis
Cumulative History Analysis for Bistable Perception Time Series
Classes and Methods for Fast Memory-Efficient Boolean Selections
A S3 Class for Vectors of 64bit Integers
Binarization and Trinarization of One-Dimensional Data
Bidirectional Two-Stage Least Squares Estimation
Read and Write Bits from Files, Connections and Raw Vectors
Bivariate Hurdle Regression with Bayesian Model Averaging
Create Bivariate Choropleth Maps with 'Leaflet'
Bivariate Laplace Transforms, Stochastic Orders, and Entropy
Measures in Reliability
Bivariate Alternating Recurrent Event Data Analysis
Tolerance Interval and EIV Regression - Method Comparison
Studies
Bivariate Residual Plots with Simulation Polygons
Generation of Bivariate Uniform Data and Its Relation to
Bivariate Binary Data
Conduct Univariate and Bivariate Wavelet Analyses
Compute the Biweight Mean Vector and Covariance & Correlation
Matrice
Business Days Calculations and Utilities
Bivariate Zero-Inflated Count Models Using Copulas
Parallel Chain Tools for Bayesian Kernel Machine Regression
Black Box Optimization and Exploration of Parameter Space
Read and Write FWF Files in the 'Blaise' Format
Blaker's Binomial and Poisson Confidence Limits
Plots (Slightly Extended) Bland-Altman Plots
Bayesian Inference with Laplace Approximations and P-Splines
Native R Implementation of an Efficient BLAST-Like Algorithm
Robust Bayesian Longitudinal Regularized Semiparametric Mixed
Models
Joint Analysis of Experiments with Mixtures and Random Effects
Record Linkage for Empirically Motivated Priors
Bayesian Functional Linear Regression with Sparse Step Functions
Bioinformatics Library for Integrated Tools
Data Files and Functions Accompanying the Book "Bayesian Data
Analysis in Ecology using R, BUGS and Stan"
A Simple S3 Class for Representing Vectors of Binary Data
('BLOBS')
Estimation of Large Block Covariance Matrices
Spatial and Environmental Blocking for K-Fold and LOO
Cross-Validation
Generation of Blocked Fractional Factorial Designs (Two-Level
and Three-Level)
Block Forests: Random Forests for Blocks of Clinical and Omics
Covariate Data
Various Blocking Methods for Entity Resolution
Select an Optimal Block-Length to Bootstrap Dependent Data
(Block Bootstrap)
blockmatrix: Tools to solve algebraic systems with partitioned
matrices
Generalized and Classical Blockmodeling of Valued Networks
GUI for the Generalised Blockmodeling of Valued Networks
Latent and Stochastic Block Model Estimation by a 'V-EM'
Algorithm
A Block-Based Framework for Data Manipulation and Visualization
Graphical Web-Framework for Data Manipulation and Visualization
A Directed Acyclic Graph Extension for 'blockr'
Interactive 'dplyr' Data Transformation Blocks
Interactive File Import and Export Blocks
Randomization for Block Random Clinical Trials
Nested and Crossed Block Designs for Factorial and Unstructured
Treatment Sets
Block, Assign, and Diagnose Potential Interference in Randomized
Experiments
Block-Wise Rank in Similarity Graph Edge-Count Two-Sample Test
(BRISE)
Estimate and Visualize Voting Blocs' Partisan Contributions
Create Blogs and Websites with R Markdown
Methods to Impute and Analyze Data with BLOQ Observations
Tools for Developing Binary Logistic Regression Models
Compress and Decompress Data Using the 'BLOSC' Library
Dose Escalation Design in Phase I Oncology Trial Using Bayesian
Logistic Regression Modeling
Stochastic Rainfall Generator Bartlett-Lewis Rectangular Pulse
Model
Interactive Document for Working with Binary Logistic Regression
Analysis
Data Viewer for Bureau of Labor Statistics Data
Download Time Series Data from the U.S. Bureau of Labor
Statistics
Make Requests from the Bureau of Labor Statistics API
Estimation of Organic Carbon Stocks and Sequestration Rates from
Soil Core Data
Blyth-Still-Casella Exact Binomial Confidence Intervals
Multivariate Extremes: Bayesian Estimation of the Spectral
Measure
Bayesian Multivariate Analysis of Summary Statistics
Bayesian Analysis for Multivariate Categorical Outcomes
CONCOR for Structural- And Regular-Equivalence Blockmodeling
Mediation Analysis with Missing Data Using Bootstrap
Spatial Interpolation using Bayesian Maximum Entropy (BME)
Mediation Analysis with Missing Data and Non-Normal Data
Bayesian Multidimensional Generalized Graded Unfolding Model
Miscellaneous Functions for Panel Data, Quantiles, and Printing
Results
Bayesian MI-LASSO for Variable Selection on Multiply-Imputed
Datasets
Bayesian Estimation for Finite Mixture of Distributions
Bayesian Multiple-Membership Multilevel Models with
Parameterizable Weight Functions
Easy and Accessible Bayesian Measurement Models Using 'brms'
An Implementation of the Bayesian Markov (Renewal) Mixed Models
Bayesian Multilevel Single Case Models using 'Stan'
Bayesian Modeling of Spatio-Temporal Data with R
Learning Discrete Bayesian Network Classifiers from Data
Bounding Omitted Variable Bias Using Auxiliary Data
Bayesian Network Structure Learning, Parameter Learning and
Inference
Bayesian Network Meta-Analysis using 'JAGS'
An Implementation of Sensitivity Analysis in Bayesian Networks
Bagged k-Nearest Neighbors Survival Prediction
Bayesian Nonparametric Sensitivity Analysis of Multiple Testing
Procedures for p Values
Simulate Genotypes from the BN-PSD Admixture Model
A Bayesian Nonparametric Algorithm for Time Series Clustering
A Repository of Bayesian Networks from the Academic Literature
Pathway Enrichment Analysis Based on Bayesian Network
Bayesian Non- And Semi-Parametric Model Fitting
Bayesian Network Structure Learning from Data with Missing
Values
Bayesian Networks Interactive Visualization and Explainable
Artificial Intelligence
Bayesian Output Analysis Program (BOA) for MCMC
Board Games and Tools for Building Board Games
Profiling of Peripheral Blood Mononuclear Cells using CyTOF
Call the Bus Open Data Service ('BODS') API Through R
Percent Body Fat Values Using Anthropometric Prediction
Equations
Reference Values for CT-Assessed Body Composition
Download Data from the 'Bank of England' Statistical Database
Real-Time PCR Data Sets by Boggy et al. (2010)
Reynolds-Style Boids and Swarm Simulation
Interface to the Boilerpipe Java Library
Managing and Compiling Manuscript Templates
Bayesian Optimal INterval (BOIN) Design for Single-Agent and
Drug- Combination Phase I Clinical Trials
Conduct Simulation Study of Bayesian Optimal Interval Design
with BOIN-ET Family
Model Consistent Lasso Estimation Through the Bootstrap
Retrieve, Transform and Analyze the Barcode of Life Data Systems
Data
Functions for Elementary Bayesian Inference
Methods for Fixed-Income Valuation, Risk and Return
Fixed Coupon Bond Valuation Allowing for Odd Coupon Periods and
Various Day Count Conventions
Maps Bone Densities from CT Scans to Surface Models
An Improved Multiple Testing Procedure for Controlling False
Discovery Rates
Component-Wise Gradient Boosting after Multiple Imputation
Functions for the Book "Bootstrap for Dependent Data, with an R
Package"
Some Distributions from the 'Boost' Library and More
Authoring Books and Technical Documents with R Markdown
Construction, Simulation and Analysis of Boolean Networks
A Boosting Approach to Data Envelopment Analysis
'R' Bindings for the 'Boost' Math Functions
Boosting for Multivariate Longitudinal Responses
Boosted Multivariate Trees for Longitudinal Data
A Bootstrap-Based Heterogeneity Test for Meta-Analysis
Bootstrapping Estimates of Clustering Stability
Combine Parameter Estimates via Parametric Bootstrap
Bootstrapping the ARDL Tests for Cointegration
Bootstrap Confidence Intervals on Effect Sizes
Simulation and Comparison of Dissolution Profiles
Bootstrap Inference for Multiple Imputation
A Bootstrap Augmented k-Means Algorithm for Fuzzy Partitions
Bootstrapped Confidence Intervals for (Negative) Likelihood
Ratio Tests
Bootstrap Hypothesis Tests for Treatment Effects in One-Way
ANOVA with Unequal Variances
Bootstrap Resampling for Multilevel Models
Bootstrap-MRMR Technique for Informative Gene Selection
Bootstrap Methods for Various Network Estimation Routines
Bootstrap Hyperparameter Selection for PLS Models and Extensions
Bootstrap Prediction Intervals and Bias-Corrected Forecasting
A Bootstrap Test for the Probability of Ruin in the Classical
Risk Process
Functions for the Book "An Introduction to the Bootstrap"
Bootstrap Algorithms for Finite Population Inference
Bootstrap cis-QTL Method that Corrects for the Winner's Curse
Bootstrap-Based Hypothesis Testing using Different Resampling
Schemes
Bootstrap Methods for Complete Survey Data
Fast, Exact Bootstrap Principal Component Analysis for High
Dimensional Data
Nonparametric Bootstrap Test with Pooled Resampling Card Game
Test Stationarity using Bootstrap Wavelet Packet Tests
Bayesian Optimal Phase II Design with Futility and Efficacy
Stopping Boundaries
Bayesian Ordination and Regression AnaLysis
Bounded Outcome Risk Guard for Model Evaluation
Estimate Causal Effects with Borrowing Between Data Sources
Wrapper Algorithm for All Relevant Feature Selection
Computes Exact Bounds of Spearman's Footrule with Missing Data
A Bunch of Structure and Sequence Analysis
Bound on the Error of the First-Order Edgeworth Expansion
Fit Bounded Continuous Item Response Theory Models to Data
Analytic Solutions for (Ground-Water) Boussinesq Equation
Outlier Detection and Influence Diagnostics for Meta-Analysis
Functions to Create Publication-Quality Plots
Write Reusable, Composable and Modular R Code
Provides 'box' Compatibility for 'languageserver'
Box-Cox-Type Transformations for Linear and Logistic Models with
Random Effects
Clustering Method Based on Boxplot Statistics
Double Box Plot for Two-Axes Correlation
Boxplot and Significance Test for Two Groups
Blood Pressure Device Accuracy Evaluation: Statistical
Considerations
Nonparametric Bounds for the Average Causal Effect Due to Balke
and Pearl and Extensions
Biplot Analysis for Multivariate Data Using Principal Components
Beta Product Confidence Procedure for Right Censored Data
Bayesian Model Selection Approach for Parsimonious Gaussian
Mixture Models
Bayesian partial least squares regression
Bayesian Purity Model to Estimate Tumor Purity
Visualize Process Execution Data on 'BPMN' Diagrams
Bayesian Projected Normal Regression Models for Circular Data
Computations Around Bayesian Predictive Power
Causal Effects in Principal Strata Defined by Antidrug
Antibodies
Forecasting with Bayesian Panel Vector Autoregressions
Bayesian Quantile Regression for Ordinal Models
Bias Reduction Through Analysis of Competing Events (BRACE)
BRACoD: Bayesian Regression Analysis of Compositional Data
Calculate the Revealed Aggregator of Probability Predictions
Visualize Combined Action Response Surfaces and Report BRAID
Analyses
Fitting Combined Action with the BRAID Response Surface Model
Inference the Partial Correlations Based on Time Series Data
Region-Level Connectivity Network Construction via Kernel
Canonical Correlation Analysis
Hypothesis Testing for Populations of Brain Networks
Helper Functions to 'misc3d' and 'rgl' Packages for Brain
Imaging
Efficient Best Subset Selection for GLMs via Branch and Bound
Algorithms
Simulation and Estimation for Branching Processes
Calculate Outbreak Probabilities for a Branching Process Model
Unified Branding with a Simple YAML File
Brand Identity Management Using brand.yml Standard
Bootstrapped Robustness Assessment for Qualitative Comparative
Analysis
Null Hypothesis Bayesian Response-Adaptive Randomization
Bayesian Screening and Variable Selection
Accesses Brazilian Public Security Data from SINESP Since 2015
Access Brazilian Data via APIs and Curated Datasets
Download and Processing of Automatic Weather Stations (AWS) Data
of INMET-Brazil
Fetch Zonal Statistics of Weather Indicators for Brazilian
Municipalities
Unified Framework for Identification and Ecological
Interpretation of Microbial Data from Bioenergy Research
Centers
Analyze Big Files Without Loading Them in Memory
Estimates Degrees of Relatedness (Up to the Second Degree) for
Extreme Low-Coverage Data
Species Richness Estimation and Modeling
Model Agnostic Explainers for Individual Predictions
Methods for Fast Multiple Change-Point/Break-Point Detection and
Estimation
Core Functions to Read and Fit 13c Time Series from Breath Tests
Stan-Based Fit to Gastric Emptying Curves
Easy and Efficient Batch Processing of Regression Models
Brain Cell Type Specific Gene Expression Analysis
Templating Framework for Report Generation
Access to Brazilian Macroeconomic and Financial Time Series
Bias Reduction in Binomial-Response Generalized Linear Models
Bias Reduction in Generalized Linear Models
Interface with the Brickset API for Getting Data About LEGO Sets
An Implementation of the Bridge Distribution with Logit-Link as
in Wang and Louis (2003)
Genome-Wide RNA Degradation Analysis Using BRIC-Seq Data
Bridge Sampling for Marginal Likelihoods and Bayes Factors
Bridging Data Frequencies for Timely Economic Forecasts
A Tree and Forest Tool for Classification and Regression
Access D2L 'Brightspace' Data Sets via the 'BDS' API
Package for Brik, Fabrik and Fdebrik Algorithms to Initialise
Kmeans
Computation of BRINDA Adjusted Micronutrient Biomarkers for
Inflammation
Fast Inference for Large Spatial Datasets using BRISC
Bayesian Marginal Effects for 'brms' Models
Bayesian Regularization for Feed-Forward Neural Networks
Broadcasted Array Operations Like 'NumPy'
Broken Adaptive Ridge Regression with Cyclops
Broken Stick Model for Irregular Longitudinal Data
Browse Over Longitudinal Data Graphically and Analytically in R
Convert Statistical Objects into Tidy Tibbles
A Compression Format Optimized for the Web
Methods for Bivariate Poverty Line Calculations
Bayesian Analysis of Quantile Regression Models
Bayesian Regression Robustness Assessment Test
Broadly Useful Convenient and Efficient R Functions
High-Level Modeling Functions with 'torch'
A 'Bootstrap 4' Version of 'shinydashboard'
Branding, Theme Application and Navigation Utilities for
'bs4Dash' Dashboards
Safety Assessment in Agricultural Field Trials
Bayesian State-Space Models for Animal Movement
Bayesian Spectral Analysis Models using Gaussian Process Priors
Bayesian Survival Model with Lasso Shrinkage Using Generalized
Weibull Regression
Nonparametric Smoothing of the Hazard Function
Modeling and Computing Biogenic Silica ('bSi') from Inland and
Pelagic Sediments
Bayesian Super Imposition by Translation and Rotation Growth
Curve Analysis
Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'
Bayes Screening and Model Discrimination
Build Decision Trees with Optimal Multivariate Splits
Analysis of Microbial Social Behavior in Bacterial Consortia
Bayesian Proposal to Fit Spatial Econometric Models
Bayesian Spatial Blind Source Separation
Bayesian Sparse Estimation of a Covariance Matrix
Adds Functionality to the R Markdown + Shiny Bootstrap Framework
Asymptotic Covariance Matrices of Some BSS Mixing and Unmixing
Matrix Estimates
Bayesian Sample Size for Binomial Proportions
Bayesian Inference of Non-Linear and Non-Gaussian State Space
Models
Blind Source Separation for Multivariate Spatial Data using
Eigen Analysis
Whitening Data as Preparation for Blind Source Separation
Bayesian Spatio-Temporal Factor Analysis Model
Create HTML Content with Bootstrap 5 Classes and Layouts
Association Among Disease Counts and Socio-Environmental Factors
Submitter and Monitor of the 'LSF Cluster'
Bayesian Estimation of Structural Vector Autoregressive Models
Bayesian SVARs with Sign, Zero, and Narrative Restrictions
Fitting a Log-Binomial Model Using the Bekhit–Schöpe–Wagenpfeil
(BSW) Algorithm
Beyond the Border - Kernel Density Estimation for Urban
Geography
Bradley-Terry Model with Exponential Time Decayed Log-Likelihood
and Adaptive Lasso
Temporal Exponential Random Graph Models by Bootstrapped
Pseudolikelihood
Bayesian Hierarchical Models for Single-Cell Protein Data
Modelling Heterogeneity in Paired Comparison Data
Bayesian Treed Machine Learning for Personalized Prediction
Bayesian Treed Regression Model for Personalized Prediction and
Precision Diagnostics
Estimate the Number of Factors in Large Nonstationary Datasets
A Toolkit for Connecting R and Large Language Models
Implementing BTYD Models with the Log Sum Exp Patch
Produces 'bubbleHeatmap' Plots for Visualising Metabolomics Data
Beautiful Bubbles for 'shiny' and 'rmarkdown' Backgrounds
Bias and Uncertainty Corrected Sample Size
A Deep Learning for Statistical Classification and Regression
Analysis with Random Effects
Partial Identification of Causal Effects with Mostly Invalid
Instruments
Stepwise Elimination and Term Reordering for Mixed-Effects
Regression
Organize & Run Build Scripts Comfortably
System for Building and Debugging C/C++ Dynamic Libraries
Buckley-James Regression for Survival Data with High-Dimensional
Covariates
Quality Control and Outlier Identification in Bulk for
Multicenter Trials
The Ultimate Tool for Reading Data in Bulk
Automatic Groove Identification via Bayesian Changepoint
Detection
Bullish Trading Strategies Through Graphs
Visualising Multiple Pairwise Variable Correlations and Other
Scores
Tools for Modeling Bumblebee Colony Growth and Decline
Quantify Disease Transmission Within and Between Population
Groups
Analyze Bunching in a Kink or Notch Setting
Serialize Model Objects with a Consistent Interface
Marginal Survival Estimation with Covariate Adjustment
Deploy '_server.yml' Compliant Applications to 'DigitalOcean'
'Burgle': Stealing the Necessary Parts of Model Objects
R Wrapper for Bursa Municipality Open Data Portal
Markov Model for Bursty Behavior in Streams
'I'm a Celebrity Get Me Out of Here' Data
Calculates Business Duration Between Two Dates
Simple Modelling Tools for Business Plans
Verification for Continually Updating Time Series Data
Download and Extract Data from the 'OzButterflies' Database
Bayesian Analysis of a Vector Autoregressive Model with
Stochastic Volatility and Time-Varying Parameters
Bayesian Inference of Vector Autoregressive and Error Correction
Models
Bayesian Vector Heterogeneous Autoregressive Modeling
The Stark-Parker algorithm for bounded-variable least squares
Backward Procedure for Change-Point Detection
Describe Image Patterns in Natural Structures
Bandwidth Selectors for Local Linear Quantile Regression
Baumgartner Weiss Schindler Test of Equal Distributions
Statistics About Bytes Contained in a File as a Circle Plot
Bivariate Zero-Inflated Negative Binomial Model Estimator
Extended Inference for Lasso and Elastic-Net Regularized Cox and
Generalized Linear Models
Dataset of Regional COVID-19 Deaths per 100,000 Pop (NUTS)
Methods for Detecting Safety Signals in Clinical Trials Using
Body-Systems (System Organ Classes)
Compare Two Classifications or Clustering Solutions of Varying
Structure
Inferring Large-Scale Gene Networks with C3NET
C5.0 Decision Trees and Rule-Based Models
Simple, Multiple and Joint Correspondence Analysis
Project Specific Workspace Organization Templates
Bootstrap Confidence Regions for Simple and Multiple
Correspondence Analysis
Conjunctive Analysis of Case Configurations
Classification Accuracy and Consistency under Item Response
Theory
Conditional Density Estimation Network Construction and
Evaluation
A Package to Perform Covariate Augmented Dickey-Fuller Unit Root
Tests
CAESAR: a Cross-Technology and Cross-Resolution Framework for
Spatial Omics Annotation
Simulation of Plasma Caffeine Concentrations by Using Population
Pharmacokinetic Model
Conditional Akaike Information Criterion for 'lme4' and 'nlme'
Graphical Aid in Correspondence Analysis Interpretation and
Significance Testings
R Graphics Device using Cairo Graphics Library for Creating
High-Quality Bitmap (PNG, JPEG, TIFF), Vector (PDF, SVG,
PostScript) and Display (X11 and Win32) Output
Comparison of Algorithms with Iterative Sample Size Estimation
Calculations for All Common Subsequences
Comparative Analysis with Annotation-Based Genomic Components
Efficient Neighborhood Basal Area Metrics for Trees
Bindings to the Calcite Design System 'JavaScript' Component
Library
Calculate Pesticide Risk Metric (PRM) Values from Multiple
Pesticides...Calc Them All
High Dimensional Numerical and Symbolic Calculus
Simple Wrapper for Computationally Expensive Functions
Create, Read, Write, and Work with 'iCalendar' Files, Calendars
and Scheduling Data
Ready to Print Monthly and Yearly Calendars Made with 'ggplot2'
'calendR' Fork with Additional Features (Backwards Compatible)
Multiple Imputation Using MICE and Random Forest
Calibration Plots for the Transition Probabilities from
Multistate Models
Automated Parameter Estimation for Complex Models
Calibration of Scatterplot and Biplot Axes
Calibration for Computer Experiments with Binary Responses
Weighting and Estimation for Panel Data with Non-Response
Bayesian Calibration of Complex Computer Codes
Mapping ML Scores to Calibrated Predictions
Assesses the Quality of Estimates Made by Complex Sample Designs
Computes Statistics from Discrimination Experimental Data
Easily Compile and Call Inline 'C' Functions
Recording Synchronisation, Call Detection and Assignment, Audio
Analysis
Improved Allele-Specific Copy Number of SNP Microarrays for
Downstream Segmentation
Canonical Associative Learning Models and their Representations
Causal Meta-Analysis for Aggregated Data
'CamelUp' Board Game as a Teaching Aid for Introductory
Statistics
Datasets from "Microeconometrics: Methods and Applications" by
Cameron and Trivedi
Connect to Campaign Manager via the 'Windsor.ai' API
Generic PK/PD Simulation Platform Campsis
Read and Manipulate Camera Trap Data Packages
Camera Trap Data Management and Analysis Framework
Maps of the Political and Administrative Divisions of Canada
Effortlessly Create Stunning Canadian Maps
Categorical Analysis of Neo- And Paleo-Endemism
Access, Retrieve, and Work with Canadian Census Data and
Geography
Publication Quality Phylogenetic Tree Plots
Classification of Cancer Using Administrative Data
Visualizing Generalized Canonical Discriminant and Canonical
Correlation Analysis
Comprehensive Groups of Experiments Analysis for Numerous
Environments
Batch Correction of Single Cell Transcriptome Data
Extra Canonical Link Family Objects for Generalized Linear
Models
Accessing Statistics Canada Data Table and Vectors
Visualization Package for CanvasXpress in R
Official Administrative Map of the Azores (CAOP 2024)
Comparative Analyses of Phylogenetics and Evolution in R
Data on Scholarships in CAPES International Mobility Programs
Capital Budgeting Analysis, Annuity Loan Calculations and
Amortization Schedules
Compute and Visualize CAPL-2 Scores and Interpretations
Correspondence Analysis with Geometric Frequency Interpretation
A Virtual Patient Simulator in the Context of Calcium and
Phosphate Homeostasis
Comprehensive Reproducibility Framework for R and Bioinformatics
Analysis
Capushe, Data-Driven Slope Estimation and Dimension Jump
Fast and Memory Efficient Fitting of Linear Models with
High-Dimensional Fixed Effects
Covariate-Adjusted Response-Adaptive Designs for Clinical Trials
Automatic Calibration by Evolutionary Multi Objective Algorithm
Covariate-Adaptive Randomization for Clinical Trials
Spatial Generalised Linear Mixed Models for Areal Unit Data
Data Used in the Vignettes Accompanying the CARBayes and
CARBayesST Packages
Spatio-Temporal Generalised Linear Mixed Models for Areal Unit
Data
Access Carbon Market Data from Emissions Trading Systems and
Voluntary Registries
Calibration and Summarisation of Radiocarbon Dates
Estimation of the Number of Fatalities from Carcass Searches
Cardiovascular Applications in Research Data
Lightweight Modern & Responsive Card Component for 'shiny'
Generate SVG Information Cards with Embedded Fonts and Badges
Companion to Applied Regression Data Sets
Automated Cardiac Data Processing via ACF, GA & Tracking Index
Identification of Cardinal Dates in Ecological Time Series
Nonlinear Modeling of R-R Interval Dynamics
A Comprehensive Collection of Cardiovascular and Heart Disease
Datasets
High-Dimensional Regression and CAR Score Variable Selection
Carbon-Related Assessment of Silvicultural Concepts
Government of Canada Vehicle Recalls Database API Wrapper
Calculate the Care Density or Fragmented Care Density Given a
Patient-Sharing Network
Procedures for Computing Indices of Careless Responding
Correspondence Analysis Plot and Associations Visualisation
Conformal Time Series Forecasting Using State of Art Machine
Learning Algorithms
Build Species Distribution Modeling using 'caret'
Continuous-Time Fractionally Integrated ARMA Process for
Irregularly Spaced Long-Memory Time Series Data
Estimation of Caribou Abundance Based on Radio Telemetry Data
Functions for Statistics Classes at Carleton College
Carlson Elliptic Integrals and Incomplete Elliptic Integrals
Covariate-Adjusted Adaptive Randomization via
Mahalanobis-Distance
Continuous Time Markov Rate Modeling for Reliability Analysis
Continuous Biomarker Evaluation with Adjustment of Covariates
A Collection of Database, Data Structure, Visualization, and
Utility Functions for R
Build Common Tables of Summary Statistics for Reports
Predicting Categorical and Continuous Outcomes Using One in Ten
Rule
Competitive Adaptive Reweighted Sampling (CARS) Algorithm
Correlation-Adjusted Regression Survival (CARS) Scores
Crafting Print-Ready Maps and Layered Visualizations
Simulation-Based Assessment of Covariate Adjustment in
Randomized Trials
Selection, Reverse-Engineering and Prediction in Cascade
Networks
Experimental Data of Cascade Experiments in Genomics
Covariate Assisted Spectral Clustering on Ratios of Eigenvectors
Casualty Actuarial Society Individual Claim Simulator
Fitting Flexible Smooth-in-Time Hazards and Risk Functions via
Logistic and Multinomial Regression
Identify Similar Cases for Qualitative Case Studies
Stratified Evaluation of Subgroup Classification Accuracy
Datasets from Computer Age Statistical Inference
Comparing Automated Subject Indexing Methods in R
Finds Missing Links and Metric Confidence Intervals in
Ecological Bipartite Networks
Compute Scagnostics on Pairs of Numeric Variables in a Data Set
'caret' Applications for Spatial-Temporal Models
Estimate Sample Size for Population Genomic Studies
Analysis and Imputation of Categorical-Variable Datasets with
Missing Values
Handling an Inconsistently Coded Categorical Variable in a
Longitudinal Dataset
Analysis of Check-All-that-Apply (CATA) Data
Explore and Code Responses to Check-All-that-Apply Survey Items
Access the 'Spark Catalog' API via 'sparklyr'
Tools for Applying Catalytic Priors in Statistical Modeling
Interface to the API 'Sede Electronica Del Catastro'
Covariate-Adjusted Tensor Classification in High-Dimensions
Test, Identify, Select and Mutate Categorical or Continuous
Values
Categorical Data Analysis Program Package
Datasets for Categorical Data Analysis by Agresti
Fishery Stock Assessment by Catch Dynamics Models
Community Assembly by Traits: Individuals and Beyond
Simulate IRT-Based Computerized Adaptive Tests
Formal Psychological Models of Categorization and Learning
Heatmap for Categorical Data using 'plotly'
Compensation Analysis Tool for Instructor Overload Pay
Tools: Moving Window Statistics, GIF, Base64, ROC AUC, etc
Optimal Categorisation of Continuous Variables in Prediction
Models
Generation of IRT Response Patterns under Computerized Adaptive
Testing
Solution Paths for Linear and Logistic Regression Models with
Categorical Predictors, with SCOPE Penalty
Post-Estimation Functions for Generalized Linear Mixed Models
Create Catseye Plots Illustrating the Normal Distribution of the
Means
Binary and Categorical Image Similarity Index
Computerized Adaptive Testing for Survey Research
Computation of the p-Value for the Exact Conditional
Cochran-Armitage Trend Test
Visualizing Causal Assignment Trees for CSDiD and DR-DDD Designs
Robust Principal Component Analysis Using the Cauchy
Distribution
Trait Evolution on Phylogenies Using the Cauchy Process
Fast, Easy, and Visual Bayesian Inference
Nonparametric and Cox-Based Estimation of Average Treatment
Effects in Competing Risks
Example Data Sets for Causal Inference Textbooks
Decision-Theoretic Causal Diagnostics via Le Cam Deficiency
Tools for Causal Discovery on Observational Data
Estimating Causal Dose Response Functions
Deriving Expressions of Joint Interventional Distributions and
Transport Formulas in Causal Models
Matching on Generalized Propensity Scores with Continuous
Exposures
Inferring Causal Effects using Bayesian Structural Time-Series
Models
MBSTS Models for Causal Inference and Forecasting
Bayesian Nonparametric Conditional Density Modeling in Causal
Inference and Clustering with a Heavy-Tail Extension
Causal Inference Modeling for Estimation of Causal Effects
Directed Causal Network Enumeration and Simulation
An Interface to Specify Causal Graphs and Compute Bounds on
Causal Effects
Optimal Transport Weights for Causal Inference
Causal Effect for Population Attributable Fractions (PAF)
Causal Inference for Qualitative Outcomes
Make, Update, and Query Binary Causal Models
Selection Bias Approach to Sensitivity Analysis for Causal
Effects
Semiparametric Least Squares Inference for Causal Effects
Nonlinear Causal Dose-Response Estimation via Splines
Compute the Causal Win Ratio Using Nearest Neighbor Matching
Calculate Correlations and Estimate Causality
Perform Causal Sensitivity Analyses Using Various Statistical
Methods
Multiple Granger Causality Tests for Time Series and Panel Data
Control Charts with Guaranteed In-Control Performance and
Cautious Parameters Learning
Cluster Analysis via Random Partition Distributions
Cayley Graph Analysis for Permutation Puzzles
CRISPR Pooled Screen Analysis using Beta-Binomial Test
Stochastic 3D Structure Model for Binder-Conductive Additive
Phase
Classification -- Bayesian Adaptive Smoothing Splines
Continuous Analog of a Beta-Binomial Distribution
Compare Baseline Characteristics Between Groups
Design and Analyze Choice-Based Conjoint Experiments
Continuous Analog of a Binomial Distribution
Browse and Query Clinical and Genomic Data from cBioPortal
Causal Discovery under a Confounder Blanket
Contrast-Based Bayesian Network Meta Analysis
Statistics Netherlands (CBS) Open Data API Client
Fits Cubic Bezier Spline Functions to Intertemporal and Risky
Choice Data
Hedonic and Multilateral Index Methods for Real Estate Price
Statistics
Caught by the Fuzz! - A Minimalistic Fuzz-Test Runner
(Robust) Canonical Correlation Analysis via Projection Pursuit
Concordance Correlation Coefficient for Repeated (and
Non-Repeated) Measures
The Cauchy-Cacoullos (Discrete Cauchy) Distribution
Utilities for Interacting with the 'CTX' APIs
Cox Model for Case-Cohort Data with Stratified
Subcohort-Selection
Transforming and Harmonizing CCHS Variables
Computational Test for Conditional Independence
Cross-Covariance Isolate Detect: a New Change-Point Method for
Estimating Dynamic Functional Connectivity
Convex Clustering Methods and Clustering Indexes
Minimization of the Convex Clustering Loss Function
Implementation of Case-Control Optimal Matching
Estimation of Mean Costs in Censored Data
Significance Tests for Canonical Correlation Analysis (CCA)
Removes the Cell-Cycle Effect from Single-Cell RNA-Sequencing
Data
Canonical Correlations and Tests of Independence
Tools for the Continuous Convolution Trick in Nonparametric
Estimation
Perform Weighted Linear Regression for Calibration Curve
Sex- and Age-Standardized Metrics from the Centers for Disease
and Control (CDC) Growth Charts
Cognitive Diagnostic Computerized Adaptive Testing
Conditional Distance Correlation Based Feature Screening and
Conditional Independence Inference
Interface to the California Data Exchange Center (CDEC)
Centroid Decision Forest for High-Dimensional Classification
Confidence Interval Estimation via CDF Inversion
Quantile Regression for Random Variables on the Unit Interval
Downscaling and Bias Correction via Non-Parametric CDF-Transform
Causal Decomposition of Group Disparities
Hidden Markov Models for Multivariate Panel Data
Words and Gestures to Words and Sentences Score Conversion
Cause-Deleted Life Expectancy Improvement Procedure
Simulation of Cropland Data Layer Products from the USDA
Tools to Download and Work with USDA Cropscape Data
Useful Tools for Cognitive Diagnosis Modeling
Correlated Destructive Negative Binomial Cure Rate Model
Constrained Sampling in Paid Research Studies
'Copernicus Data Space Ecosystem' API Wrapper
Simulating Climate Data for Research and Modelling
Cuddy-Della Valle Index for Capturing the Instability in Time
Series Data
Extract Data from the Canadian Elite Basketball League
CRISPR Screen and Gene Expression Differential Analysis
Capability-Ecological Developmental Model (CEDM) Analysis
CEEMDAN Decomposition Based Hybrid Machine Learning Models
Collection of Common Astronomical Conversion Routines and
Functions
Cell DiffErential Expression by Pooling ('CellDEEP')
Consistent Perturbation of Statistical Frequency- And Magnitude
Tables
Finds RNASeq Source Tissues Using In Situ Hybridisation Data
Translate Spreadsheet Cell Ranges to Rows and Columns
Functions to Fit Cell Volume Distributions and Thereby Estimate
Cell Growth Rates and Division Times
Broken Adaptive Ridge AFT Model with Censored Data
Consistent Estimation of the Number of Communities via
Regularized Network Embedding
Estimating Time-Dependent ROC Curve and AUC for Censored Data
Finite Mixture of Multivariate Censored/Missing Data
Base de Datos de Facil Acceso del Censo 2017 de Chile (2017
Chilean Census Easy Access Database)
Extraction and Analysis of 2022 Argentina Census Microdata from
REDATAM Databases
Download Data from Brazil's Population Census
Estimation of Censored AI/QUAI Demand System via Maximum
Likelihood Estimation (MLE)
Censored Linear Regression Models under Heavy‑tailed
Distributions
Explorer of Indonesian Population Pyramids from Harmonized and
Non-Harmonized Census Data
Non-Trivial Balance of Centrifuge Rotors
Datasets of the CEO (Centre d'Estudis d'Opinio) for Opinion
Polls in Catalonia
Cross-Entropy R Package for Optimization
Continuous Epidemiological Week Indexing for Time-Series
Analysis
Context Driven Exploratory Projection Pursuit
A Cepstral Model for Covariate-Dependent Time Series
Calculate Consumer Expenditure Survey (CE) Annual Estimates
Censored Quantile Regression & Monotonicity-Respecting Restoring
Download and Tidy Australian Clean Energy Regulator Data
Process Based Epidemiological Model for Cercospora Leaf Spot of
Sugar Beet
Causal Effect Random Forest of Interaction Trees
Outlier Detection Using the Iterated RMCD Method of Cerioli
(2010)
Identification and Analysis of ceRNA Regulation
Data Visualization Utilities for 'pyDarwin' Machine Learning
Pharmacometric Model Development
Generate Diagnostics for Pharmacometric Models Using 'shiny'
Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine
Easily Install Pharmacometric Packages and Shiny Applications
Developed by Certara
Interface for 'pyDarwin' Machine Learning Pharmacometric Model
Development
Pharmacometric Model Building Using 'shiny'
Execute Pharmacometric Models Using 'shiny'
Generate Visual Predictive Checks (VPC) Using 'shiny'
Enhances 'xpose' Diagnostics for Pharmacometric Models from
'Certara.RsNLME' and Phoenix NLME
Colony Formation Assay: Taking into Account Cellular Cooperation
Access College Football Play by Play Data
Cause-Specific Framework for Competing-Risk Analysis
Counterfactual Decomposition: MC Integration of the G-Formula
Simple Similarity for User-Based Collaborative Filtering Systems
Canadian Forest Fire Danger Rating System
Generate Citation File Format ('cff') Metadata for R Packages
Identification of Counterfactual Queries in Causal Models
Collaborative Filtering Models for Recommendation Systems
Cystic Fibrosis Survival Prediction Model Based on Stanojevic
Model
CFO-Type Designs in Phase I/II Clinical Trials
Conditional Forecasting and Scenario Analysis Using VAR Models
Estimate Disease Severity and Case Ascertainment
Using CF-Compliant Calendars with Climate Projection Data
Compare Groups, Analytically and Graphically
Constrained Groupwise Additive Index Models
Calculate AUC-type measure when gold standard is continuous and
the corresponding optimal linear combination of variables with
respect to it
Conditional Graphical LASSO for Gaussian Graphical Models with
Censored and Missing Values
Clean and Analyze Continuous Glucose Monitor Data
Continuous Glucose Monitoring Data Analyzer
Advanced Continuous Glucose Monitoring Analysis with
High-Performance C++ Backend
Missingness Benchmark for Continuous Glucose Monitoring Data
Analyzing Glucose and Glucose Variability
Compound Growth Rate for Capturing the Growth Rate Over the
Period
Interactive 3D Visualization of Large Cayley Graphs via Vulkan
Chain Binomial Models for Analysis of Infectious Disease Data
Statistical Methods and Models for Claims Reserving in General
Insurance
Automatic Colors for Multi-Dimensional Data
Geometrically Inspired Multivariate Changepoint Detection
Package to Calculate the Influence of the Data on a Changepoint
Segmentation
Methods for Nonparametric Changepoint Detection
Changepoint Detection via Modified Genetic Algorithm
A Collection of Change-Point Detection Methods
Change-Points Detections for Changes in Variance
Change Point Estimation for Clustered Signals
Change Point Tests for Joint Distributions and Copulas
Markov Model for Online Multi-Channel Attribution
Shiny Web Application for the Multichannel Attribution Problem
Loglikelihood Adjustments for Econometric Models
Estimation of Gas Properties from the Lennard-Jones Potential
CHAP-GWAS: Leveraging Chromosomal Haplotypes to Improve
Genome-Wide Association Studies
Implement Descriptive Studies Using the Common Data Model
Peak Detection and Fire History from Sediment-Charcoal Records
Reproducible Color Characterization of Digital Images for
Biological Studies
Wrapper Functions Around 'Charles Schwab Individual Trader API'
Simplified Language for Plots and Charts
Adaptive Multi-Wave Sampling for Efficient Chart Validation
Chat-Based Interactive Artificial Intelligence for R
A Flexible Interface for 'LLM' API Interactions
A Tool for Rating Text/Image/Audio Stimuli via 'LLMs'
Interact with Large Language Models in 'RStudio'
Simple Functions to Save Time and Memory
Check the Basic Validity of a (Function) Argument
'CLI' Messages for Checkmate Assertions and Checks
Check-Fields and Check-Boxes for 'rmarkdown'
Checks 'R' Configuration Set Up Correctly Before Class
Checks if a Number is Valid Using the Luhn Algorithm
Intuitive Unit Testing Tools for Data Manipulation
Analysis and Visualisation of Ecological Communities
Interactively Explore Local Explanations with the Radial Tour
Tools for Working with Data During Statistical Analysis
High Performance Tables Using 'Cheetah Grid'
Collection of 3 Chemical Databases from Public Sources
Chemical Metrics for Microbial Communities
Calibration Functions for Analytical Chemistry
Analysis of Chemical Degradation Kinetic Data
Causal Inference with High-Dimensional Error-Prone Covariates
and Misclassified Treatments
Analysing Chemodiversity of Phytochemical Data
Multivariate Statistical Analysis in Chemometrics
Exploratory Chemometrics for 2D Spectroscopy
Functions Supporting Packages ChemoSpec and ChemoSpec2D
Multiple Testing Methods for Exploratory Research
Read, Write, Create and Explore Chess Games
Create Network Connections Based on Chess Moves
FIDE Chess Players Ratings for 2015 and 2020
Change-in-Estimate Approach to Assess Confounding Effects
Estimate the Chest Volume with Markers Data
Standard TLGs for Clinical Trials Reporting
Word and Phrase Frequency Tools for CHILDES
Access and Harmonize Childfree Demographic Data
Data and Methods Around Reference Values in Pediatrics
Access Chilean Data via APIs and Curated Datasets
Mapas de las Divisiones Politicas y Administrativas de Chile
(Maps of the Political and Administrative Divisions of Chile)
Processing Chill and Heat Models for Temperate Fruit Trees
Statistical Methods for Phenology Analysis in Temperate Fruit
Trees
Access Chinese Data via Public APIs and Curated Datasets
Convenient Access to Chicago Open Data API Endpoints
Toolkit of Helper Functions to Pre-Process Amplification Data
A Post Hoc Analysis for Pearson's Chi-Squared Test for Count
Data
Chi-Square and G-Square Test of Independence, Power and Residual
Analysis, Measures of Categorical Association
Convert Antipsychotic Doses to Chlorpromazine Equivalents
Estimation and Hypothesis Testing for Threshold Regression
Thermodynamic Calculations and Diagrams for Geochemistry
Amend, Augment and Aid Analysis of John Snow's Cholera Map
Cholesky Decomposition of the Wishart Distribution
A Comprehensive Hit or Miss Probabilistic Entity Resolution
Model
Selecting General Circulation Models for Species Distribution
Modeling
Choose the Number of Principal Components via Recistruction
Error
Spatial Parallel Computing by Hierarchical Data Partitioning
Permutation Test for Some Positive and Many Zero Responses
Changepoint-Aware Ensemble for Probabilistic Modeling
A Collection of Large Language Model Assistants
Contains an Administrative-Level-1 Map of the World
Contains Maps Used by the 'choroplethr' Package
Generation of Different Animated Christmas Cards
Interface to Chromosome Counts Database API
Interactive Genomic Visualization of Biological Data
Chronological Objects which Can Handle Dates and Times
Chunkwise Text-File Processing for 'dplyr'
Functions for Conditional Hypergeometric Distributions
Learn and Apply Directed Acyclic Graphs for Causal Inference
Cluster Independent Algorithm for Rare Cell Types Identification
Calibration of Confidence Intervals to Support Intervals
Causal Inference with Continuous (Multiple Time Point)
Interventions
International Classification of Diseases 'ICD-10'/'ICD-11' for
Chile
Estimating and Testing Direct Effects in Directed Acyclic Graphs
using Estimating Equations
Estimate the Confidence Intervals for Predictive Values
Reachability-Based Primitives for Graphical Causal Inference
Visualization and Polytomous Modeling of Survival and Competing
Risks
Toolbox for Connectivity Informatics Technology Initiative
('CIFTI') Files
Tools for Reading, Writing, Viewing and Manipulating CIFTI Files
A Method to Identify Single CpG Sites for Classification and
Deconvolution
Causal Inference for Multiple Treatments with a Binary Outcome
A Computational Pipeline for Bulk 'ATAC-Seq' Profiles
Ready-to-Use Curated Gene Sets for 'cinaR'
Classification International Normalized of Education
Deciphering Central Informative Nodes in Network Analysis
Computationally-Efficient Confidence Intervals for Mean Shift
from Permutation Methods
Encryption and Decryption with Text Ciphers
Classical Cryptography Methods for Words and Phrases
Confidence Interval Post-Selection of Variable
Centered Isotonic Regression and Dose-Response Utilities
Sleep and Circadian Metrics Estimation from Actigraphy Data
Construct Cohort Inclusion and Restriction Criteria Expressions
A Small Package for Drawing Various Combinations of Circles
Algorithm for Computation of the Intersection Areas of N Circles
Visualize Proportions with Circles in a Plot
Curve Text Elements in 'Shiny' Using 'CircleType.js'
Using 'ggplot2' Feature to Write Readable R Code for Circular
Visualization
Clustering and Simulation of Spherical Cauchy and PKBD Models
Maximum Likelihood Analysis of Circular Data
Statistical Analysis of Circular Data using Nonnegative
Trigonometric Sums (NNTS) Models
Multivariate Circular Data using MNNTS Models
Circular Data using Symmetric NNTS Models
Detection of Outliers in Circular-Circular Regression
Circular Statistics, from "Topics in Circular Statistics" (2001)
'Circuitscape' and 'Omniscape' Connectivity Analysis via 'Julia'
Recent Methods for Kernel Density Estimation of Circular Data
Fast Silhouette on Circular or Linear Data Clusters
Analysis and Visualization of Circular Data
Constrained Iteratively Reweighted Least Squares
Covariates, Interaction, and Selection for DGLM
A Correlation Indicator Based on Spatial Patterns
Perform Forward and Backwards Chasing in Evidence Syntheses
Conditional Independence of Missingness Test
Clinical Trials with Intercurrent Events Simulator
Estimation of Cell Infiltration Based on Cell Crosstalk
Confidence or Prediction Intervals, Quantiles, and Probabilities
for Statistical Models
Customer Intelligence Tool for Rapid Understandable Segmentation
Controlled Interrupted Time Series Analysis and Visualization
Confidence Intervals Utilizing Uncertain Prior Information
Kabaila and Giri (2009) Confidence Interval
Copula-Based Joint Analysis of Multiple Phenotypes
R Client for 'Customer Journey Analytics' ('CJA') API
Heterogeneous Effects Analysis of Conjoint Experiments
Canonical Joint and Individual Variation Explained (CJIVE)
Client for the Comprehensive Knowledge Archive Network ('CKAN')
API
Composite Kernel Association Test for Pharmacogenetics Studies
Composite Kernel Machine Regression Based on Likelihood Ratio
Test
Optimal, Fast, and Reproducible Univariate Clustering
Measuring Morphological Diversity and Evolutionary Tempo
C++ Implementations of Phylogenetic Cladogenesis Calculations
Classical Age-Depth Modelling of Cores from Deposits
Time Series Modeling for Climate Change Proxies
Detecting Class Overlapping Regions in Multidimensional Data
Interior Point Conic Optimization Solver
Simulation-Based Inference for Regression Models
Distribution-Free Tests of Non-Nested Models
Classes and Methods for "Class Comparison" Problems on
Microarrays
Classes and Methods for "Class Discovery" with Microarrays or
Proteomics
Construct Graphs of S4 Class Hierarchies
Automatically Builds 12 Classification Models (6 Individual and
6 Ensembles of Models) from Classification Data
Generates a Visualization of Classifier Performance as a Grid of
Diagnostic Plots
Explore Classification Models in High Dimensions
Exact Confidence Limits after a Sequential Trial
Clay Stacking Rings Found in Miletus (Data)
Create Compact Letter Display (CLD) for Statistical Comparisons
To Inspect and Manipulate Data; and to Keep Track of This
Process
Clean and Standardize Epidemiological Data
Automated Doublet Detection and Classification for Cytometry
Data
Cleaning Geometries from Spatial Objects
Cleaning Validation Functions for Pharmaceutical Cleaning
Process
A Tidy Data Model for Natural Language Processing
Clean Class-Less 'R Markdown' HTML Documents
Testbench for Univariate Time Series Cleaning
Clustering and Link Prediction Evaluation in R
Helpers for Developing Command Line Interfaces
The LIC for Distributed Cosine Regression Analysis
Implement 'tableGrob' Object as a Clickable Image Map
Web Data Analysis by Bayesian Mixture of Markov Models
Model-Based Clustering of Categorical Sequences
A Simple HTTP Database Interface to 'ClickHouse'
Semi-Automatic Preprocessing of Messy Data with Change Tracking
for Dataset Cleaning
Analyzes Clickstreams Based on Markov Chains
Monthly Climate Data for Germany, Usable for Heating and Cooling
Calculations
Execute Command Line Programs Interactively
Complex-Valued Wavelet Lifting Estimators of the Hurst Exponent
for Irregularly Sampled Time Series
Interface to Download Meteorological (and Hydrological) Datasets
Statistical Tools for Modelling Climate-Health Impacts
Unified Climate Indices for Temperature, Precipitation, and
Drought
Estimating Climate Stability from Climate Model Data
Climate Tools (Series Homogenization and Derived Products)
Climate Variability Indices for Ecological Modelling
Climate Classification According to Several Indices
Generating Rainfall Rasters from IMD NetCDF Data
Constrained L1-Minimization for Inverse (Covariance) Matrix
Estimation
Climate Modeling with Point Data from Climate Stations
Set of Tools to Compute Various Climate Indices
Dataset Comparison with 'CDISC' Validation for Clinical Trial
Data
Simulation and Analysis Tools for Clinical Dose Response
Modeling
Clinical Trial Design and Data Analysis Functions
Algorithmic Fairness Assessment for Clinical Prediction Models
Interface with the 'ClinicalOmicsDB' API, Allowing for Easy Data
Downloading and Importing
A Toolbox for Clinical Significance Analyses in Intervention
Studies
Summary Measures for Clinical Trials with Survival Outcomes
Recalibration Methods for Improved Clinical Utility of Risk
Scores
Clinical Table Styling Tools and Utilities
Hemodynamic Calculations from Clinical Monitoring
Clinical Natural Language Processing using 'spaCy', 'scispaCy',
and 'medspaCy'
Predicting and Simulating Clinical Trial with Time-to-Event
Endpoint
Connect and Work with Clinical Trials Data Sources
General Utility Functions for Analysis of Clinical Data
Calculating Likelihoods by Pedigree Paring
Read and Write from the System Clipboard
Constrained Inference for Linear Mixed Effects Models
Fitting Exact Conditional Logistic Regression with Lasso and
Elastic Net Penalties
Estimate Growth Rates from Phylogenetic Trees
Seeking and Finding Clones in Copy Number and Sequencing Data
Fetch and Explore the Cornell Lab of Ornithology Open Tree of
Life Avian Phylogeny
Composite Likelihood Inference and Diagnostics for Replicated
Spatial Ordinal Data
Integrate Single-Arm Observational Data in Network Meta Analysis
Streamlined Interface to Interact with Cloud Storage Platforms
Interface to the Google Cloud Machine Learning Platform
Compute Price of Production and Labor Values
Curve Linear Regression via Dimension Reduction
Diagnostic Tools for Logistic and Conditional Logistic
Regression
Clinical and Laboratory Standards Institute (CLSI) EP15-A3
Calculations
Central Limit Theorem Experiments (Theoretical and Simulation)
Classification Using Binary Procrustes Rotation
Cluster-Robust (Sandwich) Variance Estimators with Small-Sample
Corrections
Multidimensional Cluster Generation Using Support Lines
Bootstrap a Clustering Solution to Establish the Stability of
the Clusters
A Procedure for Cluster Evolution Analytics
Simultaneous Semi-Parametric Estimation of Clustering and
Regression
ROC Analysis in Three-Class Classification Problems for
Clustered Data
Simultaneous Detection of Clusters and Cluster-Specific Genes in
High-Throughput Transcriptome Data
Statistical Methods for Analyzing Clustered Matched Pair Data
Identifying Similar T Cell Receptor Hyper-Variable Sequences
with 'ClusTCR2'
Clusters of Effects Curves in Quantile Regression Models
"Finding Groups in Data": Cluster Analysis Extended Rousseeuw et
al.
Performs Tests for Cluster Tendency of a Data Set
Analyze Clustered Data using the Cluster Bootstrap
Location and Visualization of Clustered Somatic Mutations
Random Cluster Generation (with Specified Degree of Separation)
Sparse Gaussian Graphical Modeling with Variable Clustering
Optimal Distance-Based Clustering for Multidimensional Data with
Sequential Constraint
Cluster Analysis with Missing Values by Multiple Imputation
Unbiased Single-Cell Transcriptomic Data Cell Type
Identification
Evaluate Function Calls on HPC Schedulers (SLURM, LSF, SGE, GCS,
OCS, PBS, Torque)
Integrative Clustering for Heterogeneous Biomedical Datasets
Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids
and Affinity Propagation Clustering
Reproducibility of Gene Expression Clusters
Calculate Cluster-Robust p-Values and Confidence Intervals
Searching for Optimal Clustering Procedure for a Data Set
Assessment of Stability of Individual Objects or Clusters in
Partitioning Solutions
Assessment of Cluster Stability by Randomized Maps
Fitting Latent Class Vector-Autoregressive (VAR) Models
Hierarchical Clustering with Spatial Constraints
K-Means Clustering with Build-in Missing Data Imputation
Learn Clustering Techniques Through Examples and Code
k-Prototypes Clustering for Mixed Variable-Type Data
Cluster Ordinal Data via Proportional Odds or Ordered Stereotype
Prediction and Clustering on the Torus by Conformal Prediction
Monitor Changes in Cluster Solutions of Dynamic Datasets
Methods for Joint Dimension Reduction and Clustering
Visualise Clusterings at Different Resolutions
Interactive Document for Working with Cluster Analysis
Spatio-Temporal Finite Mixture Model using 'TMB'
Clustering of Variables Around Latent Variables
Variable Selection for Gaussian Model-Based Clustering
Tools for Customer Lifetime Value Estimation
Covariance Matrix Adapting Evolutionary Strategy
Covariance Matrix Adaptation Evolution Strategy
Calculate Distance Measures for DataFrames
Process and Visualise Concept Mapping Data
Commercial Modular Aero-Propulsion System Simulation Data Set
Representation Tool For Output Of Connectivity Map (CMap)
Analysis
Implementation of the Conic Multivariate Adaptive Regression
Splines in R
Matching Algorithms for Causal Inference with Clustered Data
Conditional Mixture Modeling and Model-Based Clustering
Framework for Building Interfaces to Shell Commands
Collective Matrix Factorization for Recommender Systems
Calibrated Model Fusion Approach to Combine Surrogate Markers
Constrained Mixture of Generalized Normal Distributions
Access, Retrieve, and Work with CMHC Data
Mental Health Status, Substance Use Status and their Concurrent
Status in North American Healthcare Administrative Databases
Visualization and Analysis of Coupled Model Intercomparison
Project, Phase-6 (CMIP6) Hydroclimatic Data
Computational Methods for Numerical Analysis
Direct Parametric Inference for the Cumulative Incidence
Function in Competing Risks
Subdistribution Analysis of Competing Risks
Use IPW to Estimate Treatment Effect under Competing Risks
Analysis of Competing Risks Using Quantile Regressions
R Implementation of Congruent Matching Profile Segments Method
Analysis of Cardiac Magnetic Resonance Images
Interactive Document for Working with Confusion Matrix
Statistical Methods for Composite Material Data
More Statistical Methods for Composite Material Data
Create (Advanced) Coupled Matrix and Tensor Factorization Models
Wrapper for the Computational Morphometry Toolkit ('CMTK')
Library
The Complex Multivariate Gaussian Distribution
Causal Modeling with Coincidence Analysis
Common Network Asset Indices Methodology (CNAIM)
Optimizing Consistency and Coverage in Configurational Causal
Modeling
Canonical Non-Symmetrical Correspondence Analysis in R
Access and Analysis of Brazilian CNEFE Address Data
Get Basic Information from Chinese ID Number
Complex-Valued Wavelet Lifting for Signal Denoising
Complex-Valued Wavelet Lifting for Univariate and Bivariate Time
Series Analysis
Pre-Process DNA Copy Number (CN) Data for Detection of CN Events
CNV-Profile Regression for Copy Number Variants Association
Analysis with Penalized Regression
Dirichlet Multinomial Modeling of Relative Abundance Data
A Versatile Toolkit for Copy Number Variation Relationship Data
Analysis and Visualization
Bayesian "Now-Cast" Estimation of Event Probabilities in
Multi-Party Democracies
High-Dimensional Covariate-Augmented Overdispersed Poisson
Factor Model
Calculation of the Fractal Dimension of a Coastline
Conditional Method Agreement Trees (COAT)
Using Multiple Continuous Biomarkers for Patient Enrichment in
Two-Stage Clinical Designs
Biclustering via Latent Block Model Adapted to Overdispersed
Count Data
Cobin and Micobin Regression Models for Continuous Proportional
Data
Constrained B-Splines (Sparse Matrix Based)
Convolution-Closed Models for Count Time Series
Covariate-Based Covariance Functions for Nonstationary Spatial
Modeling
Extract, Format, and Print Statistical Output
CoCoSo - Combined Compromise Solution Method for MCDA
Dependence Condition Test Using Ranked Correlation Coefficients
Statistical Comparisons of Two or more Alpha Coefficients
Output Analysis and Diagnostics for MCMC
A Basic Set of Functions for Compositional Data Analysis
Meta-Package for Compositional Data Analysis
Compositional Data Analysis for Microbiome Studies
Learning Sparse Log-Ratios for Compositional Data
Transformation-Free Linear Regression for Compositional Outcomes
and Predictors
Compositional Models to Longitudinal Microbiome Data
Compositional Data Linear Models with Composition Redistribution
Automated C Code Generation for 'deSolve', 'bvpSolve'
Automatic Codebooks from Metadata Encoded in Dataset Attributes
Counting Codes in a Text and Preparing Data for Analysis
Analysis of R Code for Reproducible Research and Code
Comprehension
Identify Relevant Clinical Codes and Evaluate Their Use
Generate 'CodeMeta' Metadata for R Packages
Generation of Code Names for Organizations, People, Projects,
and Whatever Else
Deterministic Categorization of Items Based on External Code
Data
Find the Location of an R Package's Code
The CODEX (Comorbidity, Obstruction, Dyspnea, and Previous
Severe Exacerbations) Index: Short and Medium-Term Prognosis in
Patients Hospitalized for Chronic Obstructive Pulmonary Disease
(COPD) Exacerbations
Seq2Seq Encoder-Decoder Model for Time-Feature Analysis Based on
Tensorflow
Alternative Factor Coding Matrices for Linear Model Formulae
Meta Analysis of Factor Analysis Based on CO-Occurrence Matrices
Robust Coefficient Alpha and Omega with Missing and Non-Normal
Data
Spatially-Aware Cell Clustering Algorithm with Cluster
Significant Assessment
Chronological Ordering for Fossils and Environmental Events
Cognitive Testing Using Item Response Theory
Collaborative Graphical Lasso - Multi-Omics Network
Reconstruction
Compute Glyph Centers of Gravity from Image Data
Cognitive Mapping Tools Based on Coding of Textual Sources
Authentication for 'Shiny' Apps with 'Amazon Cognito'
Analysis and Visualization of Complex Networks
Assessing Complex Heterogeneity in Surrogacy
Summarise and Visualise Characteristics of Patients in the OMOP
CDM
Build and Manipulate Study Cohorts Using a Common Data Model
Enrichment Analysis of Clinically Relevant Concepts in Common
Data Model Cohort Data
Cohort Generation for the OMOP Common Data Model
Comparative Cohort Method with Large Scale Propensity and
Outcome Models
Simulation of Cohort Platform Trials for Combination Treatments
Estimate Survival from Common Data Model Cohorts
Sequence Symmetry Analysis Using the Observational Medical
Outcomes Partnership Common Data Model
Parametric and Nonparametric Copula-Based Imputation Methods
Conditional Inference Procedures in a Permutation Test Framework
Get 'Cryptocurrencies' Market Cap Prices from Coin Market Cap
Simultaneous Confidence Intervals for Multinomial Proportions
Composite Indicator Construction and Analysis
Unit Root Tests with Structural Breaks and Fully-Modified
Estimators
Comprehensive Cointegration Tests with Fourier and Panel Methods
Consistent Monitoring of Stationarity and Cointegrating
Relationships
Parameter Estimation and Inference in a Cointegrating Regression
Cointegration Tests with Structural Breaks in Small Samples
Convert Between Color Names and Hex Codes
Lightweight Column Drift Detection for Tabular Data
Interactive Collapsible Tree Diagrams using 'D3.js'
Functions Related to the Collatz/Syracuse/3n+1 Problem
Datasets from "Modelling Survival Data in Medical Research" by
Collett
Functions to Streamline Statistical Analysis and Reporting
Check for Namespace Collisions Across Packages and Functions on
CRAN
Visualization the Effects of Collinearity in Distributed Lag
Models and Other Linear Models
Collocation Inference for Dynamic Systems
Collapsed Latent Position Cluster Model for Social Networks
Colocalisation Tests of Two Genetic Traits
Multi-Context Colocalization Analysis for QTL and GWAS Studies
Proportional Testing for Colocalisation Analysis
Access Colombian Data via APIs and Curated Datasets
Download Colombian Demographic, Climate and Geospatial Data
Check Color Palettes for Problems with Color Vision Deficiency
Distance Metrics for Image Color Similarity
Fast Conversion of R Colors to Color Component Values and Native
Packed Integer Format
Extract Colors from Windows BMP, JPEG, PNG, TIFF, and SVG Format
Images
Intuitive Color and Palette Generation and Modification
Coloring Wildlife Distributions in Space-Time
Render Text in Color for Markdown/Quarto Documents
Colorize Old Images Using the 'DeOldify' Image Colorization API
Color Palettes using Colormaps Node Module
Basic S4 Classes and Methods for Mapping Between Numeric Values
and Colors
Color Palettes for EPL, MLB, NBA, NHL, and NFL Teams
Repel Visually Similar Colors for Colorblind Users in Various
Plots
A Toolbox for Manipulating and Assessing Colors and Palettes
Color Calculations with Emphasis on Spectral Data
"Risk Model Regression and Analysis with Complex Non-Linear
Models"
A Colour Picker Tool for Shiny and for Selecting Colours in
Plots
Convert from One Colour Space to Another, Print a Ready-to-Paste
Modern 'CSS' Syntax
Causal Discovery for Categorical Data with Label Permutation
Creates Co-Occurrence Matrices of Spatial Data
Analysis of Concept Maps and Concept Landscapes
A Combined Association Test for Genes using Summary Statistics
Fit and Apply ComBat, LMM, or Prescaling Harmonization for
ENIGMA and Other Multisite MRI Data
Comprehensive Batch Effect Diagnostics and Harmonization
A Joint Test-Statistic for the Null of Non-Cointegration
Introduction to Some Combinatorial Relations
Calculate Scores and Marks for Track and Field Combined Events
Estimation of Optimal Portfolio Weights by Combining Simple
Portfolio Strategies
A Combined Interaction Test for Unreplicated Two-Way Tables
Construction Methods for Series of PBIB Designs via Combinatory
Method S
Selection and Ranking of Omics Biomarkers Combinations Made Easy
Correcting Misclassified Binary Outcomes in Association Studies
Continuous Optimisation Towards Best Subset Selection
Covariance Measure Tests for Conditional Independence
Client for the Brazilian Foreign Trade Statistics API
('ComexStat')
Models and Equations for Human Comfort Research
Commonly Used Functions for R Shiny Applications
Computational Methods for Immune Cell-Type Subsets
Coarsened Mixtures of Hierarchical Skew Kernels
Call Functions Without Commas Between Arguments
Ecometric Models of Trait–Environment Relationships at the
Community Level
Network-Based Communities and Kernel Machine Methods
OMOP CDM DDL and Documentation Generator
Useful Libraries for Building a Java Based GUI under R
High Performance CommonMark and Github Markdown Rendering in R
JAR Files of the Apache Commons Mathematics Library
Assessing Predisposition Between Phenotypes using Polygenic
Scores
Comparison Functions for Clustering and Record Linkage
Compare Two Correlated C Indices with Right-Censored Survival
Outcome
Interface to Diverse Estimation Methods of Causal Networks
Compare C-Statistics (Concordance) Between Survival Models
Statistical Functions for the Design of Studies with Composite
Endpoints
Do a Git Style Diff of the Rows Between Two Dataframes with
Similar Structure
Compare MCMC Efficiency from 'nimble' and/or Other MCMC Engines
Finding the Best Model Using Eight Metrics Values
Correct for Verification Bias in Diagnostic Accuracy & Agreement
Multivariate Likelihood Ratio Calculation and Evaluation
Comparison of Survival Curves Between Two Groups
Conformational Manipulations of Protein Atomic Structures
Classification Measures when Subclasses are Involved
Generate Compilation Database for Use with 'Clang' Tools
A Graphical User Interface for Antitrust and Trade Practitioners
Functions Used in the Book "Computational Physics with R"
Composite Index Builder & Analytics 'shiny' App
Computation of Relative Weights of Variables and Composite Index
Values Based on PCA
Time Series Analysis and Forecasting Using Complex Variables
Calculate the Proportion of Permutations in Line with an
Informative Hypothesis
Create Complex UpSet Plots Using 'ggplot2' Components
Robust Linear Regression with Compositional Data as Covariates
Determine the Composite Reliability of a Naturalistic,
Unbalanced Dataset
Optimizing the Composite Reliability in Multivariate Nested
Designs
High Dimensional Discriminant Analysis with Compositional Data
Machine Learning with Compositional Data
Missing Value Imputation with Compositional Data
Multivariate Random Forest with Compositional Responses
Spatial Regression Models with Compositional Data
Univariate Feature Selection and Compound Covariate for
Predicting Survival, Including Copula-Based Analyses for
Dependent Censoring
Discrete Composite Distributions with Pareto Tails
Distribution Function of Quadratic Forms in Normal Variables
Flexible Framework for Simulating Community Assembly
Partitioning the Drivers of Stability of Ecological Communities
Access and Analyse UN Comtrade International Trade Data
Interface with the United Nations Comtrade API
Calculate the AQI from Pollutant Concentration
Calculate the Dutch Air Quality Index (LKI)
Conconi Estimate of Anaerobic Threshold from a TCX File
An Alternative to the Kruskal-Wallis Based on the Kendall Tau
Distance
Market Structure, Concentration and Inequality Measures
Copy Number Profile Curve-Based Association Test
Approximate Conditional Inference for Logistic and Loglinear
Models
Run Any CLI Tool on a 'Conda' Environment
Estimation and Inference for Conditional Copula Models
Parameter Estimation in Conditional GEE for Recurrent Event Gap
Times
Computation of P Values and Bayes Factors for Conditioning Data
Censored Data Imputation for Direct Modeling
Conditional Probabilities of Distributions Across Hearts Hands
Control How Many Times Conditions are Thrown
Conditional Multivariate t Distribution, Expectation
Maximization Algorithm, and Its Stochastic Variants
Estimation of the Conditional Survival Function for Ordered
Multivariate Failure Time Data
Conditional Truncated Multivariate Normal Distribution
Create Tours in 'Shiny' Apps Using 'Shepherd.js'
Conditional Visualization for Statistical Models
Interactive Conditional Visualization for Supervised and
Unsupervised Models in Shiny
Primal or Dual Cone Projections with Routines for Constrained
Regression
Visualization and Analysis of Statistical Measures of Confidence
Confidence and Consistency of Predictive Distribution Models
Confidence Estimation of Environmental State Classifications
Frequentist Confidence Analysis for Clinical Trials
Computation of 2D and 3D Elliptical Joint Confidence Regions
Highly Customizable, Parallelized Simulations of Frequentist
Confidence Clinical Trials
Manage Environment Specific Configuration Values
Package to Parse an INI File, Including Variable Interpolation
An Implementation of Parsing and Writing Configuration File
(JSON/INI/YAML/TOML)
Manage Application Settings via '.env' or '.ini' Files
Descriptive Interpretations of Confidence Intervals
Confidence Intervals for Robust and Classical Linear Mixed Model
Estimators
An Alternative Conflict Resolution Strategy
Confidence Curves and P-Value Functions for Meta-Analysis
Jackknife(+) Predictive Intervals for Bayesian Models
Conformal Prediction Methods for Multistep-Ahead Time Series
Forecasting
Tools for Conformal Inference for Regression in Multivariate
Functional Setting
Conformal Inference Tools for Regression with Multivariate
Response
Visualization Tools for Sensitivity Analysis of Unmeasured
Confounding
Configural Frequencies Analysis Using Log-Linear Modeling
Distance Metrics for Trees Generated by Congreve and Lamsdell
Correlation Guided Network Integration (CoNI)
Algorithms for Fitting Circles, Ellipses and Conics Based on the
Work by Prof. Nikolai Chernov
An Implementation of Conjoint Analysis Method
Implementation of a Method to Check the Cancellation Axioms of
Additive Conjoint Measurement
A Parametric Method for Generating Synthetic Data
Estimations using Conley Standard Errors
Conditional Mutual Information Estimation for Multi-Omics Data
Contingency Measure-Based Networks for Binary Time Series
Utilities for Interacting with the 'Posit Connect' Server API
Manage 'OAuth' Credentials from 'Posit Connect'
Visualize and Improve Connectedness of Factors in Tables
Measures of Independence and Connection Without Linear Models
Integrates with the 'RStudio' Connections Pane and 'pins'
Streamlining Data Access in Clinical Research
Expand 'connector' Package for 'Databricks' Tables and Volumes
Organize and Curate Your Content Within 'Posit Connect'
Tools for Working with Connectivity Data
Conover-Iman Test of Multiple Comparisons Using Rank Sums
Client for the Microsoft's 'Cognitive Services Text to Speech
REST' API
Consensus OPLS for Multi-Block Data Fusion
Identifying Conservation Prioritization Methods Based on Data
Availability
An Easy and Quick Way to Loop a Character Vector as a Menu in
the Console
Partial Linear Least-Squares Regression using Constrained
Splines
Compute the Median Ranking(s) According to the Kemeny's
Axiomatic Approach
Classification and Clustering of Preference Rankings
Fits Regression & ARMA Models Subject to Constraints to the
Coefficient
Reference on Constants, Units and Uncertainty
Identify Event Sequences Using Time Series Joins
Constrained, Covariance-Matching Constrained and Universal Point
or Block Kriging
Models Spatially Continuous and Discrete Population Genetic
Structure
Display Idiomatic Code to Construct Most R Objects
Social Contact Matrices for 177 Countries
Download Contact Surveys for Use in Infectious Disease Modelling
Two-Stage Detection and Attribution of Cross-Border Financial
Contagion Channels
Clustering and Classification with the Contaminated Normal
Difference-in-Differences with a Continuous Treatment
Scientific Content and Citation Analysis from PDF Documents
An Interface for Content-Based Identifiers
Content Validity Indices for Instrument Development
'a la Carte' on Text (ConText) Embedding Regression
Find Code Snippets with Context and Click to Navigate Directly
to Results
Continued Fraction Generators and Evaluators
Statistical Analysis of Contingency Tables
Contour-Enhanced Forest Plots for Meta-Analysis
Create Contour Plots from Data or a Function
Plots x,y,z Co-Ordinates in a Contour Map
Predictive Probability for a Continuous Response with an ANOVA
Structure
A Tiny Contribution Table Generator Based on 'ggplot2'
Control Function Methods with Possibly Invalid Instrumental
Variables
Quantile Comparison for Two-Sample Right-Censored Survival Data
Visualize the Effect of a Continuous Variable on a Time-to-Event
Outcome
Process Text and Compute Linguistic Alignment in Conversation
Transcripts
Convert Decimal to Binary-Coded Decimal (BCD) Form and Vice
Versa
Use the Given Parameters to Calculate the European Option Value
Convert Gene IDs Between Each Other and Fetch Annotations from
Biomart
Estimating IRT Parameters via Machine Learning Algorithms
Income Concentration Analysis with Complex Survey Samples
Co-Occurrence Network Construction and Manipulation
Your Friendly Solution to Managing Browser Cookies
Practical Tools for Scientific Computations and Visualizations
Co-Operation: Fast Covariance, Correlation, and Cosine
Similarity Operations
Important Concepts of Cooperative Game Theory
Automated Cleaning of Occurrence Records from Biological
Collections
Coordinated Networks Detection on Social Media
General Bivariate Copula Theory and Many Utility Functions
Fitting the copCAR Regression Model for Discrete Areal Data
Correlates of Protection and Correlates of Risk Functions
Copula-Based Semiparametric Analysis for Time Series Data with
Detection Limits
Coverage Probability Excursion (CoPE) Sets
Estimating Copula Entropy and Transfer Entropy
Search Download and Handle Data from Copernicus Climate Data
Service
Search Download and Handle Data from Copernicus Marine Service
Information
R Interface to Copernicus Marine Service
Adaptation of the Coloc Method for PheWAS
Tools for Nonparametric Martingale Posterior Sampling
Copula-Based Estimation and Statistical Process Control for
Serially Correlated Time Series
Copula Markov Model with Dependent Censoring
Analysis of Bivariate Survival Data Based on Copulas
Fitting Additive Copula Regression Models for Binary Outcome
Regression
Copula-Based Regression Models for Multivariate Censored Data
Estimation and Goodness-of-Fit of Copula-Based Models with
Arbitrary Distributions
Copula Mixed Models for Multivariate Meta-Analysis of Diagnostic
Test Accuracy Studies
Virtual Patient Simulation by Copula Invariance Property
Copula Based Stochastic Frontier Quantile Model
Assembling Long Gene Copies from Short Read Data
The COR for Optimal Subset Selection in Distributed Estimation
Apply 'colorffy' Color Gradients Within 'shiny' Elements
Community Estimation in G-Models via CORD
Programmatic Analysis of Sediment Cores Using Computed
Tomography Imaging
Classification, Regression and Feature Evaluation
Prepare, Manipulate and Check Data to Comply with Darwin Core
Standard
R Binding for the 'Certifiably Optimal RulE ListS (Corels)'
Learner
Core Functionality for Simulating Quantities of Interest from
Generalised Linear Models
Hidden Markov Models of Character Evolution
Record Linkage, Incorporating Imputation for Missing Agreement
Patterns, and Modeling Correlation Patterns Between Fields
Correct Mass Isotopologue Distribution Vectors
Count Regression for Correlated Observations with the
Beta-Binomial
Penalised Regression for Dichotomised Outcomes
Confounding Robust Independent Component Analysis for Noisy and
Grouped Data
The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset
Efficient Estimation of Covariance and (Partial) Correlation
Tools for Valuation, Financial Metrics and Modeling in Corporate
Finance
Statistics and Data Sets for Corpus Frequency Data
A 'Shiny' App for Exploration of Text Collections
Power Calculations for Assessing Correlates of Risk in Clinical
Efficacy Trials
Managing, Querying and Analyzing Tokenized Text
Implementation of 2D Correlation Analysis in R
Nonparametrics with Clustered Binary and Multinomial Data
Finding Associations in Position-Wise Aligned DNA Sequence
Dataset
Correct Overloaded Peaks from GC-APCI-MS Data
Corrected Test Statistics for Comparing Machine Learning Models
on Correlated Samples
Correct and Standardize References for Scientific Manuscripts
Visualize Details Behind Pearson's Correlation Coefficient
Speed Up Exploratory Data Analysis (EDA) with the Correlation
Funnel
Conduct Robust Correlations on Non-Normal Data
A Collection of Functions for Graphing Correlation Matrices
Creating Correspondence Tables Between Two Statistical
Classifications
Estimate Correlations Between Repeatedly Measured Endpoints
(E.g., Reliability) Based on Linear Mixed-Effects Models
Clustered Random Forests for Optimal Prediction and Inference of
Clustered Data
Correlation-Based and Model-Based Predictor Pruning
Software for Summarising and Evaluating STRUCTURE Output
Creates and Saves Out a Correlation Table with Significance
Levels Indicated
Modeling Correlational Magnitude Transformations in
Discretization Contexts
Arbitrary Bounding of Series and Time Series Objects
Significance Testing of Rank Cross-Correlations under SRD
Compute Cortisol Sine Score (CSS) for Diurnal Cortisol Analysis
Bound Constrained Optimal Sample Size Allocation
Cosine-Correlation Coefficient for Vector Variables
Fast Fitting of Stable Isotope Mixing Models with Covariates
Tools for Estimating and Predicting the Cosinor Model
Extended Tools for Cosinor Analysis of Rhythms
Conditional Ordinal Stereotype Model for Incident-Level
Comparison
Mutational Signatures from COSMIC (Catalogue of Somatic
Mutations in Cancer)
Cosmological Distances, Times, Luminosities, Etc
Fit Regularized Nonparametric Regression Models Using COSSO
Penalty
Sparse Nonparametric Regression for High-Dimensional Data
Copula-Based Semiparametric Models for Spatio-Temporal Data
Locates and Counts Pixels Within Color Range(s) in Images
A Countdown Timer for HTML Presentations, Documents, and Web
Apps
Estimation and Inference Methods for Counterfactual Analysis
Comprehensive Automatized Evaluation of Distribution Models for
Count Data
Discrete Response Regression for High-Dimensional Data
Penalized Estimation of Flexible Hidden Markov Models for Time
Series of Counts
Analysis of Biological Count Data, Especially from Single-Cell
RNA-Seq
Small Cell Masking Tool for One- & Two-Way Tabular Reports
Calculate Model-Based Metrics of Proportionality on Count-Based
Compositional Data
Flexible Univariate Count Models Based on Renewal Processes
Mean and Variance Modeling of Count Data
Splitting a Count Matrix into Independent Folds
Thomson Sampling for Zero-Inflated Count Outcomes
Programmatic Access to County Health Rankings & Roadmaps Data
Analysis of Coupling Coordination Degree
Optimal Pairing and Matching via Linear Assignment
Local Polynomial Regression of State Dependent Covariates in
State-Space Models
Constructing Joint Distributions with Control Over Statistical
Properties
Tests on Properties of Space-Time Covariance Functions
Brownian Motion Processes for 'nlme'-Models
Statistical Tests for Covariance and Correlation Matrices and
their Structures
Produce Forest Plots to Visualize Covariate Effects
Test for Equality of Covariance Matrices
Process Digital Cover Photography Images of Tree Crowns
Coverage Correlation Coefficient and Testing for Independence
Nonparametric Estimators for Covariance Functions
Political Linguistics Toolkit - Gaffes, Phonetics, and Text
Transformation
Load and Analyze Live Data from the COVID-19 Pandemic
Selected 'Drugbank' Drugs for COVID-19 Treatment Related Data in
R Format
Pulling Clean Data from Covid19india.org
The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Italy Dataset
The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data in Sri
Lanka
Client for Delphi's 'COVIDcast Epidata' API
Downloading, Reading and Analyzing PNAD COVID19 Microdata
Mutation Analysis Toolkit for COVID-19 (Coronavirus Disease
2019)
Estimate the Unit-Wide Probability of COVID-19
Covariance Estimation for Matrix Data with the Kronecker-Core
Decomposition
Robust Covariance Estimation via Nearest Neighbor Cleaning
VITA, IG and PLSIM Simulation for Given Covariance and Marginals
Statistical Tools for Covariance Analysis
Performs Segmented Linear Regression on Two Independent
Variables
Streamlined Plot Theme and Plot Annotations for 'ggplot2'
Messages, Warnings, Strings with Ascii Animals
Doubly Robust Inference for Cox Marginal Structural Model with
Informative Censoring
Bias-Corrected Sandwich Variance Estimators for Marginal Cox
Analysis of Cluster Randomized Trials
Cox Models by Likelihood Based Boosting for a Single Survival
Endpoint or Competing Risks
Cox Regression with Dependent Error in Covariates
Variable Selection for Cox's Model with Interval-Censored Data
Robust Likelihood Ratio Test and Confidence Intervals for the
Cox Model
A Model-X Knockoff Method for Genome-Wide Survival Association
Analysis
Cox Regression with Firth's Penalized Likelihood
Time-to-Event Data Analysis with Missing Survival Times
Stochastic Gradient Descent log-Likelihood Estimation in Cox
Proportional Hazards Model
Cox Regression (Proportional Hazards Model) with Multiple Causes
and Mixed Effects
Fit Robustly Proportional Hazards Regression Model
Confirmatory Path Analysis Through 'd-sep' Tests
Changepoint Additive Models for Time Series Omics Data
Bayesian Meta Analysis for Studying Cross-Phenotype Genetic
Associations
The Closure Principle Computational Approach Test
Concordance Probability Estimates in Survival Analysis
Classification with Parallel Factor Analysis
Association Between Methylation and a Phenotype of Interest
CpG Filtering Method Based on Intra-Class Correlation
Coefficients
Consolidates Information from the Federal Government Payment
Card
Sequential and Batch Change Detection Using Parametric and
Nonparametric Methods
Fitting Semiparametric Cumulative Probability Models for Big
Data
Correction of the P-Value after Multiple Coding in Generalized
Linear Models
Calculation of Log2 Counts per Million Cutoff from ERCC Controls
Conceptual Properties Norming Studies as Parameter Estimation
Detection of Multiple Changes in Slope in Univariate Time-Series
Composition of Probabilistic Preferences (CPP)
Check 'C' and 'C++' Files using 'Cppcheck'
'C++' Standard Template Library Containers
Fast Relative Comparisons of Floating Point Numbers in 'C++'
Algorithms for Routing and Solving the Traffic Assignment
Problem
Fast and Memory Efficient Spatial Interaction Models
Conditional Probit Model for Analysing Continuous Outcomes
Functions for Working with Danish CPR Numbers
Constructs a Correlated Pseudo-Marginal Sampler
Load CPS Microdata into R Using the 'Census Bureau Data' API
Nonparametric Change Point Estimation for Survival Data
Simulating Survival Data from Change-Point Hazard Distributions
A Toolbox for Using the CPS’s Voting and Registration Supplement
Nonparametric Change Point Detection for Multivariate Time
Series
Quantile, Composite Quantile Regression and Regularized Versions
Conditional Maximum Likelihood for Quadratic Exponential Models
for Binary Panel Data
Compute Cluster Robust Standard Errors with Degrees of Freedom
Adjustments
Congruent Rate Analyses in Birth-Death Scenarios
Multivariate Nonparametric Cramer-Test for the
Two-Sample-Problem
Cram Method for Efficient Simultaneous Learning and Evaluation
Network Analysis of Dependencies of CRAN Packages
Supplements the 'gtsummary' Package for Pharmaceutical Reporting
Download Logs from the 'RStudio' 'CRAN' Mirror
Package Directives and Collaboration Networks in CRAN
RStudio Addin for Searching Packages in CRAN Database Based on
Keywords
Conditional Random Sampling Sparse Matrices
Fit Continuous-Time Correlated Random Walk Models to Animal
Movement Data
Cyclic Redundancy Check with CPU-Specific Acceleration
Censored Regression with Conditional Heteroscedasticity
Univariate Analysis of Cluster Trials with Multiple Outcomes
Interpretable Discovery and Inference of Heterogeneous Treatment
Effects
Discounted Cash Flow Tools for Commercial Real Estate
Clustering of Genomic Regions Analysis Method
Create Logical Pairwise Comparison Matrix for the Analytic
Hierarchy Process
Tools for Managing SSH and Git Credentials
Evaluation of Credit Risk with Structural and Reduced Form
Models
Calibrated Ratio Estimator under Double Sampling Design
Crew Launcher Plugins for Traditional High-Performance Computing
Clusters
Analyze Cricketers and Cricket Teams Based on ESPN Cricinfo
Statsguru
Group-Based Modelling of Longitudinal Data
Access Crime Data from the Open Crime Database
A Comprehensive Collection of Crime-Related Datasets
A Comprehensive Set of Functions to Clean, Analyze, and Present
Crime Data
Fits a Model that Partitions the Covariate Space into Blocks in
a Data- Adaptive Way
Modeling Fissile Material Operations in Nuclear Facilities
An Implementation of the Critical Path Method
Setting the Critical Path in Project Management
Phase I/II CRM Based Drug Combination Design
Cell Ranger Output Filtering and Metrics Visualization
CCMN and Other Normalization Methods for Metabolomics Data
Object-Oriented Implementation of Dose Escalation Designs
Cellwise Robust M-Regression and SPADIMO
Implementation Helper for '[' and '[<-' of Custom Matrix-Like
Types
A Dashboard to Visualize Scientific Workflows in 'Cromwell'
Create an HTML Vertical Timeline from a Data Frame in
'rmarkdown' and 'shiny'
Schedule R Scripts and Processes with the 'cron' Job Scheduler
Synthetic Crook Deformations in Stem Point Clouds
Open Data of Agricultural Production of Crops of Peru
Crop Growing Degree Days and Agrometeorological Calculations
Changepoints for a Range of Penalties (CROPS)
Access Cropland Data Layer Data via the 'CropScape' Web Service
Climate Water Balance for Irrigation Purposes
Climate Crop Zoning Based in Air Temperature for Brazil
Analysis of Data from a Crossover Design with GEE
Cross-Expression Analysis of Spatial Transcriptomics Data
Local Haplotype Clustering and Visualization
Perform Linear or Nonlinear Cross Lag Analysis
Apply Functions to All Combinations of List Elements
Cross-Design & Cross-Format Network Meta-Analysis and Regression
Analysis and Search of Crossover Designs
Joint Distribution of Number of Crossings and Longest Run
Cross Tabulation and Loglinear Analyses of Categorical Data
Inter-Widget Interactivity for HTML Widgets
Cross-Fitting for Doubly Robust Evaluation of High-Dimensional
Surrogate Markers
Classes and Methods for Cross Validation of "Class Prediction"
Algorithms
Rename and Encode Data Frames Using External Crosswalk Files
Constrained Regression Model for an Ordinal Response and Ordinal
Predictors
Estimate Crown Scorch from Terrestrial LiDAR Scans
Tree Crown Segmentation in Airborne LiDAR Point Clouds
Unidimensional and Multidimensional Methods for Recurrence
Quantification Analysis
Bias-Corrected Variance for Competing Risks Regression with
Clustered Data
Competing Risks Regression for Stratified and Clustered Data
Stepwise Covariate Selection for the Fine & Gray Competing Risks
Regression Model
A Robust and Powerful Test of Abnormal Stock Returns in
Long-Horizon Event Studies
Nonlinear Regression Parameters Estimation by 'CRS4HC' and
'CRS4HCe'
Obtain Suggested Coordinate Reference System Information for
Spatial Data
Designing Cluster-Randomized Trials with Two Continuous
Co-Primary Outcomes
Conditional Randomization Testing (CRT) Approach for Conjoint
Analysis
Doubly Robust Inverse Probability Weighted Augmented GEE
Estimator
Sample Size Estimation Functions for Cluster Randomized Trials
Workflow for Cluster Randomised Trials with Spillover
Flexible and General Mediation Analysis Using Riesz Representers
Interface to Climatic Research Unit Time-Series Version 3.21
Data
Cluster Robust Wild Bootstrap Meta Regression
Download Crypto Currency Data from 'CoinMarketCap' without 'API'
Open Access to Cryptocurrency Market Data, Sentiment Indicators
and Interactive Charts
Access System Cryptographic Pseudorandom Number Generators
Visualization and Analytics for the Cryptoverse
Statistical Tests for Cryptographic Randomness
Crystallographic Information File (CIF) Data Processing Tools
A Cross-Scale Analysis Tool for Model-Observation Visualization
and Integration
Alerts from Public Health Surveillance Data
Functions for Conditional Simulation in Regression-Scale Models
Fitting and Tuning Regularized Cause-Specific Cox Models with
Elastic-Net Penalty
An Abstracted System for Easily Working with Databases with
Large Datasets
Statistical Downscaling of Climate Predictions
Frequent Contiguous Sequential Pattern Mining of Text
Cell Type-Specific Expression Quantitative Trait Loci Mapping
CRISPR-Based Salmonella Enterica Serotype Analyzer
Climate Services' Indicators Based on Sub-Seasonal to Decadal
Predictions
Preformatted Maps of Norway that Don't Need Geolibraries
A Collection of Tools for Building Cropping System Models
Cost-Sensitive Multi-Criteria Ensemble Selection for Uncertain
Cost Conditions
Conditionally Symmetric Multidimensional Gaussian Mixture Model
Biomarker Confirmation, Selection, Modelling, Prediction, and
Validation
A Tool for the Correlates of State Policy Project Data
Data Only: The Correlates of State Policy Project Dataset
Comparative Shortest Path Forest Stand Segmentation from LiDAR
Data
Concise Spatial Query and Representation System (c-Squares)
Selection of Number of Clusters via Normalized Clustering
Instability
Covariate Specific Treatment Effect (CSTE) Curve
Helpful Functions for Cleaning Surveillance Data
Date and Time Functions for Public Health Purposes
Assessing Skill of Climate Forecasts on Seasonal-to-Decadal
Timescales
Common Base-R Problems Relating to Lists
Read and Write CSV Files with Selected Conventions
Read and Write CSV on the Web (CSVW) Tables and Metadata
Import and Export CSV Data with a YAML Metadata Header
Processing Survey Data with Confidence Intervals Like 'SPSS'
Software
A Procedure to Clean, Decompose and Aggregate Timeseries
A Method for 'Connecting The Dots' in Weighted Graphs
Closed Testing with Globaltest for Pathway Analysis
Clinical Tolerance Limits for Assessing Agreement
Estimating the Parameters of a Continuous-Time Markov Chain from
Discrete-Time Data
Modeling Animal Movement with Continuous-Time Discrete-Space
Markov Chains
Collaborative Targeted Maximum Likelihood Estimation
A Modern and Flexible Data Pipeline for 'SurveyCTO'
Finite Sample Correction of the Two One-Sided Tests in the
Univariate Framework
Censored and Truncated Quantile Regression
Retrieve and Analyze Clinical Trials Data from Public Registers
Query Data from U.S. National Library of Medicine's Clinical
Trials Database
Density Profiles of Wood from CT Scan Images
Assess the Stability of Candidate Housekeeping Genes
Extract External 'R' Code and Insert Inline
Continuous Time Structural Equation Modelling
Continuous Time Structural Equation Modelling - Old
'OpenMx'-Based Version
Interactive Document for Working with Classification Tree
Analysis
Continuous Time Stochastic Modelling using Template Model
Builder
Visualize Item Metrics of the Classical Test Theory Framework
Multivariate Normal Mean Monitoring Through Critical-to-X
Control Chart
Read and Write Standard 'C' Types from Files, Connections and
Raw Vectors
A Class of Mixture Models for Ordinal Data
Adaptive Multivariate Integration over Hypercubes
A Vector Spatio-Temporal Data Structure for Data Analysis
Computation of a Cubic B-Spline Basis and Its Derivatives
Rule- And Instance-Based Regression Modeling
R Interface for the RAPIDS cuML Suite of Libraries
Charles's Utility Function using Formula
Tools, Measures and Statistical Tests for Cultural Evolution
Analyze Multivariate Phenotypes by Combining Univariate Results
Functions Centered Around Microsoft Excel Cumprinc Function
Cumulative Calibration Assessment for Prediction Models
Cumulative Percent Decay Curve Generator
Dependent Censoring Regression Models with Cure Fraction
Mixture and Non Mixture Parametric Cure Models to Estimate Cure
Indicators
Client for the 'currencyapi.com' Currency Conversion API
Exploring and Analyzing Academic Curricula
Toolkit for Analyzing Curricular Complexity
Data for Exploring Curricular Complexity
Data-Driven CVs with 'Quarto' and 'Typst'
Apply Mapping Functions in Frequent Saving
Partial Function Application with %<%, %-<%, and %><%
Finds Binary Outcome Designs Using Stochastic Curtailment
Tukey Curve Depth and Distance in the Space of Curves
Model-Agnostic Response Curves for Fitted Models
Cusp-Catastrophe Model Fitting Using Maximum Likelihood
Custom Made Gauss Quadrature Nodes and Weights
Pricing Various Types of Custom Derivatives
Evaluation Metrics for Customer Scoring Models Depending on
Binary Classifiers
Customized Training for Lasso and Elastic-Net Regularized
Generalized Linear Models
Easily Switch Output Format of 'Rmarkdown' Files with Shared
Frontmatter
Costs Allocation for the Installation of an Elevator
Compute Decision Interval and Average Run Length for CUSUM
Charts
Clinical Utility Tools to Analyze a Predictive Model
Estimate Cutpoints of Metric Variables in the Context of Cox
Regression
Determine and Evaluate Optimal Cutpoints in Binary
Classification Tasks
Optimal Equal-HR Method to Find Two Cutpoints for U-Shaped
Relationships in Cox Model
Compute Expected Shortfall and Value at Risk for Continuous
Distributions
Calibration, Validation, and Simulation of TKTD Models
Cross-Validated Area Under the ROC Curve Confidence Intervals
Efficient Design and Analysis of Cluster Randomized Trials
Access and Analyse Data from the 'CVD Prevent' API
Tests for the Equality of Coefficients of Variation from
Multiple Groups
Lasso Penalized Precision Matrix Estimation
Cross-Validation for Linear and Ridge Regression Models
Cross-Validation Model Averaging for Partial Linear Functional
Additive Models
Cramer von Mises Tests for Discrete or Grouped Distributions
Cross-Validation for Multi-Population Mortality Models
Compute Risk Scores for Cardiovascular Diseases
SEM Model Comparison with K-Fold Cross-Validation
Fast Cross-Validation via Sequential Testing
Cross-Validation Tools for Regression Models
Cauchy Weighted Joint Test for Pharmacogenetics Analysis
Continuous Wavelet Transformation for Spectroscopy
A Toolbox for Modelling Species Coexistence in R
Extend 'cxxfunction' by Saving the Dynamic Shared Objects
Cycle Routing and Data for Cycling Advocacy
Tools for Calculating Hypocycloids, Epicycloids, Hypotrochoids,
and Epitrochoids
Survival Modeling with a Periodic Hazard Function
Cyclic Coordinate Descent for Logistic, Poisson and Survival
Analysis
Circular-Linear Copulas with Angular Symmetry for Movement Data
Query 'Team Cymru' 'IP' Address, Autonomous System Number
('ASN'), Border Gateway Protocol ('BGP'), Bogon and 'Malware'
Hash Data Services
Agent-Based Model for Taenia_solium Transmission and Control
Plot Fan Plots for Cytometry Data using 'ggplot2'
Automated Cytometry Gating and Annotation
Optimal Transport for Gating Transfer in Cytometry Data with
Domain Adaptation
Simplex Visualization of Cell Fate Similarity in Single-Cell
Data
Use Open Data from the Czech Statistical Office in R
Descriptive 3D Multidimensional Item Response Theory Modelling
Tools for creating D3 JavaScript network, tree, dendrogram, and
Sankey graphs from R
Interactive Charts of Nested and Hierarchical Data with 'D3.js'
Fast and Beautiful Interactive Visualization for 'Markdown' and
'Shiny'
Create Interactive Collapsible Trees with the JavaScript 'D3'
Library
Interface to 'D4Science' 'StorageHub' API
Discriminant Analysis for Evolutionary Inference
Data Analysis and Graphics Data and Functions
Data Sets and Functions, for Demonstrations with Expression
Arrays and Gene Sequences
Damped Anderson Acceleration with Epsilon Monotonicity for
Accelerating EM-Like Monotone Algorithms
Data Analysis using Bootstrap-Coupled Estimation
Detection and Attribution Analysis of Climate Change
Three-Way / Multigroup Data Analysis Through Densities
Functions Useful in the Design and ANOVA of Experiments
Design and Analysis of Experiments with R
Test Robustness with Directed Acyclic Graphs
Directed Acyclic Graph HMM with TAN Structured Emissions
Spatial Vector Data for Danmarks Administrative Geografiske
Inddeling DAGI
Graphical Analysis of Structural Causal Models
Directed Acyclic Graphs: Analysis and Data Simulation
DAGs with Omitted Objects Displayed (DAGWOOD)
Data Quality Reporting for Temporal Datasets
Interface with Google Cloud Document AI API
Dynamical Assembly of Islands by Speciation, Immigration and
Extinction
Extracts Phylogenetic Island Community Data from Phylogenetic
Trees
moDel Agnostic Language for Exploration and eXplanation
Nonparametric Double Additive Location-Scale Model (DALSM)
Leveraging Experiment Lines to Data Analytics
The DALY Calculator - Graphical User Interface for Probabilistic
DALY Calculation in R
Detecting Damaged Cells in Single-Cell RNA Sequencing Data
Create an 'Area of Interest' Around a Constructed Dam for
Comparative Impact Evaluations
Dynamic Assembly Model of Colonization, Local Extinction and
Speciation
Interface to Drosophila Activity Monitor System Result Files
Dandelion Plot for R-Mode Exploratory Factor Analysis
Discovery of Candidate Disease Genes Using Trans-Regulatory
Effects
Design and Analysis of Non-Inferiority Trials
Functions for Wayne W. Daniel's Biostatistics, Tenth Edition
Discriminant Adaptive Nearest Neighbor Classification
Data Augmentation for Private Posterior Estimation
Data Quality Assessment for Process-Oriented Data
Differential Analysis with Random Reference Genes
Estimating Dark Diversity and Site-Specific Species Pools
Importing and Analysing 'SNP' and 'Silicodart' Data Generated by
Genome-Wide Restriction Fragment Analysis
Analysing 'SNP' and 'Silicodart' Data - Basic Functions
Analysing 'SNP' Data to Support Captive Breeding
Auxiliary Data Package for Our Main Package 'dartR'
Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide
Restriction Fragment Analysis
Analysing SNP Data to Identify Sex-Linked Markers
Applying Landscape Genomic Methods on 'SNP' and 'Silicodart'
Data
Install and Load the 'dartRverse' Suits of Packages
Das Gupta Standardisation and Decomposition
Customise the Appearance of 'shinydashboard' Applications using
Themes
Tools for Reading, Processing and Writing 'DSSAT' Files
Analyze Multi-Threading Performance for 'data.table' Functions
General Purpose Hierarchical Data Structure
Wrapper for 'TCdata360' and 'Govdata360' API
Connecting to Various Database Platforms
JAR Dependencies for the 'DatabaseConnector' Package
Swarm Intelligence for Self-Organized Clustering
Interactive and Reproducible Data Cleaning
Client for the 'Google Data Commons API V2'
A 'shiny' App to Compare Two Data Frames
Exploratory Data Analysis for Public Policy Applied to Culture
Data Frame Fingerprints and Lineage Figures
Concept Drift Detection Methods for Stream Data
An Interactive Editor for Viewing, Entering, Filtering & Editing
Data
Familiarity with Dataframes Before Data Manipulation
Estimating Finite State Machine Models from Data
Machine Learning for Integrating Partially Overlapped Genetic
Datasets
A Suite of Checks for Identification of Potential Errors in a
Data Frame as Part of the Data Screening Process
Modules to Import and Manipulate Data in 'Shiny'
Spatial and Taxonomic Data Utilities for Specimen Datasets
Datasets and Functions to Accompany Analisis De Datos Con R
Easily Source Publicly Available Data on Derivatives
A Flexible Container to Transport and Manipulate Data and
Associated Resources
Construct Reproducible Analytic Data Sets as R Packages
Efficient and Flexible Data Preprocessing Tools
Data Quality in Epidemiological Research
Reproducible Data Screening Checks and Report of Possible Errors
C3S Quality Control Tools for Historical Climate Data
Retrieval Functions for USGS and EPA Hydrology and Water Quality
Data
Data Bank for Statistical Analysis and Visualization
Datasets and Basic Statistics for Symbolic Data Analysis
Graphical Interface for Loading Datasets
Datasets from the Book "An Introduction to Clustering with R"
A Metapackage for Thematic and Domain-Specific Datasets
Quantifying Similarity of Datasets and Multivariate Two- And
k-Sample Testing
Create Lightweight Schema.org Descriptions of Data
Provides a Link Between the 'LSEG Datastream' System and R
The Research Data Warehouse of Miguel de Carvalho
Comprehensive Data Summarization for Statistical Analysis
Fast Access to Brazilian Public Health Data from 'DATASUS'
A Lightweight, Flexible, and Fast Data Validation Package that
Can Handle All Sizes of Data
An Interactive and Feature-Rich Data Viewer
Data Visualisation Using an HTML Page and 'D3.js'
Easy Data Wrangling and Statistical Transformations
Simplify Access to Data from the Amazon Region
Simplify Access to Brazilian Social Data
Wrangle and Modify Ts Object with Classic Frequencies and Exact
Dates
Collect and Install R Packages on a Specified Date with
Dependencies
Standardize Dates in Different Formats or with Missing Data
Datetimes with Optional UTC Offsets and/or Heterogeneous Time
Zones
A Datetime Range Picker Widget for Usage in 'Shiny' Applications
Convert and Impute Dates to ISO 8601 Format and Reconcile Data
Sets
Traduce al Español Varios Conjuntos de Datos de Práctica
Preparation of Object Dating Ranges for Density Plots (Aoristic
Analysis)
Compact Standard for Australian Phone Numbers
Datasets for "Sampling and Data Analysis Using R: Theory and
Practice"
Discriminant Analysis with Additional Information
An API Wrapper for 'DAWA' - 'The Danish Address Web API'
Distributes Teachers Lessons On Days in a Balanced Manner
Calculating Days' Supply and Daily Dose of Prescriptions
Autocovariance Estimation via Difference-Based Methods
Discrete Bayesian Additive Regression Trees Sampler
Calculates the Density-Based Clustering Validation (DBCV) Index
A Double Bootstrap Method for Analyzing Linear Models with
Autoregressive Errors
Generalised Linear Models by Subsampling and One-Step Polishing
Sequence Clustering with Discrete-Output HMMs
'DBHYDRO' Hydrologic and Water Quality Data
Database Queries Using 'data.table' Syntax
Compute the NPMLE of Distribution Function from Doubly Censored
Data, Plus the Empirical Likelihood Ratio for F(T)
Deterministic Blockmodeling of Signed, One-Mode and Two-Mode
Networks
A Metadata-Driven Framework for Streamlining Database Joins
Confidence Interval for Matrix Completion via De-Biased
Estimator
Distance-Based Measures of Spatial Structures
Dynamic Bayesian Network Structure Learning, Parameter Learning
and Forecasting
Rank Selection for Non-Negative Matrix Factorization
Dynamic Bayesian Network Learning and Inference
Simplifies Plotting Data Inside Databases
Database Connection Management and Utilities for 'dbverse'
Robust Distance-Based Visualization and Analysis of Mixed-Type
Data
Density-Based Spatial Clustering of Applications with Noise
(DBSCAN) and Related Algorithms
Doubly Robust Distribution Balancing Weighting Estimation
Produce R Functions to Create HTML Forms Based on SQL Meta Data
Inferring Condition-Specific Networks via Differential Network
Inference
Detrended Fluctuation and Detrended Cross-Correlation Analysis
Dynamic Common Correlated Effects Estimation for Panel Data
Analyzing Dichotomous Choice Contingent Valuation Data
DCC Models with GARCH and GARCH-MIDAS Specifications in the
Univariate Step, RiskMetrics, Moving Covariance and Scalar and
Diagonal BEKK Models
Fast Computation of Distance Correlations
Distributional Cost-Effectiveness Analysis for Health Technology
Assessment
Clustering Big Data using Expectation Maximization Star (EM*)
Algorithm
Efficient and Accessible Discrete Choice Experiments
Data Cloud Geometry (DCG): Using Random Walks to Find Community
Structure in Social Network Analysis
Calculate the Dendritic Connectivity Index in River Networks
Genetic Relatedness Between Polyclonal Infections
Claims Reserving under the Double Chain Ladder Model
Distance Based Cell Lineage Reconstruction
Data Cloning and MCMC Tools for Maximum Likelihood Methods
Functions for the Detection of Spatial Clusters of Diseases
Model-Based Detection of Disease Clusters
Calculating the M2 Model Fit Statistic for Diagnostic
Classification Models
Data Sets for Diagnostic Classification Modeling
Hierarchical Models Made Easy with Data Cloning
Modify Data Using Externally Defined Modification Rules
Generate 'Stan' Code for Diagnostic Classification Models
Providing Fast and Flexible Functions for Distance Correlation
Analysis
Variable Selection Algorithms Using the Distance Correlation
A Fast Implementation of Distance Covariance
Distance Covariance and Correlation for Time Series Analysis
Density Convoluted Support Vector Machines
Decision Curve Analysis for Model Evaluation
Dynamic Copula VAR Models for Time-Varying Dependence
Depth-Based Classification and Calculation of Data Depth
A Deep Dynamic Experimental Self-Organizing Neural Network
Framework
Variance Stabilization by Data-Driven Haar-Fisz (for
Microarrays)
The Data Defect Index for Samples that May not be IID
Diagonally Dominant Principal Component Analysis
Analysis and Visualization of Droplet Digital PCR in R and on
the Web
Data Sets for Discrete Probability Models
Density Regression via Dirichlet Process Mixtures of Normal
Structured Additive Regression Models
Data-Driven Sparse Partial Least Squares
Latent Class Analysis with Dirichlet Diffusion Tree Process
Prior
Outlier Detection via Trimming of Mutual Reachability Minimum
Spanning Trees
Learning Bayesian Networks with Mixed Variables
Conventional and Fuzzy Data Envelopment Analysis
A Post-Clustering Denoiser for COI-5P Barcode Data
Duration Estimation for Biomarker Enrichment Studies and Trials
Pipeline for Debiased Target Trial Emulation
Efficient Inference on High-Dimensional Linear Model with
Missing Outcomes
Bifurcation Analysis of Ordinary Differential Equation Systems
Bayesian Inference for Differential Equations
Analysis of Non-Decimal Currencies and Double-Entry Bookkeeping
Box-Plots and Outlier Detection for Probability Density
Functions
Text-Based Summaries for 'profvis' Profiling Data
Debt Sustainability Analysis and Fiscal Risk Assessment
Debug Tool to Watch Objects/Expressions While Running an R
Script
Detecting Changes in Autocorrelated and Fluctuating Signals
DEComposition of Indirect and Direct Effects
Bindings for 'Mapbox' Ear Cutting Triangulation Library
Detecting, Decomposing, and Stress-Testing Temporal Change in
Repeated Decision Systems
Construct and Audit Longitudinal Decision Paths
Quantitative Support of Decision Making under Uncertainty
Roadmap Footers for 'Reveal.js' Slides in 'Quarto' and 'R
Markdown'
Differential Co-Expression and Differential Expression Analysis
Decode Coded Variables to Plain Text and the Other Way Around
Decomposition Based Machine Learning Model
Time Series Prediction with PSF and Decomposition Methods (EMD
and EEMD)
Empirical Mode Decomposition for Cyclostratigraphy
Provides Easy Methods to Perform Life Expectancy Decomposition
Extend the Behaviour of a Function without Explicitly Modifying
it
Decorrelation Projection Scalable to High Dimensional Data
Monitoring and Analyzing Dedoose Qualitative Data Exports
Deductive Correction, Deductive Imputation, and Deterministic
Correction
Data Correction and Imputation Using Deductive Methods
Visualise and Explore the Deep Dependencies of R Packages
Bayesian Deep Gaussian Processes using MCMC
Causal Inference with Super Learner and Deep Neural Networks
Interface to the 'DeepL' Translation API
Clustering of Short Texts by Mixture of Unigrams and Its Deep
Extensions
Seamless Language Translation in 'RStudio' using 'DeepL' API and
'Rstudioapi'
Test for Differences in Diversification Rates over Time
Plotting Tools for Anyone Working in Deep Time
Geologic Pattern Data from FGDC Used in 'deeptime'
Density Estimation by Extreme Value Distributions
Change the Default Arguments in R Functions
Fitting Differential Equations to Time Series Data
Deferred List - A Read-Only List-Like Object with Deferred
Access
Estimation and Simulation of Multi-Binary Response Models
Classify RGB Images into Forest or Non-Forest
Spatial Deformation and Dimension Expansion Gaussian Processes
Estimating Remaining Useful Life with Linear Mixed Effects
Models
Degree-Day Phenology Calculator ('shiny' Application)
Models for Skewed Count Distributions Relevant to Networks
Density Estimation from GROuped Summary Statistics
Differentially Expressed Heterogeneous Overdispersion Gene Test
for Count Data
Multiple Imputation for Recurrent Events
Statistical Functions for the Delaporte Distribution
Fit Linearized Hyperbolic Model for Delay Discounting Curves
A Framework for Parallelizing Dependent Tasks
Sample Size and Power Calculations using the APPLE, SEPPLE,
APPLE+ and SEPPLE+ Methods
Delaunay Triangulation and Dirichlet (Voronoi) Tessellation
Helper Functions for Species Delimitation Analysis
Convert 'R Markdown' and 'Quarto' Documents to Ecological
Metadata Language
Quantify Rhythmic Gene Co-Expression Relative to a Reference
Delta Measurement of Agreement for Nominal Data
Estimate Potential Impact and Population Attributable Fractions
with Aggregated Data
Identification of Dichotomous Differential Item Functioning
(DIF) using Angoff's Delta Plot Method
Statistical Hypothesis Testing Using the Delta Method
Kernel Density Estimation using Lifetime Distributions
The Distributed EM Algorithms in Multivariate Gaussian Mixture
Models
Decision Making Trial and Evaluation Laboratory Technique in R
Deming, Theil-Sen, Passing-Bablock and Total Least Squares
Regression
Fit Two-Component Normal and Lognormal Mixture Models
Simulating Differential Equations with Data
Parametric Mortality Curve Fitting and Mortality Forecasting
Tools
Analysis of Age-Structured Demographic Models
Forecasting Mortality, Fertility, Migration and Population Data
Kernel Density Estimation for Demonstration Purposes
Runs a 'Shiny' App as Demo or Lists All Demo 'Shiny' Apps
Simultaneous Analysis of Multiplexed Metabarcodes
Extending 'dendrogram' Functionality in R
A Tool for Processing and Analyzing Dendrometer Data
Extra Functions to Cut, Label and Colour Dendrogram Clusters
Forest Estimations and Dendrometric Computations
Create Networks of Dendrochronological Series using Pairwise
Similarity
A Set of Tools for Calculating Spatial Synchrony Between
Tree-Ring Chronologies
Linear and Nonlinear Methods for Analyzing Daily and Monthly
Dendroclimatological Data
Dendrogram Seriation: Ordering for Visualisation
Modular Leaf Ordering Methods for Dendrogram Nodes
A Tidy Format Datasets of Dengue by Country
Generate and Simulate Deterministic Compartmental Models
Differential Expression Analysis Using a Bottom-Up Model
Statistical Analyses of De Novo Genetic Variants
Functional Linear Mixed Models for Densely Sampled Data
Density Estimation via Bayesian Inference Engines
Analysing Density Profiles from Resistance Drilling of Trees
Polygons of Bivariate Density Distributions
Clustering by Fast Search and Find of Density Peaks
Distribution Comparison Through Density Ratio Estimation
Dens-Based Method for Partial Correlation Estimation in Large
Scale Brain Networks
Density Strips and Other Methods for Compactly Illustrating
Distributions
Publication-Ready Descriptive, Bivariate, Regression,
Correlation and Diagnostic Accuracy Tools for Medical and
Dental Data
Simple Dengue Test and Vaccinate Cost Thresholds
Global Optimization by Differential Evolution
Differential Evolution Optimization in Pure R
Cache R Expressions, Taking Their Dependencies into Account
Statistical Methods for Survival Data with Dependent Censoring
Statistical Methods for the Analysis of Dependently Truncated
Data
Simulate Omics-Scale Data with Dependency
Deconvolute Mixed Genomes with Unknown Proportions
'DEploid' Data Analysis and Results Interpretation
Visualization Tools for German Regional Data
Dependent Mixture Models - Hidden Markov Models of GLMs and
Other Distributions in S4
Decision-Analytic Modelling for Depression Prevention and
Treatment
Read, Plot and Analyse Output from the DEPONS Model
Power Analysis for Differential Expression Studies
Calculating and Analyzing Measures of Deprivation in the United
States
Dependency Management with 'roxygen'-Style Comments
Statistical Depth Functions for Multivariate Analysis
Functions and R Code to Accompany Derivatives Markets
Detecting Epidemics using School Absenteeism
Tool for Unbiased Literature Searching and Gene List Curation
Seasonal Adjustment by Frequency Analysis
An Interface to the 'DescribeDisplay' 'GGobi' Plugin
Describe Data in R Using Common Descriptive Statistics
Characterizing Observed and Expected Representation
Support Functions for (Reproducible) Descriptive Statistics
Generate Plots for All Variables in Descriptive Tables
Produce Descriptive and Comparative Tables Easily
Interactive Functions to be Used as Shortcuts in 'RStudio'
Utilities for Describing and Comparing Data
Data-Driven Locally Weighted Regression for Trend and
Seasonality in TS
Blocking and Randomization for Experimental Design
Matched Samples that are Balanced and Representative by Design
Sample Size Calculation of Various Study Designs
Distributed Estimation in Single-Index Models with Multiple
Links ('Desimml')
Desirability Functions for Ranking, Selecting, and Integrating
Data
Function Optimization and Ranking via Desirability Functions
Desirability Functions for Multiparameter Optimization
Desparsified Lasso Inference for Time Series
Differentially Expressed Single Nucleotide Polymorphism
Solvers for Initial Value Problems of Differential Equations
('ODE', 'DAE', 'DDE')
Motivational Quotes and Shakespearean Bard–bits for Personal
Projects
Plotting Field Plans for Agricultural Experiments
Representation of DET Curve with Confidence Intervals
Create Details HTML Tag for Markdown and Package Documentation
Analyzing Wildlife Data with Detection Error
Detect Nonnormality in Meta-Analysis without Raw Data
Detect Data Containing Personally Identifiable Information
Detect Runs of Homozygosity and Runs of Heterozygosity in
Diploid Genomes
Detect and Check for Separation and Infinite Maximum Likelihood
Estimates
Life Insurance Premium and Reserves Valuation
Implementation of the DetMCD Algorithm (Robust and Deterministic
Estimation of Location and Scatter)
Density Estimation and Random Number Generation with
Distribution Element Trees
A Graphical User Interface (GUI) to Visualize and Analyze
Dendrochronological Data
Clear and Condense Argument Check for User-Defined Functions
Detecting Extremal Values in a Normal Linear Model
Data sets from Devore's "Prob and Stat for Eng (7th ed)"
Quantify the Relationship Between Development Rate and
Temperature in Ectotherms
Tools to Make Developing R Packages Easier
Develop Treatment Rules with Observational Data
'DEXi' Decision Tree Analysis and Visualization
Linear Discriminant Function and Canonical Correlation Analysis
Degrees of Freedom Adjustment for Robust Standard Errors
Phase I/II Adaptive Dose-Finding Design for Combination Studies
Compare Two Dataframes and Return Adds, Changes, and Deletes
Dose-Finding by the Continual Reassessment Method
Extract Drugs from Differential Expression Data from LINCS
Database
Common Department for Education Analysis Tasks
Automatically Expand Delimited Column Values into Multiple
Binary Columns with 'dfexpand'
Differential Functioning of Items and Tests
Simulate a Data Frame Mirroring an Input and Produce Shareable
Simulation Code
Phase I/II Adaptive Dose-Finding Design for MTA
Detection and Analysis of Insect Defoliation Signals in Tree
Rings
Phase I Control Charts (with Emphasis on Distribution-Free
Methods)
Accelerated Derivative-Free Method for Large-Scale Nonlinear
Systems of Equations
Diewert and Fox's Method of Value Added Growth Decomposition
Capture-Recapture Estimation using Bayesian Model Averaging
Differential Gene Expression Analysis with R
Differential Gene Expression (DGE) Analysis Results Data Object
Differential Gene Expression (DGE) Analysis Utility Toolkit
Differential Geometric Least Angle Regression
Double Generalized Linear Models Extending Poisson Regression
Dependent Gaussian Processes for Longitudinal Correlated Factors
Interface to 'dgpsi' for Deep and Linked Gaussian Process
Emulations
Residual Diagnostics for Hierarchical (Multi-Level / Mixed)
Regression Models
Double Hierarchical Generalized Linear Models
Reproductive Age Female Data of Various Demographic Health
Surveys
Independence Testing via Hilbert Schmidt Independence Criterion
Create Large Scale Repeated Regression Summary Statistics
Dataset and Visualization Seamlessly
Recover Diagnostic Test Accuracy Counts from Reported Accuracy
Measures
Verifiable FDR Diagnostics for Proteomics
Diagnostic Plot and Multivariate Summary Statistics of Weighted
Samples from Importance Sampling
Routines for Fit, Inference and Diagnostics in Linear L1 and LAD
Models
Meta-Analysis of Diagnostic Accuracy Studies with Several
Cutpoints
Block Diagonal Extraction or Replacement
Functions for Visualising Simple Graphs (Networks), Plotting
Flow Diagrams
Export DiagrammeR Graphviz Graphs as SVG
Parse, Format, and Validate International Phone Numbers
Required 'libphonenumber' jars for the 'dialr' Package
Tools for Creating Tuning Parameter Values
'R' Interface to the 'Diariodeobras' Application
Calculate Ecological Information and Diatom Based Indices
Calculate probabilities of various dice-rolling events
Construction and Evaluation of Metamodels
Kriging Methods for Computer Experiments
Kriging-Based Optimization for Computer Experiments
High Dimensional Categorical Data Visualization
Methods for Visualization of Computer Experiments Design and
Surrogate
R6 Based Key-Value Dictionary Implementation
Retrieve the Dictionary Definitions of English Words
Treatment Effects with Multiple Periods and Groups
Two-Stage Difference-in-Differences Following Gardner (2021)
A Simple Implementation and Demonstration of Gradient Boosting
A Big Data Implementation of Difference-in-Differences
Estimation with Staggered Treatment
Difference-in-Differences in Heterogeneous Adoption Designs with
Quasi Untreated Groups
Imputation Estimator from Borusyak, Jaravel, and Spiess (2021)
Estimators DID with Multiple Groups and Periods
Estimation in Difference-in-Difference Designs with Multiple
Groups and Periods
Compute Recency Frequency Monetary Scores for your Customer Data
Genome Polarization via Diagnostic Index Expectation
Maximization
Calculate the Cost and Environmental Impact of a Ideal Diet
R Interface to the ZEIT ONLINE Content API
Detection of Differential Item Functioning (DIF) in Rasch Models
by Boosting Techniques
Fisher's z-Tests Concerning Differences Between Correlations
Analyzing and Visualizing Differential Correlation Networks in
Biological Data
Compute the Difference Between Data Frames
Given a List of Gene Symbols, Performs Differential Enrichment
Analysis
Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)
Metrics of Difference for Comparing Pairs of Maps or Pairs of
Variables
Diffusion IRT Models for Response and Response Time Data
Multi-Fidelity Computer Experiments Using the Tuo-Wu-Yu Model
Identifying Significant Node Scores using Network Diffusion
Algorithm
Display Differences Between Two Files using Codediff Library
Pattern Analysis Across Contingency Tables
A Penalty Approach to Differential Item Functioning in Rasch
Models
Dynamic ICAR Spatiotemporal Factor Models
DIF and DDF Detection by Non-Linear Regression Models
Multilevel Mantel-Haenszel Statistics for Differential Item
Functioning Detection
Collection of Methods to Detect Dichotomous, Polytomous, and
Continuous Differential Item Functioning (DIF)
Differential Item Functioning via Shiny Application
Item Focussed Trees for the Identification of Items in
Differential Item Functioning
Create Compact Hash Digests of R Objects
A Curated Collection of Digestive System and Gastrointestinal
Disease Datasets
Tests for Detecting Irregular Digit Patterns
Determination of Intervals Using Georeferenced Survey Simulation
Reconstruct Paleoclimate and Paleoecology with Leaf Physiognomy
Differential Identification using Mixture Ensemble
Gathering Bibliographic Records from 'Digital Science
Dimensions' Using 'DSL' API
Fit Multivariate Diversity-Interactions Models with Repeated
Measures
Visualising and Interpreting Statistical Models Fit to
Compositional Data
A Framework for Dimensionality Reduction
A Method to Analyze Recurrent DNA Copy Number Aberrations in
Tumors
Finding Recurrent DNA Copy Number Alterations and Differences
A Toolkit for Year-Quarter, Year-Month and Year-Isoweek Dates
Differential Pattern Analysis via Linear Modeling
Robust Tests for Differential Dispersion and Differential
Expression in RNA-Sequencing Data
Depth Importance in Precision Medicine (DIPM) Method
Directional Penalties for Optimal Matching in Observational
Studies
A Dipping Sauce for Data Analysis and Visualizations
Hartigan's Dip Test Statistic for Unimodality - Corrected
Debiased Inverse Propensity Score Weighting
Linear Regressions with a Latent Outcome Variable
Bayesian Clustering of Multivariate Data Under the
Dirichlet-Process Prior
Direct Age Standardisation with Confidence Intervals
Estimating Controlled Direct Effects for Explaining Causal
Findings
A Collection of Functions for Directional Data Analysis
Direction Analysis for Pathways and Kinases
Adjusted Means and Proportions by Direct Standardisation
Build Dirichlet Process Objects for Bayesian Modelling
Distributed Imputation for Random Effects Models with Missing
Responses
Nonparametric Methods for Directional Data
Support Functions for Time Series Analysis Book
Two-Steps Benchmarks for Time Series Disaggregation
Autoregressive Integrated Moving Average (ARIMA) Based
Disaggregation Methods
Wrapper for the UN OCHA ReliefWeb Disaster Events API
Bayesian Multi-State Modelling of Chronic Disease Burden Data
Linear and Non-Linear AUC for Discounting Data
A User-Friendly Pipeline for Biomarker Discovery in Single-Cell
Transcriptomics
Cox Models for Time-to-Event Data with Nonparametric Discrete
Group-Specific Frailties
Discrete Laplace Mixture Inference using the EM Algorithm
Mixtures of Discrete Laplace Distributions using Numerical
Optimisation
Text Conversion from Nexis Uni PDFs to R Data Frames
Test for Discretized Normality in Ordinal Data
Implementation of the DISCO Metric for Internal Clustering
Evaluation
Functions for Discordant Kinship Modeling
Analyze Group Patterns using Graph Theory in Educational
Settings
Checks Title, Abstract and Keywords to Optimise Discoverability
Interactive Tutorials and Data for "Discovering Statistics Using
R and RStudio"
Example Data Sets for Use with Discrete Statistical Tests
Bayesian Distributed Lag Model Fitting for Binary and Count
Response Data
FDR Based Multiple Testing Procedures with Adaptation for
Discrete Tests
Simulated Goodness-of-Fit Tests for Discrete Distributions
FWER-Based Multiple Testing Procedures with Adaptation for
Discrete Tests
An Extension of the Gap Statistic for Ordinal/Categorical Data
Improved q-Values for Discrete Uniform and Homogeneous Tests
Vectorised Computation of P-Values and Their Supports for
Several Discrete Statistical Tests
Discrete Weibull Distributions (Type 1 and 3)
Data Preprocessing, Discretization for Classification
Model Wrappers for Discriminant Analysis
A Companion Package for the Book "Discrete Choice Analysis with
'R'"
Measuring Discursive Sophistication in Open-Ended Survey
Responses
Data for Comparing Species Distribution Modeling Methods
Modelling Spatial Variation in Disease Risk for Areal Data
Feature Stores for the 'diseasy' Framework
Calculate Dissimilarity Matrix for Dataset with Mixed Attributes
Calculates Disproportionate Impact When Binary Success Data are
Disaggregated by Subgroups
Simulation of Demic Diffusion with Environmental Constraints
Indicators for the Analysis of Dispersion of Datasets with
Batched and Ordered Samples
Numeric and Color Sequences with Non-Linear Interpolation
Create Disposable R Packages for Testing
Analysis of Disposition Effect on Financial Portfolios
Multiple Assemblage Dissimilarity for Orders q = 0-N
Spatial Downscaling using the Dissever Algorithm
Creating, Manipulating, and Subsetting "dist" Objects
Fitting Sample Selection Models for Discrete Response Variables
Structured Random Variables for Reliability System Distributions
Distance Sampling Detection Function and Abundance Estimation
Distance Metrics for High-Dimensional Clustering
Advanced Toolset for Efficient Time Series Dissimilarity
Analysis
DiSTATIS Three Way Metric Multidimensional Scaling
Computations over Distributed Data without Aggregation
Distributional Method for the Dichotomisation of Continuous
Outcomes
Distribution-Free Goodness-of-Fit Testing for Regression
Reconstruct a Distribution from a Collection of Quantiles
'R Markdown' Format for Scientific and Technical Writing
Method Functions for Confidence Intervals and to Distill
Information from an Object
Create and Evaluate Probability Distributions
Usual Operations for Distance Matrices in R
A Graphical User Interface for Plotting Common Univariate
Distributions
Manipulate and Combine Probability Distributions
Object Oriented Implementation of Distributions
Documentation for 'distr' Family of R Packages
S4 Classes for Elliptically Contoured Distributions
Distributional Instrumental Variable (DIV) Model
Powerful Goodness-of-Fit Tests Based on the Likelihood Ratio
Object Oriented Implementation of Probability Models
Estimate and Manage Empirical Distributions
Distribution Classes for Distributions from Rmetrics
Simulation Classes Based on Package 'distr'
Extensions of Package 'distr' for Teaching
Stochastics/Statistics in Secondary School
Estimation and Testing Classes Based on Package 'distr'
A Collection of Full Defined Distribution Tails
A Test Environment for Database Requests
Ditwah Storm Data and Tools for Storm Monitoring and Early
Warning November 2025, Sri Lanka
Early Warning Information on Landslides in Sri Lanka During the
Ditwah Storm
Diversity Dynamics using Fossil Sampling Data
Entropy Partitioning to Measure Diversity
Easily Install and Load Interactive Data Visualization Tools
Evolutionary Trait Divergence Between Sister Species and Other
Paired Lineages
Econometric Tools to Measure Portfolio Diversification
Comparative 'Phylogenetic' Analyses of Diversification
Computes Diversity Indices with Archaeological Data
Innovative Complex Split Procedures in Random Forests Through
Candidate Split Sampling
Diversity Indices with Statistical Inference
Curated Datasets and Tools for Epidemiological Data Analysis
Tools for Analysis of Diversity and Similarity in Biological
Systems
Diversity Metrics Calculations for Rasterized Data
Calculate Diversity and Segregation Indices
Spatial Subsampling of Biodiversity Occurrence Data
Nearest Neighbour Contingency Table Analysis
Dixon's Ratio Test for Outlier Detection
Record Linkage and Epidemiological Case Definitions in 'R'
Lightweight Utilities for 'DIZ' R Package Development
Utilities for 'DIZ' R Package Development
Distance Measure Based Judgment and Learning
Time Series Regression Models with Distributed Lag Models
Implementation of Adaptive or Non-Adaptive Differentiable Lasso
and SCAD Penalties in Linear Models
Distributed Loading Estimation for General Factor Model
Bayesian and Likelihood Analysis of Dynamic Linear Models
Distributed Linear Regression Models with Response Missing
Variables
Dynamic Linear Model for Wastewater-Based Epidemiology
Tools for Data Diagnosis, Exploration, Transformation
Distributed-Lag Linear Structural Equation Models
Model Based Clustering of Binary Dissimilarity Measurements
Diffusion Model of Conflict (DMC) in Reaction Time Tasks
Computational Tools for Meta-Analysis of Diagnostic Accuracy
Test
Daily Based Morgan-Morgan-Finney (DMMF) Soil Erosion Model
Dynamic Modeling and Parameter Estimation in ODE Models
Delete or Merge Regressors Algorithms for Linear and Logistic
Model Selection and High-Dimensional Data
Competing Risk in Dependent Net Survival Analysis
Generates a Fractal Image of a DNA Sequence
Diffusion Non-Additive Model with Tunable Precision
Statistical Inference for Mixed Traces of DNA (Lite-Version)
Tools for Analysing Forensic Genetic DNA Data
Dungeons & Dragons Functions for Players and Dungeon Masters
Estimating Differential Networks under Semiparametric Gaussian
Graphical Models
Deep Neural Network Tools for Probability and Statistic Models
Single-Index Neural Network for Skewed Heavy-Tailed Data
Simulate Dynamic Networks using Exponential Random Graph Models
(ERGM) Family
Probabilistic Phylogenetic Principal Component Analysis
Dimension Reduction for Outlier Detection
Data from the GLM Book by Dobson and Barnett
Groupwise Statistics, LSmeans, Linear Estimates, Utilities
Measuring Concreteness in Natural Language
Distributed Representations of Sentences, Documents and Topics
Using the Docker Container to Create R Workers on Local or Cloud
Platform
Use Docker Images to Process Rmarkdown Blocks
Layout Manager Widget for R and 'shiny' Apps
Document Conversion to 'PDF', Thumbnails and Visual Testing
Distributed Online Covariance Matrix Tests
Provides Docstring Capabilities to R Functions
Generate Tests from Examples Using 'roxygen' and 'testthat'
Run 'roxygen2' on (Chunks of) Single Code Files
Validate Brazilian Administrative Registers - Valida Documentos
Extract Data Tables and Comments from 'Microsoft' 'Word'
Documents
Full Factorials, Orthogonal Arrays and Base Utilities for DoE
Packages
Creation of Arrays by Mixed Integer Programming
Wrapper Package for Design of Experiments Functionality
Analysis of Design of Experiments for Biological Research
The Distributed Online Expectation Maximization Algorithms to
Solve Parameters of Poisson Mixture Models
Use Foreach to Parallelize via the Future Framework
Distributed Online Goodness-of-Fit Tests for Distributed
Datasets
Append DOIs to References in Word Documents
R Console Bindings for the 'Domino Command-Line Client'
Foreach Parallel Adaptor for the Rmpi Package
Nearest Neighbour Search with Variables on a Torus
Exploration of Dental Surface Topography
Analysis of Clinical Trials with the Desirability of Outcome
Ranking Methodology
'foreach' Parallel Adapter for 'parabar' Backends
Foreach Parallel Adaptor for the 'parallel' Package
'Foreach' Parallel Adapter Using the 'Redis' Database
Detection and Analysis of Dormant Patterns in Data
Generic Reproducible Parallel Backend for 'foreach' Loops
Design of Observational Studies, Companion to the Second Edition
Causal Effect Identification from Multiple Incomplete Data
Sources
Interactive Designing of Dose Finding Studies
Planning and Analyzing Dose Finding Experiments
Conduct Sensitivity Analysis with Continuous Exposures and
Binary or Continuous Outcomes
Foreach Parallel Adaptor for the 'snow' Package
Enhanced Foreign Function Interface Supporting Long Vectors
Gene-Set Analysis via Decorrelation by Orthogonal Transformation
Create and Manage Configuration Profiles
Dot-and-Whisker Plots of Regression Results
Survivor Function Estimation for Doubly Interval-Censored
Failure Time Data
Test Against Parametric Regression Function
Differential Exon Usage Test for RNA-Seq Data via Empirical
Bayes Shrinkage of the Dispersion Parameter
Enable Operators Containing the '?' Symbol
Double Constrained Correspondence Analysis for Trait-Environment
Analysis in Ecology
Create Elegant Table 1 in HTML for Bio-Statistics
Kernel Hazard Estimation with Best One-Sided and Double
One-Sided Cross-Validation
Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's
Book Measuring Market Risk
Access Federal, State, and Local Election Data
Syntax Highlighting and Automatic Linking
Implement Download Buttons in 'rmarkdown'
A Tool to Downsize Large Analysis Projects for Testing
Dynamic Path Analysis of Survival Data via Aalen's Additive
Hazards Model
Dynamic Programming for Convex Clustering
Dirichlet Process Clustering with Dissimilarities
Automated Analysis of Multiplex Digital PCR Data
Interface to Health Canada Drug Product Database API
Dynamic Programming Based Gaussian Mixture Modelling Tool for 1D
and 2D Data
The Directed Prediction Index for Causal Direction Inference
from Observational Data
RStudio Addin for Teaching and Learning Data Manipulation Using
'dplyr'
Dynamic Panel Models Fit with Maximum Likelihood
Inference of Parameters of Normal Distributions from a Mixture
of Normals
Differentially Private Statistical Analysis and Machine Learning
Determinantal Point Process Mixture Models
Density, Probability, Quantile ('DPQ') Computations
Dirichlet Quantile Bootstrap for Time Series
DPQ (Density, Probability, Quantile) Distribution Computations
using MPFR
Computation of Some Important Distributional Properties
Piecewise Linear Segmentation by Dynamic Programming
Dynamic Panel Multiple Threshold Model with Fixed Effects
Graphical User Interface for Data Quality Assessment
Core Functions for Data Quality Assessment
A BSA Software for Detecting All Types of QTLs in BC, DH, RIL
and F2
Methods for Dimension Reduction for Regression
Joint Dimension Reduction and Spatial Clustering
Dose Response Data Analysis using the 4 Parameter Logistic (4pl)
Model
Statistical Tools to Identify Dragon Kings
Drag and Drop Elements in 'Shiny' using 'Dragula Javascript
Library'
A Pipeline Toolkit for Reproducible Computation at Scale
Draw Samples with the Desired Properties from a Data Set
Data Representation: Bayesian Approach That's Sparse
Improving Estimation Efficiency in CAR with Imperfect Compliance
Consider Ambiguity in Probabilistic Descriptions Using Density
Ratio Classes
Simultaneous Clustering and (or) Dimensionality Reduction
Utilities for Data Analyses in Seed Germination/Emergence Assays
Statistical Approaches for Time-to-Event Data in Agriculture
Dynamic Relational Event Analysis and Modeling
Dose Response Models for Bayesian Model Averaging
Regularized Estimation of Dynamic Linear Regression in the
Presence of Autocorrelated Residuals (DREGAR)
DRESS - A Continuous Framework for Structural Graph Refinement
Doubly Robust Generalized Estimating Equations
Fitting Linear and Generalized Linear Models in "Divide and
Recombine" Approach to Large Data Sets
Differential Risk Hotspots in a Linear Network
Political Science Academic Research Gears
Estimating (Time-Dependent) Drift Diffusion Models
Concept Drift and Concept Shift Detection for Predictive Models
Estimation, Simulation and Reliability of Drifting Markov Models
Imputing Dropout Events in Single-Cell RNA-Sequencing Data
Discontinuous Regression and Image Processing
Prioritizing Cancer Driver Genes Using Genomics Data
Doubly Robust Matching-Adjusted Indirect Comparison for HTA
Design-Robust Meta-Analysis via Variance-Function Models
High-Performance HTTP Server for R via 'Drogon'
Data for Data Visualisation Geometries Encyclopedia
Handling Incomplete Responses in Survey Data Analysis
Doubly-Robust Estimators for Ordinal Outcomes
Statistical Modeling and Assessment of Drought
Efficient and Doubly Robust Population Size Estimation
Quality Measurements for Dimensionality Reduction
Doubly-Robust Estimation for Survival Outcomes in
Cluster-Randomized Trials
Doubly-Robust Nonparametric Estimation and Inference
Utility-Based Optimal Phase II/III Drug Development Planning
Diagnostics for OMOP Common Data Model Drug Records
Automated Analysis of 'QuPath' Output Data and Metadata
Extraction
Predict Drug Functional Similarity to Drug Repurposing
Summarise Patient-Level Drug Utilisation in Data Mapped to the
OMOP Common Data Model
Drug Repurposing in Cancer via a Subpathway Crosstalk Network
Seasonal Adjustment of Daily Time Series
Dynamical Systems Approach to Infectious Disease Epidemiology
(Ecology/Evolution)
Dynamical Systems Approach to Immune Response Modeling
Data Splitting Algorithms for Model Developments
Discretization-Based Direct Random Sample Generation
Normalize & Denoise Droplet Single Cell Protein Data (CITE-Seq)
Bayesian Subgroup Analysis in Clinical Trials
Survival Proximity Score Matching in Multi-State Survival Model
Distributed Skew Factor Model Estimation Methods
Dynamic Stochastic General Equilibrium Models
Data Science Infrastructure for Global Health in R
What Skills and Qualifications are Required for Data Science
Related Jobs?
'DataSHIELD' Implementation on Local Datasets
Density Surface Modelling of Distance Sampling Data
Estimation and Simulation of Drifting Semi-Markov Models
'DataSHIELD' Client for 'MOLGENIS Armadillo'
Dynamic Shrinkage Process and Change Point Detection
Tools for Computations with Discrete Splines
Tests and Confidence Intervals on Directly Standardized Rates
for Several Methods
A Comprehensive R Interface for the DSSAT Cropping Systems Model
The Discrete Stable Distribution Functions
Analyze Two Choice Reaction Time Data with the D*M Method
Conditional Sensitivity Analysis for Matched Observational
Studies
Demonstrated Insensitivity to Bias in 2x2xK Contingency Tables
Multiple Testing of Local Extrema for Detection of Change Points
A Wrapper of the JavaScript Library 'DataTables'
Tabular Comparison of Paired Diagnostic Tests
Cell Type Deconvolution from Gene Expressions
Creates Plots Accompanying Bayesian Diagnostic Test Accuracy
Meta-Analyses
Audit and Diagnostic Tools for 'data.table' Workflows
Diagnostic Test Assessment in the Absence of Gold Standard
Multi-Way Spherical Clustering via Degree-Corrected Tensor Block
Models
Statistical Combination of Diagnostic Tests
Comparison of Binary Diagnostic Tests in a Paired Study Design
Doubly Truncated Data Analysis, Cumulative Incidence Functions
Doubly Truncated Data Analysis, Non Iterative
Assurance Methods for Clinical Trials with a Delayed Treatment
Effect
Bayesian Optimal Phase II Randomized Clinical Trial Design with
Delayed Outcomes
Distributed Online Covariance Matrix Tests for Truncated Factor
Model
Supervised Generalized Association Plots Based on Decision Trees
Discrete Transmuted Generalized Inverse Weibull Distribution
Analysis of Diffusion Weighted Imaging (DWI) Data
A Performance-Focused Package for Clinical Trial Tables
Fetching Data from the 'Displacement Tracking Matrix'
Suite of Functions Related to Discrete-Time Discrete-State
Markov Chains
Dose Transition Pathways for Continual Reassessment Method
Interact with Data Type Registries and Create Machine-Readable
Data
Estimate and Make Inference About Optimal Treatment Regimes via
Smoothed Methods
Statistical Learning Methods for Optimizing Dynamic Treatment
Regimes
DTR Estimation and Inference via G-Estimation, Dynamic WOLS,
Q-Learning, and Dynamic Weighted Survival Modeling (DWSurv)
Dynamic Treatment Regimes for Survival Analysis
A Class for Working with Time Series Data Based on 'data.table'
and 'R6' with Largely Optional Reference Semantics
Manipulate Date, POSIXct and hms Vectors
Imputation of Time Series Based on Dynamic Time Warping
Time Series Clustering Along with Optimizations for the Dynamic
Time Warping Distance
Simplified Data Analysis with Wrapper Functions for the
'Data.Table' Package
Imputation of Multivariate Time Series Based on Dynamic Time
Warping
Automatic Differentiation with Dual Numbers
Decimated and Undecimated 2D Complex Dual-Tree Wavelet Transform
Securely Wrangle Dataset According to Data Usage Agreement
Unpacking Assignment for Lists via Pattern Matching
DBI Package for the DuckDB Database Management System
High Performance Remote File System, Database and 'Geospatial'
Access Using 'duckdb'
Simple Client for the DuckDuckGo Instant Answer API
R Interface to 'DuckDB' Database with Spatial Extension
Analysing Non-Verbal Communication in Dyadic Interactions from
Video Data
Displaying Changes Between Two Points Using Dumbbell Plots
Automatic Creation of Dummies with Support for Predictive
Modeling
Preprocessing Tools for Clinical Trial Data
Dunn's Test of Multiple Comparisons Using Rank Sums
Bayesian Inference from Count Data using Discrete Uniform Priors
Computes DNSLbetweenness, a Betweenness Measure that Includes
Self-Loops
Effect Size Estimation and Visualisation
Visualizing and Quantifying Decision Uncertainty
Analyze Dose-Volume Histograms and Check Constraints
Convenience Functions, Moving Window Statistics, and Graphics
Edit and Validate Darwin Core Taxon Data
Fast Algorithms for Large Scale Generalized Distance Weighted
Discrimination
Read Binary Radar Files from 'DWD' (German Weather Service)
Gene Expression Deconvolution Using Dampened Weighted Least
Squares
Parametric Regression for Discrete Response
Dyadic Matrices and their Algebra using 'Rcpp' and
'RcppArmadillo'
Pattern Identification for Dyadic Sequences Using Transition
Matrices
Dyad Ratios Algorithm for Latent Variable Estimation
Calibration Assistant and Post-Processing Tool for Aquatic
Ecosystem Model DYRESM-CAEDYM
Detection of Chaotic and Regular Intervals in the Data
Interface to 'Dygraphs' Interactive Time Series Charting Library
Quadratic Programming using Cyclic Projections
Dynamic Mode Decomposition Forecasting with Conformal Predictive
Sampling
Retrieve Reaction Rate Dynamics from Metabolite Concentration
Time Courses
Dynamic Simulation and Testing for Single-Equation ARDL Models
Evaluates Present Values and Health Economic Models with Dynamic
Pricing and Uptake
Species Distribution and Abundance Modelling at High
Spatio-Temporal Resolution
Methods for Detection of Clusters in Hierarchical Clustering
Dendrograms
Bayesian Modeling and Causal Inference for Multivariate
Longitudinal Data
Bringing the Power of 'Dynare' to 'R', 'R Markdown', and
'Quarto'
An Implementation of Dynamic TOPMODEL Hydrological Model in R
Algorithms for Helping Build Dynamic TOPMODEL Implementations
from Spatial Data
Full Interactive GUI for Dynamic Biplot in R
Denoising and Clustering for Dynamical Image Sequence (2D or
3D)+t
Dynamic Models for Confidence and Response Time Distributions
Dimensionality Reduction Methods in a Common Format
Emulation of Dynamic Simulators via One-Step-Ahead Approach
Resisting Neighbor Label Attack in a Dynamic Network
Random Forest with Multivariate Longitudinal Predictors
A Multi-Modal Simulator for Spearheading Single-Cell Omics
Analyses
Visualising Statistical Models using Dynamic Nomograms
Dynamic Simulations of Autoregressive Relationships
Dynamic Stem Profile Models, AKA Tree Taper Equations
Methods for Estimating Optimal Dynamic Treatment Regimes
Common Functionality for the 'dynverse' Packages
Representing and Inferring Single-Cell Trajectories
Background and Pathway Data Used in 'DysPIA'
Misc Functions of the Department of Statistics, Probability
Theory Group (Formerly: E1071), TU Wien
Ensemble Learning Framework for Diagnostic and Prognostic
Modeling
Fitting Dose-Response Models Using an Evolutionary Algorithm
Plots of the Empirical Attainment Function
Multiple Locus Association Mapping on a Genome-Wide Scale
Dynamic Web-Based Analytics for the Energy Industry
Properties of Bayesian Early Gating Designs
Estimation of Transmissibility in the Early Stages of a Disease
Outbreak
Parallel Implementation of 'ETERNA 3.40' for Prediction and
Analysis of Earth Tides
Derive a Color Palette from a Particular Location on Earth
Interactive 'shiny' GUI for the 'earth' Package
Simulating Explicit Population Genetics Models
Functions to Simplify the Use of 'glmnet' for Machine Learning
Frequently Used Functions for Easy R Programming
Efficient Approximate Bayesian Computation Sampling Schemes
Generate Alluvial Plots with a Single Line of Code
Analysis of Variance and Other Important Complementary Analyses
Extracting and Visualizing Bayesian Graphical Models
Comprehensive Single-Cell Annotation and Transcriptomic Analysis
Toolkit
Quickly Find, Extract, and Marginalize U.S. Census Tables
Easy Access to High-Resolution Daily Climate Data for Europe
Generate Comment Boxes with Custom Alignment
Easily Connect to Common Types of Databases
A Convenient Way of Descriptive Statistics
Interactive Scatter Plot and Volcano Plot Labels
Easy Model-Builder Functions for 'OpenMx'
Tools to Easily Read/Write NetCDF Files into/from
Multidimensional R Arrays
Sample Size Estimation for Experimental Designs
Reading, Formatting, and Organizing the Panel Study of Income
Dynamics (PSID)
Search and Retrieve Scientific Publication Records from PubMed
Helpful Functions from Oliver Wyman Actuarial Consulting
Easy Reference Generation for R Packages
Easy Interface to Search 'SciELO' Database
Easy Interface to the Statistical Disclosure Control Package
'sdcTable' Extended with Own Implementation of
'GaussSuppression'
Automated Statistical Analysis, Visualization and Multi-Format
Narrative Reporting
Framework for Easy Statistical Modeling, Visualization, and
Reporting
Simplify Survival Data Analysis and Model Fitting
Ensemble Forecast Verification for Large Data Sets
Easy Visualization of Conditional Effects from Regression Models
Create Constraints for Small Test Assembly Problems
Spreadsheet Interface for Relational Databases
Data Management of Large Hierarchical Data
Exponentially Weighted Moving Average with Adjustments to
Measurement Error
Educational Assessment Tools for Replication Methods
Miscellaneous Functions for the Analysis of Educational
Assessments
Deterministic Verbal Autopsy Coding with Expert Algorithm Verbal
Autopsy
Entropy Reweighting to Create Balanced Samples
Estuarine Bayesian Single-Station Estimation Method for
Ecosystem Metabolism
Empirical Bayes Thresholding and Related Methods
An Empirical Bayes Method for Chi-Squared Data
Robust Empirical Bayes Confidence Intervals
Co-Data Learning for Bayesian Additive Regression Trees
Empirical Bayes Estimation of Dynamic Bayesian Networks
Estimating Bivariate Dependency from Marginal Data
Genotyping and SNP Detection using Next Generation Sequencing
Data
Access and Analyze eBird Status and Trends Data Products
Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs
Sampling or EM-Algorithms
Ensemble-Based Methods for Class Imbalance Problem
Solve the Empirical Bayes Normal Means Problem
Ebrahim-Farrington Goodness-of-Fit Test for Logistic Regression
"Empirical Bayes Smoothing Splines with Correlated Errors"
Empirical Bayesian Tobit Matrix Estimation
An Automated Way to Estimate EC50 for Stratified Datasets
Programmatic Access to the European Central Bank's Data Portal
Translate English Sentence into Chinese, or Translate Chinese
Sentence into English
Empirical Cumulative Distribution Function Niche Modeling Tools
Statistical Tests for the Production of Reference Materials
Functions for Spatial Point Pattern Analysis
A Goodness-of-Fit Test for Elliptical Distributions with
Diagnostic Capabilities
Embedding Interactive Charts Generated with ECharts Library into
Shiny Applications
Create Interactive Graphs with 'Echarts JavaScript' Version 6
Minimal R/Shiny Interface to JavaScript Library 'ECharts'
The Echelon Analysis and the Detection of Spatial Clusters using
Echelon Scan Method
Finding Rhythms Using Extended Circadian Harmonic Oscillators
(ECHO)
Echo State Networks for Time Series Modeling and Forecasting
Efficient Calculation of Fine Structure Isotope Patterns via
Fourier Transforms of Simplex-Based Elemental Models
Graphical Visualizations for ROBUST-RCT Risk of Bias Assessments
Methods Based on the e-Closure Principle
Approximating Evidence via Bounded Harmonic Means
Interface to 'ECMWF' and 'CDS' Data Web Services
Calculating Optimum Sampling Effort in Community Ecology
Integrating Ecosystem Remote Sensing Products to Derive EBV
Indicators
Enhancing Data Quality of Biogeographic Ranges with Application
for Marine Invertebrates
Tools to Create, Use, and Convert ecocomDP Data
Graphical Modelling and Ordination using Copulas
Ordinary Differential Equation Systems in Ecology
Estimating a Diet Matrix from Biotracer and Stomach Content Data
Dissimilarity-Based Functions for Ecological Analysis
Parallel and Memory-Efficient Ecological Diversity Metrics
A General Framework for Combining Ecosystem Models
Complexity Measures for Supervised Problems
"A Practical Guide to Ecological Modelling - Using R as a
Simulation Platform"
Coalescent-Based Simulation of Ecological Communities
Ecological Inference of RxC Tables by Latent Structure
Approaches
Causal Analysis for Macroeconomic Time Series (ECM-MARS, BSTS,
Bayesian GLM-AR(1))
Easily Load and Install the 'EconDataverse'
Estimation of Parameter-Dependent Network Centrality Measures
Simulate and Sample from Ecological Interaction Networks
Computing Key Indicators of the Spatial Distribution of Economic
Activities
Community Niche Position and Width Estimation Tools
Computational Methods for Economic Complexity
Enrich and Analyze Sovereign-Level Economic Data
Null Model Analysis for Ecological Networks
Power Estimates and Equivalence Testing for Multivariate Data
Ecological Regression using Aggregate and Individual Data
Conducts Analyses Informing Ecosystem Restoration Decisions
Risk Assessments for Ecosystems or Ecosystem Components
Economic Statistics System of the Bank of Korea
Simulating Community Assembly and Ecological Diversification
Using Ecospace Frameworks
State-Space Mass-Balance Model for Marine Ecosystems
Code and Data Accompanying the Eco-Stats Text (Warton 2022)
Statistical Scaling Functions for Ecological Systems
Educational Datasets for Ecology and Agriculture
Characterising and Locating Ecotones and Communities
Collection of Data on Wildlife Sightings, Tourism Counts, and
Weather from Australia
Download and Extract Data from US EPA's ECOTOX Database
Temporal Trends in Ecological Niche Models
An Implementation of the EcoTroph Ecosystem Modelling Approach
Procedures for Ecological Assessment of Surface Waters
Lagged Cross-Correlation Analysis of Environmental Time Series
Non-Parametric Multiple Change-Point Analysis of Multivariate
Data
Quantitative Estimates of Small Ectotherm Temperature Regulation
Effectiveness
Cointegration Based Support Vector Regression Model
Cointegration Based Timedelay Neural Network Model
Equality of 2 (or k) Continuous Univariate and Multivariate
Distributions
Enhanced Coefficient of Variation and IDR Extensions for
Reproducibility Assessment
Estimate ED50 and Its Confidence Interval
Experimental Design and Analysis for Tree Improvement
Convenient Functions for Exploratory Data Analysis
Ecological Data Collection and Processing Package
Exploratory and Descriptive Event-Based Data Analysis
Read Data from European Data Format (EDF and EDF+) Files
Tool for the U.S. SEC EDGAR Retrieval and Parsing of Corporate
Filings
Retrieve Fundamental Financial Data from SEC 'EDGAR'
Algorithms for Bundling Edges in Networks and Visualizing Flow
and Metro Maps
Datasets that Support the EDGE Server DIY Logic
Local Large Language Model Inference Engine
Encapsulating Elements of Experimental Design
Modeling Urban Agriculture at City Scale
Bayesian Estimation of an Exploratory Deterministic Input, Noisy
and Gate Model
Network Reconstruction and Changepoint Detection
'DT' Extension for CRUD (Create, Read, Update, Delete)
Applications in 'shiny'
'RStudio' Addin for Editing a 'data.frame'
Model Transport of Environmental DNA in River Networks
Parsing, Applying, and Manipulating Data Cleaning Rules
An API Client for the Environmental Data Initiative Repository
Toolbox for Error-Driven Learning Simulations with Two-Layer
Networks
R Integration for Edlib, the C/C++ Library for Exact Pairwise
Sequence Alignment using Edit (Levenshtein) Distance
Dynamic Model Averaging with Grid Search
Working with Metabarcoding Data in a Tidy Format
Joint Modeling of Traditional and Environmental DNA Survey Data
in a Bayesian Framework
Implements the EDNE-Test for Equivalence
Empirical Distribution Ordering Inference Framework (EDOIF)
Analysis of NCES Education Survey and Assessment Data
Download and Process Brazilian Education Data from INEP
Retrieve Records from the Urban Institute's Education Data
Portal API
A Comprehensive Collection of Educational Datasets
Compute and Decompose Inequality in Education
Objects for Predicting Energy Expenditure
Handle Air Quality Data from the European Environment Agency
Data Portal
Explicit Exploration Strategy for Evolutionary Algorithms
Robust Analytical Methods for Evaluating Educational
Interventions using Randomised Controlled Trials Designs
Read and Preprocess Fluorescence Excitation-Emission Matrix
(EEM) Data
EEMD Based Auto Regressive Integrated Moving Average Model
Ensemble Empirical Mode Decomposition and Its Variant Based ELM
Model
EEMD Based LSTM Model for Time Series Forecasting
Ensemble Empirical Mode Decomposition and Its Variant Based
Support Vector Regression Model
EEMD and Its Variant Based Time Delay Neural Network Model
Ensemble Explainable Machine Learning Models
Tools for Pre-Processing Emission-Excitation-Matrix (EEM)
Fluorescence Data
Convenience Functions for Education Data
Eigenvectors from Eigenvalues Sparse Principal Component
Analysis (EESPCA)
Modelling Framework for the Estimation of Salmonid Abundance
Exploratory Factor Analysis Functions for Assessing
Dimensionality
Dimensionality Assessment Using Minimum Rank Factor Analysis
Determining the Number of Factors in Exploratory Factor Analysis
Fast and Flexible Implementations of Exploratory Factor Analysis
Tools
Utility Functions for Exploratory Factor Analysis
Simulate Forest Resources with the European Forestry Dynamics
Model
Wavelet-Based Enhanced FDR for Detecting Signals from Complete
or Incomplete Spatially Aggregated Data
Efficient Least Squares for Total Causal Effects
Calculate Effective Number of Clusters for a Linear Model
Statistical Consistency Checker for Published Research Results
Effect Displays for Linear, Generalized Linear, and Other Models
Visualization of Categorical Response Models
Efficient Initials for Computing the Maximal Eigenpair
Fetch Data from the Federal Reserve Economic Database
Exploratory Graph Analysis – a Framework for Estimating the
Number of Dimensions in Multivariate Data using Network
Psychometrics
Extensions for 'ggplot2': Custom Geom, Custom Themes, Plot
Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel
Size
Hierarchical Modelling of Faecal Egg Counts
Extended Generalised Linear Hidden Markov Models
Simple Presentation of Estimated Exponential Semi-Variograms
Import and Analyse Ego-Centered Network Data
Exploration and Graphics for RivEr Trends
Exploration and Graphics for RivEr Trends Confidence Intervals
Ensemble Gene Regulatory Network Inference
Leveraging eQTLs to Identify Individual-Level Tissue of Interest
for a Complex Trait
Quality Control and Semantic Enrichment of Datasets
Enhanced Help to Enable "Docstring"-Comments in Users Functions
Electronic Health Record (EHR) Data Processing and Analysis Tool
Multi-Cohort Selection Bias Correction using IPW and AIPW
Methods
Delineating Temporal Dataset Shifts in Electronic Health Records
Methodologies for Functional Data Based on the Epigraph and
Hypograph Indices
Real Datasets for Assessing Ecological Inference Algorithms
API Wrapper for U.S. Energy Information Administration ('EIA')
Open Data
Ecological Inference of RxC Tables by Overdispersed-Multinomial
Models
Utilities for Expanding Functionality of 'eiCompare'
Semiparametric Factor and Regression Models for Symmetric
Relational Data
Visualizing Probabilities, Frequencies, and Conditional
Independence for Categorical Variates
Efficiently Impute Large Scale Incomplete Matrix
Effective Information and Causal Emergence
Flexible, Powerful, and Readable Tensor Operations
Access to RFR (Risk-Free Rate) Curves Produced by the EIOPA
Ecological Inference for RxC Tables via Nonlinear Quadratic
Optimization
Ecological Inference and Higher-Dimension Data Management
Explanatory Item Response Modeling for Dichotomous and
Polytomous Items
An Algorithm for Reducing Errors-in-Variable Bias in Simple and
Multiple Linear Regressions
MCMC Procedures for Estimating Enzyme Kinetics Constants
Empirical Likelihood (EL) for Comparing Two Survival Functions
A 'shiny' Application for Exploring Laboratory Data
Elastic Analysis of Sparse, Dense and Irregular Curves
Enhanced Least Absolute Shrinkage and Selection Operator
Regression Model
Elastic Full Procrustes Means for Sparse and Irregular Planar
Curves
Database Interface to 'Elasticsearch' and 'OpenSearch'
Elastic-Net for Sparse Estimation and Sparse PCA
Electricity Load Curves Forecasting at Individual Level
Estimation of Life Expectancies Using Multi-State Models
R Functions to Download and Clean Brazilian Electoral Data
Allocating Seats Methods and Party System Scores
Load Associated Press Election Results with Elex
Kumaraswamy Complementary Weibull Geometric (Kw-CWG) Probability
Distribution
Ecological Limit Function Model Generation and Analysis Toolkit
Empirical Likelihood for General Block Designs
Sampling from a Empirical Likelihood Bayesian Posterior of
Parameters Using Hamiltonian Monte Carlo
ELISA Data Analysis with Batch Correction
Equipment for Logarithmic and Linear Time Stepwise Multiple
Hypothesis Testing
Linear, Logistic and Generalized Linear Models Regressions for
the EnvWAS/EWAS Approach
Functions for Drawing Ellipses and Ellipse-Like Confidence
Regions
Inference of Elliptical Distributions and Copulas
Weierstrass and Jacobi Elliptic Functions
Empirical Likelihood Inference of Variance Components in Linear
Mixed-Effects Models
Model-Based Gene Selection for Paired Data
Ranking Teams by Elo Rating and Comparable Methods
Preference Rating for Visual Stimuli Based on Elo Ratings
Optimized Elo Rating Method for Obtaining Dominance Ranks
Animal Dominance Hierarchies by Elo Rating
Bayesian Dominance Hierarchy Steepness via Elo Rating and
David's Scores
Entropy-Based Local Indicator of Spatial Association
Utilise Catastrophe Model Event Loss Table Outputs
Empirical Likelihood Analysis for the Cox Model and
Yang-Prentice (2005) Model
Client for the 'emailalvalidation.io' E-Mail Validation API
EM Bayesian Adaptive LASSO Variational Inference Based GWAS
Robust Bayesian Variable Selection via Expectation-Maximization
Fast Embedding Guided by Self-Organizing Map
Tools to Analyze the Thermal Reaction Norm of Embryo Growth
Energy Burden Analysis Using Net Energy Return Methodology
Bayesian Hierarchical Analysis of Cognitive Models of Choice
Evolutionary Version of the Metropolis-Hastings Algorithm
EM Algorithm for Model-Based Clustering of Finite Mixture
Gaussian Distribution
Empirical Mode Decomposition and Hilbert Spectral Analysis
Empirical Mode Decomposition Based Artificial Neural Network
Model
Support Functions and Data for "Ecological Models and Data"
Estimating and Mapping Disaggregated Indicators
Empirical Mode Decomposition Based Support Vector Regression
Model
Estimation for Binary Emax Models with Missing Responses and
Bias Reduction
Accuracy Statistic Estimation for Imperfect Gold Standards
Ecosystem Multifunctionality: Richness, Divergence, and
Regularity
Exponentially Modified Gaussian (EMG) Distribution
Expectation-Maximization Algorithm for Multivariate Normal
(Gaussian) with Missing Data
Fit a Mixture Cure Rate Model with Custom Link Function
EM Algorithms for Estimating Item Response Theory Models
Tools for Create Emissions for Air Quality Models
Evolutionary Mode Jumping Markov Chain Monte Carlo Expert
Toolbox
Read and Write Ecological Metadata Language Files
Computationally Efficient Maximum Likelihood Identification of
Linear Dynamical Systems
Organize, Handle, and Explore Ecological Multilayer Networks
Estimated Marginal Means, aka Least-Squares Means
A Mixture Model-Based Approach to the Clustering of Microarray
Expression Data
Mixture Models with Component-Wise Factor Analyzers
Semi-Supervised Gaussian Mixture Model with a Missing-Data
Mechanism
A Maximum Likelihood Approach to the Analysis of Modularity
Fitting Mixed Models with Known Covariance Structures
Access 'EMODnet' Web Feature Service Data
Tools for Environmental and Ecological Survey Design
Eye Movement Analysis Package for Fixation and Saccade Detection
Expected Maximum Profit Classification Performance Measure
Conducting the Peak Fitting Based on the EM Algorithm
Exploratory Analysis of Tabular Data using Colour Highlighting
Evaluates the Empirical Characteristic Function for Multivariate
Samples
Routines for Performing Empirical Calibration of Observational
Study Estimates
Empirical Discovery of Differential Equations from Time Series
Data
Empirical Likelihood Ratio for Censored/Truncated Data
Empirical Likelihood Ratio Test for Two-Sample U-Statistics with
Censored Data
Empirical Likelihood Ratio Test/Confidence Interval for AUC or
pAUC
Empirical Likelihood with Current Status Data for Mean,
Probability, Hazard
Test Reliability and CSEM in Educational Measurement
Epimed Solutions Collection for Data Editing, Analysis, and
Benchmark of Health Units
Some EM-Type Estimation Methods for the Heckman Selection Model
Tools for Fast Computing and Visualizing Euclidean Minimum
Spanning Trees
Exact Multinomial Test: Goodness-of-Fit Test for Discrete
Multivariate Data
Main Package of the EMU Speech Database Management System
Encuesta Nacional de Hogares (Peruvian Home National Survey)
Ensemble Methods for Multiple Change-Point Detection
Enhanced Office Open XML Charting for 'openxlsx2'
Represent Ordered Lists and Pairs as Strings
Direct Multi-Step Forecast Based Comparison of Nested Models via
an Encompassing Test
Easily Encrypt and Decrypt Data Frame/Tibble Columns or Files
using RSA Public/Private Keys
Padronizador de Endereços Brasileiros (Brazilian Addresses
Standardizer)
Recursive Two-Stage Models to Address Endogeneity
Bayesian Measurement Models for Analyzing Endorsement
Experiments
Transmissions and Receptions in an End to End Network
E-Statistics: Multivariate Inference via the Energy of Data
Goodness-of-Fit Tests for Univariate Data via Energy
Two-Sample Test of many Functional Means using the Energy Method
Distribution Free Multivariate Control Chart Based on Energy
Test
Data Published by the United States Federal Energy Regulatory
Commission
Robust and Sparse Methods for High Dimensional Linear and Binary
and Multinomial Regression
Engineering Economics Analysis for Engineering Projects Cost
Analysis
Data sets from "Introductory Statistics for Engineering
Experimentation"
Automated Tuning and Evaluations of Ecological Niche Models
Ecological Niche Modeling using Presence-Absence Data
Species Distribution Modeling and Ecological Niche Modeling
Analysis of Niche Evolution using Niche and Distribution Models
Ensemble Partial Least Squares Regression
Enrichment Analysis and Intersecting Sankey Diagram
'C++' Implementations of Functional Enrichment Analysis
Methods to Enrich R Objects with Extra Components
Probabilistic Forecasting using Ensembles and Bayesian Model
Averaging
Ensemble Taxonomic Assignments of Amplicon Sequencing Data
Human Gene Annotation Data from 'Ensembl'
Enhanced Teaching Assistant (AI) for Statistical Analysis
Estimation of Entropy, Mutual Information and Related Quantities
Estimation of Entropy and Related Quantities
Miscellaneous Functions for Environmental Analyses
Detection of Structural Changes in Climate and Environment Time
Series
Various Utilities for Microbial Genomics and Metagenomics
Environmental Interpolation using Spatial Kernel Density
Estimation
GC/LC-MS Data Analysis for Environmental Science
Isotope Pattern, Profile and Centroid Calculation for Mass
Spectrometry
Environmental Probabilistic Risk Assessment Tools
Keep Track of User-Defined Environment Names
Whole Genome Phylogenies Using Sequence Environments
Methods for Identification of Outliers in Environmental Data
Support the Setup of the R Environment for Clinical Trial
Programming Workflows
Configurable Reporting on your External Compute Environment
Package for Environmental Statistics, Including US EPA Guidance
Make Working with Environment Variables Easier and More
Consistent
Wildlife Mortality Estimator for Low Fatality Rates and
Imperfect Detection
Official R API for Fetching Data from 'EODHD'
Export or Graph and Tables to 'Microsoft' Office and Import
Figures and Tables
Data Management Package (Exposure and Occurrence Data in R)
Statistical Functions for the Censored and Uncensored
Epanechnikov Distribution
Call 'EPANET' Functions to Simulate Pipe Networks
Ensemble Penalized Cox Regression for Survival Prediction
EPE's 4MD Model to Forecast the Adoption of Distributed
Generation
Argentina's Permanent Household Survey Data and Manipulation
Utilities
Elementary Epidemiological Functions for Epidemiology and
Biostatistics
Ewnet: An Ensemble Wavelet Neural Network for Forecasting and
Epicasting
Simulating and Analysing Transmission Chain Statistics Using
Branching Process Models
Statistical and Viz Tools for Vector-Borne Diseases in Colombia
Handling, Visualisation and Analysis of Epidemiological Contacts
Epidemiological Tool for Contact Tracing
Evaluation Platform in Chronic Obstructive Pulmonary Disease
Tools to Retrieve Economic Policy Institute Data Library
Extracts
Epidemiology Data Dictionaries and Random Data Generators
Digital Epidemiological Analysis and Visualization Tools
Estimate Time Varying Reproduction Numbers from Epidemic Curves
Analysis and Simulation of Plant Disease Progress Curves
Predicting Disease Spread from Flow Data
Code Sharing at the Department of Epidemiology Research at
Statens Serum Institut
Interface Package for the 'EpiGraphDB' Platform
Nonlinear Mixed Effects Models of Epidemic Growth
Spatial and Network Based Individual Level Models for Epidemics
Miscellaneous Helper Tools for Epidemiologists
The 'epilogi' Variable Selection Algorithm for Continuous Data
A Fast and Flexible Bayesian Tool for Estimating Epidemiological
Parameters
Functions and Data for "Epidemics: Models and Data in R"
Functions and Data for "Epidemics: Models and Data in R (2nd
Edition)"
Mathematical Modeling of Infectious Disease Dynamics
Epistatic Network Modelling with Forward-Time Simulation
Flexible Extended State-Space Epidemiological Models with Modern
Inference
Estimate and Forecast Real-Time Infection Dynamics
Analysis of Omics Data in Observational Studies
Classes and Helper Functions for Working with Epidemiological
Parameters
Estimating Plant Pathogen Epidemiology Parameters from
Laboratory Assays
Tools for the Analysis of Epidemiological Data
Ensemble Based Machine Learning Approach for Predicting
Methylation States
Basic Sensitivity Analysis of Epidemiological Results
A 'Shiny' App to Simulate the Dynamics of Epidemic and Endemic
Diseases Spread
Early Detection of Public Health Threats from Social Media Data
Constructing an Epistemic Model for the Games with Two Players
Flexible Contingency Tables for Epidemiology
Test for Gene x Gene Interactions in Bi-Parental Populations
Manipulate 'EpiTrax' Data and Generate Reports
Small Helpers and Tricks for Epidemics Analysis
Data Visualisation Functions for Epidemiological Data Science
Products
Fast and Effortless Calibration of Agent-Based Models using
Machine Learning
A 'shiny' Wrapper of the R Package 'epiworldR'
Spatially Explicit Population Models of Disease Transmission in
Wildlife
Partial Linear Single Index Models for Environmental Mixture
Analysis
A Toolkit for Using Whole Building Simulation Program
'EnergyPlus'
Exploratory and Person/Item Misfit Diagnostics for Polytomous
Data
Robust Estimation of Probit Models with Endogeneity
Clinical Coding of Patients with Kidney Disease
IEEG (Intracranial Electroencephalography) Epoch Data Tools
String Interpolation for Documents, Reports and Apps
Interface to the EPPO Database and Public APIs
Exact Post Selection Inference with Applications to the Lasso
Ensemble Patch Transform, Visualization and Decomposition
Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index
Scores
Extreme Quantile Regression Neural Networks for Risk Forecasting
Comparison of Images for Researchers Without Coding Skills
Testing the Equality of Two Covariance Matrices
Testing the Equality of a High Dimensional Set of Densities
Encryption and Decryption of Files and Data for Researchers
Without Coding Skills
Algorithm Driven Time Series Analysis for Researchers without
Coding Skills
Algorithm Driven Statistical Analysis for Researchers without
Coding Skills
Equivalent Estimation Balanced Split Plot Designs
Calculate Urinary Saturation with the EQUIL2 Algorithm
Modeling, Confidence Intervals and Equivalence of Survival
Curves
Equivalence Testing for Pre-Trends in Difference-in-Differences
Designs
Provides Tests and Graphics for Assessing Tests of Equivalence
Equivalence Test for the Means of Two Normal Distributions
Testing for Equivalence and Noninferiority
Uniformly Most Powerful Invariant Tests of Equivalence
Automated Spectral Deconvolution, Alignment, and Metabolite
Identification in GC/MS-Based Untargeted Metabolomics
Nonparametric Multiple Expectile Regression via ER-Boost
Fitting Tails by the Empirical Residual Coefficient of Variation
Fit, Simulate and Diagnose Exponential-Family Models for
Networks
Fit, Simulate and Diagnose Exponential-Family Models for
Networks with Count Edges
Fit, Simulate and Diagnose Exponential-Family Random Graph
Models to Egocentrically Sampled Network Data
Fit, Simulate and Diagnose Exponential-Family Models for
Multiple or Multilayer Networks
Fit, Simulate and Diagnose Exponential-Family Models for
Rank-Order Relational Data
Exponential-Family Models for Signed Networks
Process Analysis for Exponential Random Graph Models
Exponential-Family Random Graph Models for Network Clustering
Tools for Modeling ERGM Generating Processes
Local Health Department network data set
Exponential Random Graph Models for Small Networks
Check Arguments and Generate Readable Error Messages
Significance Analysis of Event-Related Potentials Data
Bayesian Error Propagation and Forecast Uncertainty
Decomposition
Exploratory Reduced Reparameterized Unified Model Estimation
Empirically Informed Random Trajectory Generation in 3-D
Retrieve and Explore ERVISS Respiratory Virus Surveillance Data
Extended Empirical Saddlepoint Density Approximations
Indicators of Electoral Systems and Party Systems
Effect Size Computation for Meta Analysis
A Modular Approach to Dose-Finding Clinical Trials
Estimation Statistics with Confidence Intervals
Adaptive Enrichment Designs with Sample Size Re-Estimation
Ensemble Tool for Predictions from Species Distribution Models
Adaptive Clinical Trial Designs with Endpoint Selection and
Sample Size Reassessment
Exploratory Structural Equation Modeling ESEM
Data Preparation During and After the Use of the Experience
Sampling Methodology (ESM)
Preprocessing Experience Sampling Method (ESM) Data
Easy Study of Patient DICOM Data in Oncology
Explore and Visualize Your Data Interactively
Joint Quantile and Expected Shortfall Regression
Efficient Stepwise Selection in Decomposable Models
Datasets and Utilities for Essentials of Statistics for the
Behavioral Sciences
Download Data from the European Social Survey on the Fly
Fundamentos de estadística descriptiva e inferencial
Calibrating Parameters for the Samejima's Continuous IRT Model
Polynomial Maximization Method for Non-Gaussian Regression
Tools for Assessing Estimability of Linear Predictions
Estimation of Environmental Variables and Genetic Parameters
Perform the Joint Graphical Lasso and Selects Tuning Parameters
Maximum Likelihood Estimation for Probability Functions from
Data Sets
Fast Estimators for Design-Based Inference
Diagnostic Tools and Unit Tests for Statistical Estimators
Estimation of Four-Fold Table Cell Frequencies (Raw Data) from
Effect Size Measures
Estimating the Sample Mean and Standard Deviation from Commonly
Reported Quantiles in Meta-Analysis
Visualization and Estimation of Effect Sizes
Plotting Functions for Climate Science and Services
Forest Yield Tables for Northwest Germany and their Application
Modeling Earthquake Data Using 'ETAS' Model
Bootstrap Confidence Interval Estimation for 'ETAS' Model
Parameters
Mixed FLP and ML Estimation of ETAS Space-Time Point Processes
for Earthquake Description
Automated Eye Tracking Data Quality Determination for
Screen-Based Eye Trackers
Ethnobotanical Analysis, Decision-Framing, and TEK Modeling
Ethnicity Annotation from Whole-Exome and Targeted Sequencing
Data
Extract-Transform-Load Framework for Medium Data
Utility Functions to Execute Standard Extract/Transform/Load
Operations (using Package 'ff') on Large Data
Classification and Regression with Structured and Mixed-Type
Data
Analysis of Elliptical Tubes Under the Relative Curvature
Condition
Computes Moments of Univariate Truncated t Distribution
Efficient Testing Using Surrogate Information
Creates Safety Results Summary in XML to Upload to EudraCT, or
ClinicalTrials.gov
Analyse 'EuFMDiS' Output Files via a Shiny App
Area-Proportional Euler and Venn Diagrams with Ellipses
Efficient Univariate Maximum Mean Discrepancy
Standard Dataset Manager for Observational Medical Outcomes
Partnership Common Data Model Sample Datasets
Fast and Easy Eurostat Data Import and Search
R Interface to the Europe PubMed Central RESTful Web Service
Historical Populations of European Cities, 1500-1800
Extreme Value Analysis with Goodness-of-Fit Testing
Evaluation of 3D Meteorological and Air Quality Models
Evaluation Clustering Methods for Disease Subtypes Diagnosis
Tools for Evaluating Diagnostic Test Performance
Parsing and Evaluation Tools that Provide More Details than the
Default
Collection of Model Evaluation Measure Functions
Sensitivity Analyses for Unmeasured Confounding and Other Biases
in Observational Studies and Meta-Analyses
Modelling Actual, Potential and Reference Crop
Evapotranspiration
VCG Sampling using Energy-Based Covariate Balancing
Computes and Plot the Optimal Charging Strategy for Electric
Vehicles
Functions for Extreme Value Distributions
Bayesian Analysis in Extreme Value Theory
The Eigenvalues Entropy as a Classifier Evaluation Measure
A Posteriori Probs of Suits Breaking Evenly Across Four Hands
Regression Models for Event History Outcomes
Event Prediction Including Cured Population
Diagnose, Visualize, and Aggregate Event Report Level Data
Streaming Events and their Early Classification
Estimation and Visualization of Linear Panel Event Studies
Event Prediction for Time-to-Event Endpoints
Event-Specific Win Ratios for Terminal and Non-Terminal Events
Evolution Emulator: Species Diversification under an
Evolutionary Relatedness Dependent Scenario
Generalised Additive Extreme Value Models
Epidemic Volatility Index as an Early-Warning Tool
Reporting Tools for Sensitivity Analysis of Evidence Factors in
Observational Studies
Likelihood-Based Evidence Ratios for Classical Statistical Tests
Synthesizing Causal Evidence in a Distributed Research Network
Evidence Factors in Observational Studies
A Seamless Integration of 'EViews' and R
Test Dice Sets for Intransitive Properties
Inference with Extreme Value Inflated Count Data
Extreme Value Analyses with Missing Data
Extreme Value Mixture Modelling, Threshold Estimation and
Boundary Corrected Kernel Density Estimation
Extreme Value Modeling for r-Largest Order Statistics
Important Concepts of Evolutionary Game Theory
Open Software for Teaching Evolutionary Biology at Multiple
Scales Through Virtual Inquiries
Evolutionary Parameter Estimation for 'Repast Simphony' Models
Pre- And Postprocessing of Morphological Data from Relaxed Clock
Bayesian Phylogenetics
Electric Vehicle Charging Sessions Profiling and Modelling
Electric Vehicle Charging Sessions Simulation
Mean of Order P, Peaks over Random Threshold Hill and High
Quantile Estimates
Evolutionary Learning of Globally Optimal Trees
Goodness-of-Fit Tests for the Exponential and Two-Parameter
Weibull Distributions
Escalation with Overdose Control using 2 Drug Combinations
An Empirical Model for Underdispersed Count Data
Forecasting Tipping Points at the Community Level
Exact Samples Sizes and Inference for Clinical Trials with
Binary Endpoint
Exact Tests and Confidence Intervals for 2x2 Tables
Exact P-Values and Matching Confidence Intervals for Simple
Discrete Parametric Cases
Inductive Confidence Intervals for the Difference Between Two
Proportions
Admissible Exact Intervals for One-Dimensional Discrete
Distributions
Exact Test and Exact Confidence Interval for the Cox Model
Fast Extraction from Raster Datasets using Polygons
An Exact Method for Life Table Response Experiment (LTRE)
Analysis
Exact Mediation Analysis for Binary Outcomes
Exact Distributions for Rank and Permutation Tests
Help for Writing Unit Tests Based on Function Examples
Support for Compiling Examination Tasks using the 'exams'
Package
Sample and Precomputed Data for Use with 'exams.forge'
Question Generation in the 'MyLearn' XML Format
Embedding 'exams' Exercises as Forms in 'rmarkdown' or 'quarto'
Documents
Interface for 'exams' Exercises in 'learnr' Tutorials
Automatic Generation of Exams in R for 'Sakai'
Confidence/Credible Regions for Exceedance Sets and Contour
Lines
Convenient Data Exchange with Microsoft Excel
Streamline Data Import, Cleaning and Recoding from 'Excel'
A Wrapper of the 'JavaScript' Library 'jExcel'
Excerpt Structuring Comments from Your Code File and Set a Table
of Contents
Checks for Exclusion Criteria in Online Data
Creating Tables of Excluded Observations
Excursion Sets and Contour Credibility Regions for Random Fields
Quantile Maximization Likelihood Estimation and Bayesian
Ex-Gaussian Estimation
Item Selection and Exhaustive Search for Rasch Models
A Fast and Scalable Exhaustive Feature Selection Framework
A k Nearest Neibour Ensemble Based on Extended Neighbourhood
Rule
Pacote Para Analise De Experimentos Com Graficos De Superficie
Resposta
Fitting of Exponential Autoregressive (EXPAR) Model
Fitting of Exponential Autoregressive Moving Average (EXPARMA)
Model
Analyzing Human Exposure to Mosquito Biting
Modular Differential Evolution for Experimenting with Operators
R Package for Designing and Analyzing Randomized Experiments
Datasets Used in Social Science Experiments: A Hands-on
Introduction
Design of Discrete Choice and Conjoint Analysis
Incorporate Expert Opinion with Parametric Survival Models
Non-Additive Expression Analysis of Hybrid Offspring
Exponential Integral and Incomplete Gamma Function
Calculate Exploded Coordinates Based on Original Node
Coordinates and Node Clustering Membership
Interactive Interfaces for Results Exploration
A Tool for Large-Scale Exploratory Analyses
A Set of Tools for Exploratory Data Analysis
Streamlined Export of Graphs and Data Tables
Exploratory Analysis with the Singular Value Decomposition
Models Topographic Exposure to Hurricane Winds
An R Package for Mining Global Plant Diversity and Distribution
Data
Computing Expectations and Marginal Likelihoods for Permutations
Network-Based Analysis of Gene Expression Perturbations
An Exponential Stochastic Block Model for Interaction Lengths
Data Sets from "Forecasting with Exponential Smoothing"
Tables, Labels and Some Useful Functions from Spreadsheets and
'SPSS' Statistics
Fast, Reliable and Elegant Reproducible Research
Extending the Range of Functions for Probability Distributions
Survival Analysis using Indicators under Time Dependent
Covariates
Additional Families for Generalized Linear Models
Constructs the Exterior Match from Two Matched Control Groups
Maximum Penalized Likelihood Estimation with Extended Lasso
Penalty
An Extended Mallows Model and Its Hierarchical Version for
Ranked Data Aggregation
Additional Univariate and Multivariate Distributions
Holding the Database for the 'extrafont' Package
Estimation and Additional Tools for Alternative Shared Frailty
Models
Extra Binary Relational and Logical Operators
More Miscellaneous Steps for the 'recipes' Package
Power Calculation for Two-Way Factorial Designs
Astrobiology Equations Estimating Extraterrestrial Life
Extended RC Models for Contingency Tables
Realistic Confidence Intervals for Non-Stationary Extreme Value
Statistics
Estimation of Extreme Conditional Quantiles and Probabilities
Forecast Verification for Extreme Events
Bayesian Estimation of Extreme Value Mixture Models
Extreme Value Statistics and Quantile Estimation
Estimation of Extreme Value Dependence for Time Series Data
Spatial Dependencies and Indices for Extremes
Econometric Analysis of Explosive Time Series
Value Added in Exports and Other Input-Output Table Analysis
Tools
Open Source Ophthalmic Data Sets Curated for R
Import ASC Files from EyeLink Eye Trackers
Import Gaze Data for EyeLink Eye Tracker
Flexible, Extensible, & Reproducible Pupillometry Preprocessing
Organising and Analysing Eye-Tracking Data
Easy Analysis and Visualization of Factorial Experiments
Analyze and Integrate Any Type of Nucleotide Recoding RNA-Seq
Data
Easy Interface to Effective Concentration Calculations
Event Categorization Matrix Classification for Nuclear
Detonations
Compute Neural Fragility for Ictal iEEG Time Series
Easy-to-Interpret Gaussian Process Models for Computer
Experiments
Avoid the Typical Working Directory Pain When Using 'knitr'
Easy Use of R via Shiny App for Basic Analyses of Experimental
Data
Tunes AdaBoost, Elastic Net, Support Vector Machines, and
Gradient Boosting Machines
Change Point Detection in High-Dimensional Time Series Networks
'ATAforecasting' Modelling Interface for 'fable' Framework
INGARCH and GLARMA Models for Count Time Series in Fable
Framework
Core Tools for Packages in the 'fable' Framework
Overfitting Bayesian Mixtures of Factor Analyzers with
Parsimonious Covariance and Unknown Number of Components
Compute FAB (Frequentist and Bayes) Conformal Prediction
Intervals
Wrapper Functions Collection Used in Data Pipelines
Create Easily Canvas in 'shiny' and 'RMarkdown' Documents
Fast Covariance Estimation for Sparse Functional Data
Access to Facebook Ads via the 'Windsor.ai' API
Get Facebook Leads Ads Data via the 'Windsor.ai' API
Get Data from 'Facebook Organic' via the 'Windsor.ai' API
Analyze Mathematical Models of Healthcare Facility Transmission
Time Series Factor Models for Asset Returns
Characterization and Diagnostic Tools for Factorial Block
Designs
Efficiencies of Block Designs for Factorial and Fractional
Factorial Experiments
Instrumental Variables Estimation for 2^k Factorial Experiments
Combination of Factorial Methods and Cluster Analysis
Extract and Visualize the Results of Multivariate Data Analyses
Automatic Description of Factorial Analysis
Multivariate Exploratory Data Analysis and Data Mining
Factorial Optimal Designs for Two-Colour cDNA Microarray
Experiments
Post-Processing MCMC Outputs of Bayesian Factor Analytic Models
Use Raw Vectors to Minimize Memory Consumption of Factors
Factor Model Estimation with Latent Variables
Set of Assumptions for Factor and Principal Component Analysis
Factor, Bi-Factor, Second-Order and Factor Tree Copula Models
Design and Analysis for Factorial Experiments
Multifactor Nonparametric Rank-Based ANOVA with Post Hoc Tests
Estimate Heterogeneous Effects in Factorial Experiments Using
Grouping and Sparsity
Factor Model Estimation Using Proxy Variables
Eigenvalue-Based Estimation of the Number of Factors in
Approximate Factor Models
Bayesian Estimation of (Sparse) Latent Factor Stochastic
Volatility Models
Perform Factorial Analysis from 'FactoMineR' with a Shiny
Application
Multi-Environment Genomic Prediction with Penalized Factorial
Regression
Variable Selection for Supervised Classification in High
Dimension
Distributions that are Sometimes Used in Hydrology
Functional Data Clustering Using Adaptive Density Peak Detection
FDA Adverse Event Reporting System Quarterly Data Extracting
Tool
Design and Analysis of Pilot Trials Assessing Recruitment
Feasibility
Data from the Book "Multivariate Statistical Modelling Based on
Generalized Linear Models", First Edition, by Ludwig Fahrmeir
and Gerhard Tutz
Fair Data Adaptation with Quantile Preservation
Fair Gated Algorithm for Targeted Equity
Ontology Tools with Data FAIRification in Development
Fairness Evaluation Metrics with Confidence Intervals for Binary
Protected Attributes
Flexible Tool for Bias Detection, Visualization, and Mitigation
Flexible Data Simulation Using the Multivariate Normal
Distribution
Privacy-Preserving Synthetic Data for 'LLM' Workflows
Generate Fake Datasets for Prototyping and Teaching
Fuzzy Adaptive Resonance Theory K-Means Clustering Technique
Finding Allele-Specific Copy Number in Next-Generation
Sequencing Data
Finding Allele-Specific Copy Number in Whole-Exome Sequencing
Data
Family Age-at-Onset Data Simulation and Penetrance Estimation
Statistical Tests of Familial Hypotheses
End-to-End Automated Machine Learning and Model Evaluation
Probabilities for Pedigrees Given DNA Data
Kinship Ties in (Virtual) Multi-Generation Populations
Flexibly Tune Families of Probability Distributions
Maximum Likelihood and Bayesian Estimation of Univariate
Probability Distributions
A Flexible Algorithm for Model Selection
Family Sequence Kernel Association Test for Rare and Common
Variants
Feature Allocation Neighborhood Greedy Search Algorithm
Visualisation of Sequential Probability Distributions Using Fan
Charts
ANSI Control Sequence Aware String Functions
Translate Words or Sentences via Online Translators
Evapotranspiration Based on FAO Penman-Monteith Equation
Influential Case Detection Methods for Factor Analysis and
Structural Equation Models
Factor Analytic Profile Analysis of Ipsatized Data
Modelization for Functional AutoRegressive Processes
Datasets and Functions for Books by Julian Faraway
Fast and Robust Deconvolution of Tumor Infiltrating Lymphocyte
from Expression Profiles using Least Trimmed Squares
Data and Code for Empirical Research in Accounting
Interactive Interface to Data Envelopment Analysis Modeling
High Performance Colour Space Manipulation
Factor-Augmented Sparse Regression Tuning-Free Testing
Fasano-Franceschini Test: A Multivariate Kolmogorov-Smirnov
Two-Sample Test
Rmetrics - Analysing and Modelling Financial Assets
Fast Additive Switching of Seasonality, Trend, and Exogenous
Regressors
Analyze, Summarize, and Visualize Daily Streamflow Data
Analyze and Visualize FAST-Generated Data
Self-Tuning Data Adaptive Matrix Imputation
Fast Regression for the Accelerated Failure Time (AFT) Model
Fast Backward Elimination Based on Information Criterion
Fast Estimation of a Covariance Matrix by Banding the Cholesky
Factor
Fast Approximation of Time-Varying Infectious Disease
Transmission Rates
Scalable and Flexible Derivation of Custom-Time Bioclimatic and
Environmental Summary Variables
Fast Hierarchical Clustering Routines for R and 'Python'
Lasso and Elastic-Net Penalized Cox's Regression in High
Dimensions Models using the Cocktail Algorithm
Fast Change Point Detection via Sequential Gradient Descent
Fast Estimation of CUB Models via Louis' Identity
Fast Creation of Dummy (Binary) Columns and Rows from
Categorical Variables
Methods for ''A Fast Alternative for the R x C Ecological
Inference Case''
Faster Raster and Spatial Vector Processing Using 'GRASS'
Fast Functional Generalized Estimating Equations via a One-Step
Estimator
Fast Functional Mixed Models using Fast Univariate Inference
Fast Multiscale Raster Extraction and Moving Window Analysis
with FFT
Fast and Exact Computation of Gaussian Stochastic Process
High-Performance 'GeoJSON' and 'JSON' Serialization
Fast 'Rcpp' Implementation of Gauss-Hermite Quadrature
Fast and Stable Fitting of Generalized Linear Models using
'RcppEigen'
Fast Algorithms for Generalized Principal Component Analysis
Efficiently Using Gaussian Processes with Rcpp and RcppEigen
Fast Drawing and Shading of Graphs of Statistical Distributions
Fast Computation of Pairwise Hamming Distances
FastICA Algorithms to Perform ICA and Projection Pursuit
Learn from Training Data then Quickly Fill in Missing Data
Semi-Parametric Joint Modeling of Longitudinal and Survival Data
Efficient Jonckheere-Terpstra Test Statistics for Robust Machine
Learning and Genome-Wide Association Studies
A Fast Multiple-Kernel Method Based on a Low-Rank Approximation
Faster K-Medoids Clustering Algorithms: FastPAM, FastCLARA,
FastCLARANS
A Fast Algorithm for Kernel Quantile Regression
Kernel Ridge Regression using 'RcppArmadillo'
Fast Probabilistic Record Linkage with Missing Data
Fast Functions for Liu Regression with Regularization Parameter
and Statistics
Fast Local Polynomial Regression and Kernel Density Estimation
Fast Computation of Multivariate M-Estimators
High-Performance Matrix Market File Operations
Fast Computation of some Matrices Useful in Statistics
Fast Mutual Information Based Independence Test
Guarded Resampling Workflows for Safe and Automated Machine
Learning in R
Extremely Fast Implementation of a Naive Bayes Classifier
FastPCS Robust Fit of Multivariate Location and Scatter
A Fast Implementation of Partial Least Square
Fast Alternatives to 'tidyverse' Functions
Read and Write PNG Files with Configurable Decoder/Encoder
Options
Constructs Policy Trees from Covariate and Reward Data
Finds the Critical Sequential Point of Stability for a Pearson
Correlation
Faster Generation of Quantile Quantile Plots with Large Samples
Fast Algorithms for Quantile Regression with Selection
Foundations and Applications of Statistics Using R (2nd Edition)
Fast Reverse Complement of DNA and RNA Sequences
Fits the FastRCS Robust Multivariable Linear Regression Model
Fast Conversion and Querying of Danish Registers with 'Parquet'
Time-Saving Package for Creating Reports
Hardware-Accelerated Rerandomization for Improved Balance
Retention Time Prediction in Liquid Chromatography
Sample Generalized Random Dot Product Graphs in Linear Time
Functions to Access Premier Hockey Federation and National
Hockey League Play by Play Data
Fast Interactive Framework for Web Scripting Using R
A Fast Algorithm for Sparse Precision Matrix Estimation
Efficient Learning of Word Representations and Sentence
Classification
Fast Utility Function for Time Parsing and Conversion
Fast Algorithms for Fitting Topic Models and Non-Negative Matrix
Factorizations to Count Data
Identifies Parameters in a Tree-Shaped SCM
Fast Time Series Modeling for Seasonal Series with Exogenous
Variables
A Suite of High-Performance Packages for Statistics and Data
Manipulation
Efficient Voting Methods for Committee Selection
Compute Maximal Overlap Discrete Wavelet Transform (MODWT) and À
Trous Discrete Wavelet Transform
Fast Utilities for Year Month Day Objects
Two-Locus Family-Based Association Test with Polytomous Outcome
Quantification of Fate Bias in Multipotent Progenitors
Kiener Distributions and Fat Tails in Finance and Neuroscience
Fault Trees for Risk and Reliability Analysis
Explore Catálogo Taxônomico da Fauna do Brasil Database
Quantify Compositional Variability Across Relative Abundance
Vectors
'Font Awesome' Icons as 'shiny' 'favicons'
Find the URL to the 'Favicon' for a Website
Functions and Datasets for "Forest Analytics with R"
'Fish Bioenergetics 4.0' Model Implementation with
High-Performance 'TMB' Backend
Fourier Bootstrap ARDL Cointegration Test
Gene by Environment Interaction and Conditional Gene Tests for
Nuclear Families
Algorithm for Searching the Space of Gaussian Directed Acyclic
Graph Models Through Moment Fractional Bayes Factors
Flexible Bayesian Model Selection and Model Averaging
FISH Based Normalization and Copy Number Inference of SNP
Microarray Data
Analyzing and Managing Facebook Ads from R
Fast Algorithms to Bootstrap Receiver Operating Characteristics
Curves
The Full Bayesian Evidence Test, Full Bayesian Significance Test
and the e-Value
Floating Catchment Area (FCA) Methods to Calculate Spatial
Accessibility
Parse Farm Credit Administration Call Report Data into Tidy Data
Frames
Functional Change Point Detection and Analysis
Inference of Fuzzy Cognitive Maps (FCMs)
Flexible Cutoffs for Model Fit Evaluation in Covariance-Based
Structural Models
Rmetrics - Bivariate Dependence Structures with Copulae
A Method to Search for Differentially Expressed Genes and to
Detect Recurrent Chromosomal Copy Number Aberrations
Estimation and Inference for the Fractionally Cointegrated VAR
Measuring Functional Diversity (FD) from Multiple Traits, and
Other Tools for Functional Ecology
Functional Data Analysis and Utilities for Statistical Computing
Autocorrelation Function for Functional Time Series
Joint Clustering and Alignment of Functional Data
Concurrent Regression and History Index Models for Functional
Data
Functional Data Analysis for Density Functions by Transformation
to a Hilbert Space
Functional Data Analysis in a Mixed Model Framework
Model-Based Clustering for Functional Data with Covariates
Analysis of Variance for Univariate and Multivariate Functional
Data
Outlier Detection Tools for Functional Data Analysis
Functional Data Analysis and Empirical Dynamics
Physics-Informed Spatial and Functional Data Analysis
Partially Observed Integrated Functional Depth
Two-Dimensional FPCA, Marginal FPCA, and Product FPCA for
Repeated Functional Data
Interval Testing Procedure for Functional Data
Supervised Classification for Functional Data via Signed Depth
Fast Implementation of the Diffusion Decision Model
Optimal Experimental Designs for Dynamic/Functional Models
Data Mining and R Programming for Beginners
Dynamic Model Averaging and Dynamic Model Selection for
Continuous Outcomes
Optimal Transport Based Testing in Factorial Design
f-Differential Privacy and Gaussian Differential Privacy
Permutation-Based FDR Point and Confidence Interval Estimation
False Discovery Rate Procedures Under Discrete and Heterogeneous
Null Distributions
Estimate, Plot, and Summarize False Discovery Rates
Computing Power and Sample Size for the False Discovery Rate in
Multiple Applications
Compute Sample Size that Meets Requirements for Average Power
and FDR
Estimation of (Local) False Discovery Rates and Higher Criticism
Frequency Distribution Tables, Histograms and Polygons
Application of Optimal Transport to Functional Data Analysis
False Discovery Exceedance Controlling Multiple Testing
Procedures
Feature Extraction and Statistics for Time Series
Incremental Feature Engineering with Database Persistence
Automated Feature Engineering for Credit Scoring
Local Inferential Feature Significance for Multivariate Kernel
Density Estimation
Measurement Level Independent Feature Correlation Matrix
Turn Features On and Off using Feature Flags
Feature Importance for Partitional Clustering
Feature Extraction for Discretely-Sampled Functional Data
Feature Selection Engine to Remove Features with Minimal
Predictive Power
Some Helper Functions that Help Create Features from Data
Data Package for the 2016 United States Federal Elections
Download Geospatial Data Available from Several Federated Data
Sources
Client Package for the U.S. Federal Register API
Fast, Flexible, and User-Friendly Record Linkage Methods
Unofficial API for Fedstat (Rosstat EMISS System) for Automatic
and Efficient Data Queries
An Easier Access to Financial Accounts of the United States(Z.1)
Estimate the First-Exposure Effect (FEE) using Count Data Models
SM/LM EGARCH & GARCH, VaR/ES Backtesting & Dual LM Extensions
Estimating Fixed Effects Individual Slope Models
Fixed Effect Jackknife Instrumental Variables Estimation
Functional Help for Functions, Objects, and Packages
Fixed Effects Nonlinear Maximum Likelihood Models
Fixed Effects Logistic Model with High-Dimensional Parameters
Facilitate Exploration of touRR optimisatioN
Process Data from the Social Networks and Fertility Survey
Get Data from Google Analytics via the 'Windsor.ai' API
Get Data from Salesforce via the 'Windsor.ai' API
Rmetrics - Modelling Extreme Events in Finance
Memory-Efficient Storage of Large Data on Disk and Fast Access
Functions
Download Data from Kenneth French's Website
R Interface to 'FFIEC Central Data Repository REST API' Service
Download Official Spatial Data from Germany
Fully Flexible Probabilities for Stress Testing and Portfolio
Construction
API Client for Fantasy Football League Platforms
Tidy Manipulation of Fourier Transformed Data
Generate, Visualise, and Evaluate Fast-and-Frugal Decision Trees
Fast FFT and DCT Based on the FFTW Library
Wrapper for 'FFTW3' Includes: One-Dimensional, Two-Dimensional,
Three-Dimensional, and Multivariate Transforms
Rmetrics - Autoregressive Conditional Heteroskedastic Modelling
Access Small ForestGEO Datasets For Examples
Using 'FastGit' to Accelerate the Access to 'GitHub'
Truncated Functional Generalized Linear Models
A Feasible Generalized Least Squares Estimator for Regression
Analysis of Outcomes with Network Dependence
Functional Genomics Repository for POST-GWAS Analysis
Fractional Hot Deck and Fully Efficient Fractional Imputation
Fitting Hidden Markov Models to Financial Data
Tests for Right and Interval-Censored Survival Data Based on the
Fleming-Harrington Class
Provide Functions for Forest Inventory Calculations
Occlusion Surface Using the Occluded Surface and Fibonacci
Occluded Surface
Focused Information Criteria for Model Comparison
Classical, Reloaded and Adaptive FastICA Algorithms
Bayesian Multinomial Logistic Normal Regression
A Shiny App for Design of Experiments in Life Sciences
Simulation of Plot Errors and Phenotypes in Plant Breeding Field
Trials
A Lightweight and Flexible Web Framework
Forest Inventory Estimation and Analysis
Utility Functions for Forest Inventory Estimation and Analysis
Check Validity of FIGI, CUSIP, ISIN, SEDOL
Easily Arrange External Figures with Patchwork Alongside
'ggplot2' Figures
Transform Files to 'microtable' Object with 'microeco' Package
File-Backed Array for Out-of-Memory Computation
Wrapper for the Filebin File Sharing API
File-Backed Matrix Class with Convenient Read and Write Access
Effective File Navigation from the R Console
Data Utilities for Congressional Research
Matrix Completion, Imputation, and Inpainting Methods
Patterned Fills for 'ggplot2' and 'grid' Graphics
IMDb Film Ratings from the Summer of 2022
Feature Selection Using Supervised Filter-Based Methods
Rmetrics - Importing Economic and Financial Data
Quickly Create Elegant Regression Results Tables and Plots when
Modelling
Financial Analysis and Regression Diagnostic Analysis
Flexible Graphs for Analysis of Financial Data and Time Series
Interface for the 'Finnish Biodiversity Information Facility'
API
Time Value of Money, Time Series Analysis and Computational
Finance
Covariance Matrix Estimation and Regularization for Finance
Objective Comparison of Phase I Dose-Finding Designs
Estimate Genome Size of Polyploid Species Using k-Mer
Frequencies
Find Pattern in Files of All Branches of a 'git' Repository
Functions to Find an Acceptable Python Binary
Find Code Snippets, R Scripts, R Markdown, PDF and Text Files
with Pattern Matching
Calculate Social Vulnerability Index for Communities
A View Generator for Multidimensional Data
Functions to Operate on Binary Fingerprint Data
Computation of the Probability of Ruin Within a Finite Time
Horizon
Test for Finiteness of Moments in a Distribution
Portfolio Analytics and Simulation Toolkit
Quickly Build and Manipulate Financial Networks
Analyse Open-Ended Survey Responses in Finnish
Microsoft Finance Time Series Forecasting Framework
Companion to Tsay (2005) Analysis of Financial Time Series
Regional and Multi-Regional Input-Output Data
Mass-Spectra Prediction Using the FIORA Model
Lightweight Federal Information Processing System (FIPS) Code
Information Retrieval
Integrates 'Google Firebase' Authentication Storage, and
'Analytics' with 'Shiny'
R Wrapper for 'Firebase Authentication REST API'
Authentication and Authorization for 'fiery' Servers
A Collection of Security Related Plugins for 'fiery'
Reverse Proxy and Load Balancing for 'fiery'
Flexible Integration of Single-Cell RNA-Seq Data
Robust Probabilistic Matching for German Company Names
Factor Importance Ranking and Selection using Total Indices
A Small Collection of Fish Population Datasets
Classify Aquatic Animal Behaviours from Vertical Movement Data
The FisherEM Algorithm to Simultaneously Cluster and Visualize
High-Dimensional Data
Transform Base Maps Using Log-Azimuthal Projection
Dataset of Measurements of Fish Species at Kirkkojarvi Lake,
Finland
Computes Kinematic Parameters for Swimming
Fits Poisson-Sum-of-Gammas GLMs, Tweedie GLMs, and Delta
Log-Normal Models
Phylogenies for a List of Finned-Ray Fishes
Proximate Composition Analysis of Fish and Feed Ingredients
Global Fishery and Aquaculture Statistics
Fuzzy Inference System Design and Optimization
Distribution Fitting with Calibrating Priors for Commonly Used
Distributions
Help to Fit of a Parametric Distribution to Non-Censored or
Censored Data
Mean and Covariance Matrix Estimation under Heavy Tails
Fit Vector Fields and Potential Landscapes from Intensive
Longitudinal Data
Finite Mixture Model Fitting of Lifespan Datasets
Multidimensional Nuclear Magnetic Resonance Peak Fitting and
Analysis
Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD
'Shiny' Application for R Package 'fitODBOD'
Genotype Calling for Bi-Allelic Marker Assays
Classes for Fitness Landscapes and Seascapes
FITS (Flexible Image Transport System) Utilities
Fit Hundreds of Theoretical Distributions to Empirical Data
Fit Univariate Mixed and Usual Distributions
Fit the Vector Autoregressive Model for Multiple Individuals
Data and Code Behind the Stories and Interactives at
'FiveThirtyEight'
Algorithms for Finding Fixed Point Vectors of Functions
The Distribution of Distances Between Discrete Events in Fixed
Time
An R Client for the "Fixer.io" Currency API
Tools for Creating and Visualizing Fixed-Effects Event Study
Models
Fixing Data Made Easy for Statistical Analysis
Fixed Sequence Multiple Testing Procedures
Data Frame Joins Leveraging 'data.table'
Available Light Within the Water Column and on the Seafloor of
Arctic Fjords
Functional K-Centroids Clustering Using Phase and Amplitude
Components
Fast Kalman Filtering Through Sequential Processing
Fréchet Distance-Based K-Means and Extensions for Longitudinal
Data
Feature-Based Landscape Analysis of Continuous and Constrained
Optimization Problems
Flexible and Accurate Gaussian Graphical Models
Fits Piecewise Constant Models with Data-Adaptive Knots
Interpretable Matching for Causal Inference
Implementing Computational Models of Attentional Selectivity
Implementation of Fast Hierarchical Clustering
Shed Light on Black Box Machine Learning Models
Fast and Scalable Single Cell Differential Expression Analysis
using Mixed-Effects Models
Create Flashcards of Terms and Definitions
Penalized Estimation for Multi-State Models with Lasso and Fused
Penalties
Transforms Contingency Tables to Data Frames, and Analyses Them
Obtaining a Flat Table from Pivot Tables
Tools for Working with XML Files as R Dataframes
Smoother Change Tracking and Versioning for R Packages
Flexible, Ensemble-Based Variable Selection with Potentially
Missing Data
Fuzzy Linear Squares Estimation with Explicit Formula (FLEX)
Fast & Flexible Implementation of Bayesian Causal Forests
Causal Effect Estimation via Doubly Robust One-Step Estimators
and TMLE in Graphical Models with Unmeasured Variables
Estimation of a Variety of Count Regression Models
R Markdown Format for Flexible Dashboards
Tools to Work with the Flexible Dirichlet Distribution
Flexible Non-Linear Least Square Model Fitting
Generalized Additive Models with Flexible Response Functions
Dynamic Failure Rate Distributions for Survival Analysis
Flexible Latent Trait Metrics using the Filtered Monotonic
Polynomial Item Response Model
A General Framework for Flexible Multi-State Survival Modelling
Flexible Clustering of Ordinal and Mixed-with-Ordinal Data
Regression Models for Bounded Continuous and Discrete Responses
Breaks Single Page Applications from 'flexdashboard' in Multiple
Files
Flexible Parametric Survival and Multi-State Models
Estimate Joint Models with Subject-Specific Variance
Reconstruct Animal Paths from Solar Geolocation Loggers Data
Download Flight and Airport Data from Brazil
Simple and Flexible Tests of Sample Exchangeability
Parses Code, Creates Partial Code Builds, Delivers Code Movie
Implement a Countdown in 'RMarkdown' Documents and 'shiny'
Applications
A Wrapper of JavaScript Library 'flipdown.js'
Flexible Inference via Permutations in R
Robust Score Testing in GLMs, by Sign-Flip Contributions
Process Synchronization Using File Locks
Statistical Methods for the (Regional) Analysis of Flood
Frequency
Flood Probability Plotting and Graphical Frequency Analysis
Tools for Interacting with the Brazilian Flora 2020
Explore Flora e Funga do Brasil Database
Fit Log-Ratio Lasso Regression for Compositional Data
View and Browse Code Using Flow Diagrams
Reciprocity Indices for Style-Polymorphic Plants
Draw Flows (Migration, Goods, Money, Information) on 'ggplot2'
Plots
Transport Modeling: Network Processing, Route Enumeration, and
Traffic Assignment
The Environmental Costs of Flow Regulation
Daily Streamflow Trend and Change Point Screening
Tracing Information Flow for Inter-Software Comparisons in Mass
Spectrometry-Based Bottom-Up Proteomics
Path Algorithm for the General Fused Lasso Signal Approximator
Mining Rigs for Problems in the Subset Sum Family
Analysis of Chlorophyll a Fluorescence Transient Parameters
Estimate Insect Survival from Fluorescence Data
Parsing, Computation, and Diagnostics for Greenhouse Gas
Measurements
Advanced Framework for Sap Flow Data Post-Process
Ecosystem Gas Fluxes Calculations for Closed Loop Chamber Setup
Change Point Detection for Non-Stationary and Cross-Correlated
Time Series
Separation of Diffusive and Ebullitive Fluxes
A 'shiny' App for Reproducible QA/QC of Eddy Covariance Data
Data Sets from "Forecasting: Methods and Applications" by
Makridakis, Wheelwright & Hyndman (1998)
Factorial Experiments with Minimum Level Changes
Finite Mixture of Censored Regression Models with Skewed
Distributions
A Flexible Modelling Environment for Inverse Modelling,
Sensitivity, Identifiability and Monte Carlo Analysis
Model-Agnostic Interpretations with Forward Marginal Effects
Triangle Meshes and Related Geometry Tools
Hierarchical Permutation Tests for Functional Measurement
Invariance
Rhythmic Patterns Modeling by FMM Models
Filtered Monotonic Polynomial IRT Models
Flexible Client for the 'Financial Modeling Prep' API
R Access to the 'FMP Cloud' and 'Financial Modeling Prep' API
Fast AR and ARMA Noise Whitening for Functional MRI (fMRI)
Design and Data
Hemodynamic Response Functions for fMRI Data Analysis
Functional MRI Quality Assurance Routines
Scrubbing and Other Data Cleaning Routines for fMRI
Routines for Common fMRI Processing Tasks
Functions for Medical Statistics Book with some Demographic Data
Regression Models with Finite Mixtures of Skew Heavy-Tailed
Errors
Variance Estimation of FMT Method (Fully Moderated T-Statistic)
Rmetrics - Modeling of Multivariate Financial Return
Distributions
Factor-Adjusted Network Estimation and Forecasting for
High-Dimensional Time Series
Fast Nearest Neighbor Search Algorithms and Applications
Rmetrics - Nonlinear and Chaotic Time Series Modelling
Inbreeding and Numerator Relationship Coefficients
Numerical Tools for 'Rcpp' and Lambda Functions
Feature Ordering by Conditional Independence
Coherent Forecast Combination for Linearly Constrained Multiple
Time Series
Online Changepoint Detection in Univariate and Multivariate Data
Streams
Summarize CRAN Check Results in the Terminal
Forward Stepwise Discriminant Analysis with Pillai's Trace
Datasets for Teaching Archaeology and Paleontology
Add Extra 'Fomantic UI' Components to 'shiny.semantic'
Easy Estimation and Vizualisation of Indicators from Data with
Complex Design
Fonts with 'Bitstream Vera Fonts' License
Computer Modern Font for Use with Extrafont Package
Food Quotient and Nutrient Analysis for HSFFQ
Enhanced Wrapper to Show Which Functions Call What
Penalties in the German Men's Football Bundesliga
Fitting Bayesian and MLE Football Models
Field Observation Quick Analysis Toolkit
Organization Measures for Visual Foraging
Foraminifera and Community Ecology Analyses
Tools for Working with Categorical Variables (Factors)
A Curated Collection of 'Causal Inference' Datasets and Tools
Feature Ordering by Integrated R Square Dependence
Forest Many-Objective Robust Decision Making ('FoRDM')
Forecasting Functions for Time Series and Linear Models
Convenient Functions for Ensemble Time Series Forecasts
Time Series Forecasting Using 23 Individual Models
Forecasting Routines for Locally Stationary Wavelet Processes
Forecast Reconciliation with Machine Learning
Size-Power Tradeoff Visualization for Equal Predictive Ability
of Two Forecasts
Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata',
'Systat', 'Weka', 'dBase', ...
Allele Frequency Data for Human Genetic Markers
Systems Insights from Generation of Hydroclimatic Timeseries
Forest Carbon Sequestration and Potential Productivity
Calculation
Balancing Confounder Distributions with Forest Energy Balancing
Approximate False Positive Rate Control in Selection Frequency
for Random Forest
Fitting and Assessing Neighborhood Models of the Effect of
Interspecific Competition on the Growth of Trees
Data Structures and Functions for Working with Forest Data
A Unified Framework for Random Forest Prediction Error
Estimation
Statistical Modelling for Plant Size Distributions
Forest Growth and Yield Model Based on Clutter Model
Forest Health Evaluation System at the Forest Stand Level
Design-Based Global and Small-Area Estimations for Multiphase
Forest Inventories
Advanced Forest Plot Using 'grid' Graphics
Ecosystem and Canopy Structural Complexity Metrics from LiDAR
Forest Spatial Structure Analysis Systems
Exploratory Subgroup Identification in Clinical Trials with
Survival Endpoints
Tools for Analyzing Remote Sensing Forest Data
Projecting Customer Retention Based on Fader and Hardie
Probability Models
Convert Formatted Spreadsheets to Presentation-Ready Display
Tables
Functions to Estimate Tree Volume and Phytomass in the Italian
Forest Inventory 2005
'ForLion' Algorithm to Find D-Optimal Designs for Experiments
Formatting Numbers in 'rmarkdown' Documents
A Simple Connection Between the 'FormShare App' and 'R' for
Advanced Analytics
Programmatic Utilities for Manipulating Formulas, Expressions,
Calls, Assignments and Other R Objects
Dynamic Generation and Quality Checks of Formula Objects
Comprehensive Tools for Drug Formulation Analysis and
Visualization
Forensic Pedigree Analysis and Relatedness Inference
String Manipulation Package for Those Familiar with 'Microsoft
Excel'
Automatic Processing of Terrestrial-Based Technologies Point
Cloud Data for Forestry Purposes
Palaeoecological and Palaeogeographical Analysis Tools
Automated Cleaning of Fossil Occurrence Data
Simulation and Plots for Fossil and Taxonomy Data
'Palantir Foundry' Software Development Kit
A Game for Human vs. Human or Human vs. AI
Parsimonious Hidden Markov Models for Four-Way Data
Utilities for Joining Dataframes with Inexact Matching
Power and Sample Size for Projection Test under Repeated
Measures
Three Dimensional Functional Component Analysis
The FPCdpca Criterion on Distributed Principal Component
Analysis
Reliable Comparison of Floating Point Numbers
Automatic Distribution Graphs Using Formulas
Segmentation using Optimal Partitioning and Function Pruning
Weighted Segmentation using Functional Pruning and Optimal
Partioning
Rmetrics - Portfolio Selection and Optimization
Computing the Noncentrality Parameter of the Noncentral F
Distribution
Data for "Forecasting: Principles and Practice" (2nd Edition)
Data for "Forecasting: Principles and Practice" (3rd Edition)
Fast Partial Receiver Operating Characteristic (ROC) Test for
Ecological Niche Modeling
Compute Measures of Foreign Policy Similarity/Agreement
Approximation of First-Passage-Time Densities for Diffusion
Processes
Calculate Floristic Quality Assessment Metrics
Contains Regional Floristic Quality Assessment Databases
Floristic Quality Assessment Tools for R
Fourier ARDL Methods: Quantile, Nonlinear, Multi-Threshold &
Unit Root Tests
Fractionally Differenced ARIMA aka ARFIMA(P,d,q) Models
Numerical CDFs for Fractional Unit Root and Cointegration Tests
Compositional Statistical Framework for RNA Fractionation
Analysis
Fraction Proliferation via a Quiescent Growth Model
Simulation and Parameter Estimation of Randomized Sierpinski
Carpets using the p-p-p-q-Model
Estimation of Fractal Dimension of a Black Area in 2D and 3D
(Slices) Images
Assessing and Visualizing Fragility of Clinical Results with
Binary Outcomes
Competing Risks Models for Multi-Center Survival Data with
Frailty
Fitting Frailty Models with the EM Algorithm
Frailty Models via Hierarchical Likelihood
Efficient Algorithm for High-Dimensional Frailty Model
Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints
Time-Dependent ROC Curve Estimation for Correlated
Right-Censored Survival Data
General Semiparametric Shared Frailty Model
Structured Data Science Project Scaffolding
Financial Risk Modelling and Portfolio Optimisation with R
FRAP Data Analysis Using Nonlinear Mixed Effect Models with
'shiny'
Automatic Data Processing and Visualization for FRAP
Fuzzy Rule-Based Systems for Classification and Regression Tasks
Fast Regularized Canonical Correlation Analysis
Statistical Analysis for Random Objects and Non-Euclidean Data
Estimation and Inference for High Dimensional Mediation and
Surrogate Analysis
'FreeBSD' Contributor and Commit Statistics
Client for the 'freecurrencyapi.com' Currency Conversion API
Read and Write 'FreeSurfer' Neuroimaging File Formats
Tree Method for High Dimensional Longitudinal Data
A Wrapper of the JavaScript Library 'Freewall'
Rmetrics - Regression Based Decision and Prediction
Generate Open or Closed Interpolating Curves
Download Data Sets from Kenneth's French Finance Data Library
Site
FREQ: Estimate population size from capture frequencies
Automated Cumulative Frequency Plots for Grouped Distribution
Frequency Domain Based Analysis: Dynamic PCA
Estimates Allele Frequency on qPCR DeltaDeltaCq from Bulk
Samples
Frequency Profiles Computing and Plotting
Make Quick Descriptive Tables for Categorical Variables
Spectral Decomposition of Connectedness Measures
Implementation of Frequent-Directions Algorithm for Efficient
Matrix Sketching
Screened Selection Design with Survival Endpoints
Screened Selection Design with Binary Endpoints
Feature Selection Algorithms for Computer Aided Diagnosis
Create Custom 'Bootstrap' Themes to Use in 'Shiny'
Fractional Factorial Designs with 2-Level Factors
Catalogues of Resolution IV 128 Run 2-Level Fractional
Factorials Up to 33 Factors that Do Have 5-Letter Words
Relative Importance of Main and Interaction Effects
Read and Write Frictionless Data Packages
The Entire Transcript from Friends in Tidy Format
Utilities for the Forest Research Institute of the State
Baden-Wuerttemberg
Emulate a 'Forth' Programming Environment
Calculate the Fit-Robustness of CNA-Solutions
A Blazing Fast Implementation of Random Forest
Evaluation Tools for Assessing Climate Adaptation of Fruit Tree
Species
Cross-Platform File System Operations Based on 'libuv'
Simple Fisheries Stock Assessment Methods
Data to Support Fish Stock Assessment ('FSA') Package
Managing and Visualizing Brain Surface Data
Forward Stepwise Deep Autoencoder-Based Monotone NLDR
Robust Data Analysis Through Monitoring and Dynamic
Visualization
'Rcpp' Implementation of 'FSelector' Entropy-Based Feature
Selection Algorithms with a Sparse Matrix Support
Estimation, Variable Selection and Prediction for Functional
Semiparametric Models
Import and Analysis of OMR Data from FormScanner
An Interface Between the 'FSKX' Standard and 'R'
Wrapper Functions for 'FSL' ('FMRIB' Software Library) from
Functional MRI of the Brain ('FMRIB')
Rosenthal's Fail Safe Number and Related Functions
Estimating the Number of Factors in EFA with Out-of-Sample
Prediction Errors
Social Relations Analyses with Roles ("Family SRM")
Generate Fully-Sequential Space-Filling Designs Inside a Unit
Hypercube
Lightning Fast Serialization of Data Frames
Genetic Distance Segmentation for Population Genetics
Unified Sequence-Based Association Tests Allowing for Multiple
Functional Annotation Scores
Fault Tree Analysis Based on Proxel Simulation
A Wrapper for the API of the Danish Parliament
Rmetrics - Trading and Rebalancing Financial Instruments
Feature Extraction from Biological Sequences
White Noise and Goodness-of-Fit Tests for Functional Time Series
Framework for Unified Estimation in Lognormal Models
3D Fuel Segmentation Using Terrestrial Laser Scanning and Deep
Learning
Sensitivity Analysis Optimized for Matched Sets of Varied Sizes
Plot Full ROC Curves using Eyewitness Lineup Data
Simultaneous Prediction and Confidence Bands for Time Series
Data
Clean and Visualize Over Expression Results from
'ConsensusPathDB'
Convenience Functions by Michael Chirico
Model-Free Functional Chi-Squared and Exact Tests
Functional Analysis (with Interactions) for Dense SNP Data
Aggregated Functional Data Calibration using Splines and
Wavelets
Functional Programming with Parallelism and Progress Tracking
Easy Computation of Functional Diversity Indices
Clustering in the Discriminative Functional Subspace
Psychometric Functions from the Waller Lab
Gaussian Process Models for Scalar and Functional Inputs
Univariate and Multivariate Model-Based Clustering in
Group-Specific Functional Subspaces
Rmetrics - Modelling Trends and Unit Roots
Functional Data Analysis for Multiplexed Cell Images
Generating Funky Heatmaps for Data Frames
Functional Mediation for a Distal Outcome
Exploratory Data Analysis and Data Preparation Tool-Box
Time-Based Joins to Analyze Sequences of Events
Funnel Plots for Comparing Institutional Performance
Simple Utility Providing Terminal Access to all R Functions
Functional Regression for Irregularly Timed Data
Creating and Representing Functional Trait Spaces
Modeling Time-to-Event Data with Functional Predictors
Visualize Function Call Dependencies in R Source Code
Apply Mapping Functions in Parallel using Futures
Implementation of Fused MGM to Infer 2-Class Networks
Fused Partitioned Regression for Clinical and Omics Data
Fused Lasso for High-Dimensional Regression over Groups
Clustering and Feature Screening using L1 Fusion Penalty
Interim Analysis of Operational Futility in Randomized Trials
with Time-to-Event Endpoints and Fixed Follow-Up
Unified Parallel and Distributed Processing in R for Everyone
Apply Function to Elements in Parallel using Futures
A Future API for Parallel and Distributed Processing using
'batchtools'
A Future API for Parallel Processing using 'callr'
A 'Future' API for Parallel Processing using 'mirai'
Parallelize Common Functions via One Magic Function
Imputation Procedures and Quality Tests for Fuzzy Data
Join Tables Together on Inexact Matching
Probabilistic Record Linkage Using Pretrained Text Embeddings
Apply Two Fuzzy Numbers on a Monotone Function
Fuzzy Quantification of Common and Rare Species
Fuzzy Rank Tests and Confidence Intervals
Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers
Fuzzy Similarity in Species Distributions
Simulation and Resampling Methods for Epistemic Fuzzy Data
Fuzzy Spectral Clustering with Variable-Weighted Adjacency
Matrices
Statistical Methods for Trapezoidal Fuzzy Numbers
Selecting Variables in Regression Models
Scatter Plot After Residualizing Using 'fixest' Package
Fresh Weight Determination from Visual Image of the Plant
Extract Species Ecological Parameters from
Www.freshwaterecology.info
'fxl' Single Case Design Charting Package
Generalized Ridge Regression for Linear Models
Grain-Size Statistics and Description of Sediment
Graph Visualisation Engine Widget for R and 'shiny' Apps
Facilitation of Data Preparation and Plotting Procedures for RDA
and PCA Analyses
Generalized Adaptive Capped Estimator for Time Series
Forecasting
Genetic Similarity in User-Based Collaborative Filtering
Analysis of Variance from General Principles
A Genetic Algorithm for Learning Directed Acyclic Graphs
Globally-Applicable Area Disaggregated General Ecosystem Toolbox
V3
Graph Adjustment Identification Distances for Causal Graphs
Global Adaptive Generative Adjustment Algorithm for Generalized
Linear Models
Genetic Algorithm Assisted Genomic Best Liner Unbiased
Prediction
Calculate Gauge Repeatability and Reproducibility
Graphical Extension with Accuracy in Parameter Estimation
(GAIPE)
Biodiversity Data from the GBIF Node Network
Geometry-Adaptive Lyapunov-Assured Hybrid Optimizer with
Softplus Reparameterization and Trust-Region Control
Generalized Additive Latent and Mixed Models
Describe, Package, and Share Biodiversity Data
Collection of Packages for Internet Marketing
Configuration of Jupiter's Four Largest Satellites
Generate Test Matrices for Numerical Experiments
Genomic Annotation in Livestock for Positional Candidate LOci
Genetic Algorithms and C-Steps Based LTS (Least Trimmed Squares)
Estimation
Hierarchical Partitioning of Adjusted R2 and Explained Deviance
for Generalized Additive Models
Fit the Gambin Model to Species Abundance Distributions
Functions and Data for a Course on Modern Regression and
Classification
Generalized Additive Models for Bivariate Conditional Dependence
Structures and Vine Copulas
Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for
Binary Classification
Genetic Algorithm for Sequential Symmetric Games
Generalized Additive Models for Location Scale and Shape
Extra Additive Terms for Generalized Additive Models for
Location Scale and Shape
Fitting an Interval Response Variable Using `gamlss.family'
Distributions
Data for Generalized Additive Models for Location Scale and
Shape
Distributions for Generalized Additive Models for Location Scale
and Shape
Fitting Mixed (Inflated and Adjusted) Distributions
Extra Lasso-Type Additive Terms for GAMLSS
Fitting Mixture Distributions with GAMLSS
Generating and Fitting Truncated `gamlss.family' Distributions
Bimodal Skew Symmetric Normal Distribution
Generalized Additive Extreme Value Models for Location, Scale
and Shape
Generalized Additive Mixed Models using 'mgcv' and 'lme4'
Dose Rate Estimation from in-Situ Gamma-Ray Spectrometry
Measurements
Non-Linear Mixed Effects Model Based on the Gamma Function Form
Classic Gamma Regression: Joint Modeling of Mean and Shape
Parameters
Generalized Additive Mixed Model Interface
Generalized Additive Mixed Model Analysis via Slice Sampling
Fit Regularization Path for Generalized Additive Models
Bayesian Generalized Additive Model Selection
Utilities to Facilitate Modeling Routines with Generalized
Additive Models
Build a Metric Subspaces Data Model for a Data Source
High Performance, Low Friction Large Language Model Chat
Generate Generative Data for a Data Source
Gene Association Network-Based Pathway Analysis (GANPA)
Create Interactive Gantt Charts with Work Breakdown Structure
Conservation Indicators Using Spatial Information
Searching Parsimony Models with Genetic Algorithms
Drawing Gapped Cluster Heatmaps with 'ggplot2'
Estimation and Exogenous Covariate Selection for ARCH-m(X),
Additive ARCH-m(x), and GARCH-X Models
Estimating a GARCHSK Model and GJRSK Model
Gene and Region Counting of Mutations ("GARCOM")
Fitting and Forecasting Gegenbauer ARMA Time Series Models
Generalized Array Arithmetic for Ragged Arrays with Named
Margins
Import, Recompute and Analyze Data from Portable Gas Analyzers
Genetic Algorithm (GA) for Variable Selection from
High-Dimensional Data
Greenhouse Gas Flux Calculation from Chamber Measurements
Train and Apply a Gaussian Stochastic Process Model
Analyzing Gastric Emptying from MRI or Scintigraphy
Genetic Data Handling (QC, GRM, LD, PCA) & Linear Mixed Models
Easily Gate or Select Points on a Scatter Plot
Flow/Mass Cytometry Gating via Spatial Kernel Density Estimation
Geographic and Taxonomic Occurrence R-Based Scrubbing
Lotka-Volterra Models for Gause's 'Struggle for Existence'
The Gaussian Covariate Method for Variable Selection
Difference Measures for Multivariate Gaussian Probability
Density Functions
The Greatest Mathematician Since Antiquity
Inference, Goodness-of-Fit and Forecast for Univariate Gaussian
Hidden Markov Models
Collection of Functions for Gaussian Quadrature
Tabular Data Suppression using Gaussian Elimination
Multi-Trait Dissimilarity with more Uniform Contributions
Generalized Beta Distribution of the Second Kind: Properties,
Likelihood, Estimation
Estimation of the Generalised Beta Distribution of the Second
Kind from Grouped Data
Gradient Boosting Algorithm for Predicting Methylation States
Generalized Bayesian Adaptive Smoothing Splines
Generalized Beta and Beta Prime Distributions
Generalized Berk-Jones Test for Set-Based Inference in Genetic
Association Studies
Automated Boosted Regression Tree Modelling and Mapping Suite
Generalized Bayesian Optimal Phase II Design (G-BOP2)
Utilities for Processing Rd Objects and Files
Hyperparameter Search for Gradient Boosted Trees
Utilities for Simulation, Plots, Quantile Functions and
Programming
Simple Peak Alignment for Gas-Chromatography Data
Graph-Based Two-Sample Tests for Categorical Data
'GPU'/CPU Benchmarking in Debian-Based Systems
GCC Estimation of the Multilevel Factor Model
The (Adaptive) LASSO and Elastic Net Penalized Least Squares,
Logistic Regression, Hybrid Huberized Support Vector Machines,
Squared Hinge Loss Support Vector Machines and Expectile
Regression using a Fast Generalized Coordinate Descent
Algorithm
Regression Coefficients Estimation Using the Generalized Cross
Entropy
Analysis of Geostatistical Count Data using Gaussian Copulas
Gene-Cluster Discovery, Annotation and Visualization
Generalized Correlation and Related Measures
Bayesian Meta-Analysis of Pleiotropic Effects Using Group
Structure
Generalized Contrastive Principal Component Analysis
Implements Generic Composite Similarity Measure
Gaussian and Student-t Copula Models for Count Time Series
Estimation of Forest Volume, Biomass, and Carbon
Geographical Detectors for Assessing Spatial Factors
Datasets for the Book Graphical Data Analysis with R
Earth Observation Data Cubes from Satellite Image Collections
Wrappers for 'GDAL' Utilities Executables
Various R Programming Tools for Data Manipulation
Volumetric Analysis using Graphic Double Integration
Spatial Modeling of Infectious Diseases with Co-Variate Error
Spatial Modeling of Infectious Disease with Reinfection
Inference for Infectious Disease Transmission in SIR Framework
Estimate Graph Dimension using Cross-Validated Eigenvalues
Distances and Routes on Geographical Grids
Gauss - Dantzig Selector: Aggregation over Random Models
Font Metrics and Font Management Utilities for R Graphics
Analysis of Spatial Stratified Heterogeneity
IO for GAMS GDX Files using 'data.table'
Evaluate the Geboes Score for Histology in Ulcerative Colitis
Geographical Ecology and Conservation Knowledge Online
Adaptive Association Tests for Multiple Phenotypes using
Generalized Estimating Equations (GEE)
Solve Generalized Estimating Equations for Clustered Data
Bias-Corrected GEE for Cluster Randomized Trials
Marginal Proportional Hazards Mixture Cure Models with
Generalized Estimating Equations
Building and Managing Local Databases from 'Google Earth Engine'
Mediation Analysis for Generalized Linear Models Using the
Difference Method
Modified Variance Estimators for Generalized Estimating
Equations
Modified Generalized Estimating Equations for Small-Sample Data
Modified Generalized Estimating Equations for Binary Outcome
A Comprehensive Analysis of High Dimensional Longitudinal Data
Calculate Generalized Eigenvalues, the Generalized Schur
Decomposition and the Generalized Singular Value Decomposition
of a Matrix Pair with Lapack
Gene-Environment Interaction Analysis Incorporating Prior
Information
Misspecified Models for Gene-Environment Interaction
Best Linear Unbiased Prediction of Genotype-by-Environment
Metrics
Network Meta-Analysis Using Bayesian Methods
Generalized Two-Stage Designs for Phase II Single-Arm Studies
General Engine for Eco-Evolutionary Simulations
Genetic Algorithm and Particle Swarm Optimization
Classes and Methods to Use Genetic Algorithms for Feature
Selection
Analysis and Visualization Tools for Genetic Barcode Data
Clopper-Pearson Confidence Interval and Generalized Binomial
Distribution
Comprehensive Analysis of 'GENCODE' Annotations and Splice Site
Motifs
Interacting with Roberts and Utych's (2019) Gendered Language
Dictionary
Predict Gender from Names Using Historical Data
Predict Gender from Brazilian First Names
This is a Collection of Functions to Analyse Gender Differences
Quantitative Analysis Tools for Gender Studies
Segmentation and Classification of Accelerometer Data
Identification of Periodically Expressed Genes
Easily Downloads a Gene Expression Dataset from a GEO Code and
Retrieves the Gene Symbols of Its Probesets
A Pipeline to Define Gene Families in Legumes and Beyond
Non-Negative Matrix Factorization for Single-Cell Omics
Automated Gene Identification for Post-GWAS and QTL Analysis
Genetic Epidemiology Design and Inference
Population Genetic Data Analysis Using Genepop
Population Genetics Statistics for Selective Sweep
Generalized Correlations, Causal Paths and Portfolio Selection
Goodness of Fit Tests for Logistic Regression Models
Credible Visualization for Two-Dimensional Projections of Data
Fully Parameterized Generalized Wendland Covariance Function
Blinder-Oaxaca Decomposition for Generalized Linear Model
Statistical Tools for Balanced and Unbalanced Ranked Set
Sampling
Generate Data Containing Fake Personally Identifiable
Information
Common S3 Generics not Provided by Base R Methods Related to
Model Fitting
Simulation of Single Cell RNA-Seq Data with Complex Structure
Get Gene Sets for Gene Enrichment Analysis
Statistical Tools for the Analysis of Multi Environment
Agronomic Trials
Identify Favorable Subsets of Germplasm Collections
Spatial Graph-Theoretic Genetic Gravity Modelling
Generating Triangular and Trapezoidal Fuzzy Random Numbers via
Uniform Distribution
Goodness-of-Fit for Zero-Inflated Univariate Hidden Markov
Models
Fast, Robust, and Outlier Resistant Hierarchical Clustering
Project GENIE BioPharma Collaborative Data Processing Pipeline
Genie: Fast and Robust Hierarchical Clustering
Path Algorithm for Generalized Lasso Problems
Generalized Convergence Diagnostics for Difficult MCMC
Algorithms
Implements Generalized Meta-Analysis Using Iterated Reweighted
Least Squares Algorithm
Finding the DNA and Protein Sequences of Any Genomic or
Proteomic Loci
Models Dealing with Spatial Dependency in Genomic Data
Circular Genomic Permutation using Genome Wide Association
p-Values
Plot Publication-Grade Gene and Genome Maps
Genotype Imputation and Population Genomics Efficiently from
Variant Call Formatted (VCF) Files
Simulation of Discrete Random Variables with Given Correlation
Matrix and Marginal Distributions via a Gaussian or Student's t
Copula
Genotyping Triploids (or Diploids) from Luminescence Data
Sequential Change-Point Tests for Generalized Ornstein-Uhlenbeck
Processes
Pathmox Approach Segmentation Tree Analysis
Robust, Logged and Reproducible Iteration at Organizational
Scale
Generalized Ridge Trace Plots for Ridge Regression
R Functions for Generalized Simulated Annealing
Predict Epidemic Curves with Generalized SEIR Modeling
Resampling Based Yield Stability Analyses
A Generalized Multiclass Support Vector Machine
Estimation and Other Tools for Generalized Transmuted Models
R Shiny App for Creating Simplified Trial Summary (TS) Domain
Generalized Two Arms Clinical Trial Sample Size Calculation
Spline Based Window Boundaries for Genomic Analyses
Accounting for Random Displacements of True GPS Coordinates of
Data
Extension Types for Spatial Data for Use with 'Arrow'
Attach '(Geo)Arrow' and/or '(Geo)Parquet' Data to a Widget
Analysis of Geostatistical Data using Bayes and Empirical Bayes
Methods
Download Official Spatial Data Sets of Brazil
Causal Inference with Spatio-Temporal Data
Implementing Methods for Spatial Fuzzy Unsupervised
Classification
Geolocalização De Endereços Brasileiros (Geocoding Brazilian
Addresses)
Mitigating Spatial Bias Through Geographical Complexity
Quantifying Variable Change Induced by Administrative Boundary
Transformations
Stratified Heterogeneity Measure, Dominant Driving Force
Detection, Interaction Relationship Investigation
Fast, Dependency-Free Geodesic Distance Calculations
Methods for Calculating Gradient Surface Metrics
3D-Visualization of Geoelectric Resistivity Measurement Profiles
'ggplot2' Faceting Utilities for Geographical Data
Spatial Data Processing for Decision Making
Orchestrate Geospatial (Meta)Data Management Workflows and
Manage FAIR Services
Select Sparse Geoadditive Models for Spatial Prediction
Generator from American Community Survey Geodatabases
Turn Geospatial Polygons into Regular or Hexagonal Grids
Geographical Risk Analysis Based on Habitat Connectivity
Convert Data from and to 'GeoJSON' or 'TopoJSON'
Geographic Tools for Studying Gerrymandering
Data for Topographic and Geologic Mapping
Finds the Geometrical Archetypal Analysis of a Data Frame
Easily Visualize Geographic Data of Morocco
Tools for Reading and Writing ISO/OGC Geographic Metadata
Heterogeneous Methods for Shape and Other Multidimensional Data
Convert Between R Objects and Geometric Structures
Mesh Generation and Surface Tessellation
A Computer Program for Geotechnical Investigations
Procedures for Gaussian and Non Gaussian Geostatistical (Large)
Data Analysis
Geometric Morphometric Analyses of 2D and 3D Landmark Data
Multidimensional Queries Enriched with Geographic Data
Interface to the "Geonames" Spatial Query Web Service
Identification and Visualisation of European NUTS Regions from
Geolocations
Perpendicular Line Transects for Geosciences
Methods of Applied Psychology and Psychometrics in Geographical
Analysis
Calculating Geographic Range from Occurrence Data
Robust Geostatistical Analysis of Spatial Data
Open Source Geometry Engine ('GEOS') R API
Comprehensive Geospatiotemporal Analysis and Multimodal
Integration Toolkit
Geostatistical Analysis and Design of Optimal Spatial Sampling
Networks
Spatio-Temporal Radial Basis Functions with Distance-Based
Methods (Optimization, Prediction and Cross Validation)
An Introduction to Statistics for Geoscientists
Geostatistical Modelling with Likelihood and Bayes
'targets' Extensions for Geographic Spatial Formats
Efficient Spatial Thinning of Species Occurrences
Tools to Improve the Use of Geostatistic
An R Plug-in for the Distributed Hydrological Model GEOtop
Methods for Handling and Analyzing Time Series of Satellite
Images
User-Friendly Interface for Geographically-Weighted Models
Google Encoded Polyline Algorithm Format
Generalised Exponential Poisson and Poisson Exponential
Distributions
Generalized Efficient Regression-Based Imputation with Latent
Processes
Preparer of Main Scientific References for Automatic Insertion
in Academic Papers
Indices and Graphics for Assess Seed Germination Process
Seed Germination Indices and Curve Fitting
Simulation, Visualization and Comparison of Tumor Evolution Data
Generalized Structured Component Analysis Structural Equation
Modeling
Reproducible Data Retrieval from the GESIS Data Archive
Tools for Making and Combining Functions
Generalised Survival Trial Assessment Tool Environment
Fetching Tabular Data "Onload" in Compiled R Markdown HTML
Documents
Imports Datasets from BCB (Central Bank of Brazil) using Its
Official API
Generalized Extended Triangular Designs ('GETdesigns')
Reading Annual and Quarterly Financial Reports from B3
Translating Coding Statements using get() and eval() for
Improved Run-Time Coding Efficiency
Reading FRE Corporate Data of Public Traded Companies from B3
Import and Process Data from the 'Lattes' Curriculum Platform
Reading Bibliometric Data from Lattes Platform
Quantifying Systematic Heterogeneity in Meta-Analysis
Fast and Cached Import of Data from 'Quandl' Using the 'json
API'
Download Radar Data for Biological Research
General-to-Specific (GETS) Modelling and Indicator Saturation
Methods
General-to-Specific Modelling of Panel Data
SPRE Statistics for Exploring Heterogeneity in Meta-Analysis
Get Data for Brazilian Bonds (Tesouro Direto)
Joint Test of Gene and GxE Interactions via Varying Coefficients
GEV Conditional Density Estimation Network
General Hypothesis Testing Problems for Multivariate
Coefficients of Variation
Multiple RMST-Based Tests in General Factorial Designs
Multiple RMTL-Based Tests for Competing Risks Data in General
Factorial Designs
Tests for Survival Data in General Factorial Designs
Gross Flows Estimation under Complex Surveys
Strand-Wise Gene and Protein Extraction from GFF3 Files
Generalized Fisher's Combination Tests Under Dependence
Generalized Fiducial Inference for Ultrahigh-Dimensional
Regression
Offline 'Google' Fonts for 'Markdown' and 'Shiny'
Parametric Iterative Conditional Expectation G-Formula
G-Formula for Causal Inference via Multiple Imputation
Exploratory Data Analysis using Tiled One-Dimensional Graphics
A 'ggplot2' Extension for Composable Visualization
Visualizing Sequence Alignment by Generating Publication-Ready
Plots
Flexible Segment Geoms with Arrows for 'ggplot2'
Automatically Create and Style 'ggplot2' Charts
Create Maps from a Column of Place Names
Categorical Scatter (Violin Point) Plots
A Grammar of Graphics Implementation of Biplots
Blending and Compositing Algebra for 'ggplot2'
Create Images of Volumetric Brain Data in NIfTI Format Using
'ggplot2' Syntax
Waffle Style Chart with a Brick Layout in 'ggplot2'
Mini Bubble Plots for Comparison of Discrete Data with 'ggplot2'
Combines Changepoint Analysis with 'ggplot2'
Shorten the Distance from Data Visualization Idea to Actual Plot
Multi-Sequence 'BLAST' Alignment Chord Diagram Visualization
Tool
Gabriel Graph Based Large-Margin Classifiers
Implementation of Plots from Cleveland's Visualizing Data Book
Make Flexible 'ggplot2' Correlation Heatmaps
Visualization of a Correlation Matrix using 'ggplot2'
Analyze and Create Elegant Directed Acyclic Graphs
Add Day/Night Patterns to 'ggplot2' Plots
'ggplot2' Extension for Seasonal and Trading Day Adjustment with
'RJDemetra'
Create Dendrograms and Tree Diagrams Using 'ggplot2'
Interpretable Bivariate Density Visualization with 'ggplot2'
Object-Oriented Diagram Plots with 'ggplot2'
Visualizations of Distributions and Uncertainty
Likelihood Computation for 'ggdmc' Package
Prior Probability Functions of the Standard and Truncated
Distribution
'ggplot2'-Based Tools for Visualising DNA Sequences and
Modifications
Modern Graphs for Design of Experiments with 'ggplot2'
Turnkey Visualisations for Exploratory Data Analysis
Create Tidy Data Frames of Marginal Effects for 'ggplot' from
Model Outputs
Visualization Tools for Genealogical Data
Audit 'ggplot2' Visualizations for Accessibility and Best
Practices
Visualisation of High-Throughput Behavioural (i.e. Ethomics)
Data
Visualization of 'exametrika' Output Using 'ggplot2'
Add Marginal Histograms to 'ggplot2', and More 'ggplot2'
Enhancements
Manage & Modify 'ggplot' Figures using 'ggfigdone'
Visualise and Calculate Life History Parameters for Fisheries
Science using 'ggplot2'
Dedicated 'ggplot2' Methods for 'fixest' Objects
Scales that Focus Specific Levels in your ggplot()
Plotting Football Matches Expected Goals (xG) Stats with
'Understat' Data
Publication-Ready Forest Plots with 'ggplot2'
Formula Interface to the Grammar of Graphics
Data Visualization Tools for Statistical Analysis Results
Streamlined Creation of Segments on the Y-Axis of 'ggplot2'
Plots
A 'ggplot2' Extension for Geometric Data Analysis
A Grammar of Graphics for Comparative Genomics
Capture the Spirit of Your 'ggplot2' Calls
Simplified Legend and Guide Alignment for 'ggplot2'
Create a Half Normal Plot Using 'ggplot2'
HDX Theme, Scales, and Other Conveniences for 'ggplot2'
Make Hexagonal Heatmaps with Varying Hexagon Sizes
Graphics Layers for Plotting Image Data with 'ggplot2'
Extend 'ggplot2' with Layers and Scales for Spatial Uncertainty
Visualization
Visualise the Results of Inferential Statistics using 'ggplot2'
Explore the Innards of 'ggplot2' Objects
Visualizing Interval-Valued Data Using 'ggplot2'
Data Visualization for IP Addresses and Networks
Make Interactive 'ggplot2'. Extension to 'ggplot2' and 'ggiraph'
Wearable Accelerometer Data File Readers
'ggplot2' Friendly Isotonic or Monotonic Regression Curves
Group Lasso Penalized Learning Using a Unified BMD Algorithm
Grammar of Graphics for Linear Model Diagnostic Plots
Plotting Lorenz Curve with the Blessing of 'ggplot2'
Network-Style Visualization of Directed Pairwise Relationships
Graphical Markov Models with Mixed Graphs
Customizable China and Global Map Visualizations
Plot Columns of Two Matrices Against Each Other Using 'ggplot2'
Tools for Analyzing MCMC Simulations from Bayesian Inference
Visualizations for 'mice' with 'ggplot2'
Variable Selection in Linear Mixed Models for SNP Data
'GGML' Tensor Operations for Machine Learning
Gaussian Graphical Models with Nonconvex Regularization
Gaussian Graphical Models Using Ridge Penalty Followed by
Thresholding and Reestimation
Visualizing Multi-Species Relative Synonymous Codon Usage and
Extensible Data Exploration
Visualization of Multiple Genome-Wide Association Study Summary
Statistics
Create Muller Plots of Evolutionary Dynamics
Geometries to Plot Networks with 'ggplot2'
Multiple Fill and Colour Scales in 'ggplot2'
A 'ggplot2' Extension to Make Normal Violin Plots
Plot Data on Oceanographic Maps using 'ggplot2'
'Okabe-Ito' Scales for 'ggplot2' and 'ggraph'
Make 'ggplot2' Versions of Vegan's Ordiplots
Identify Individuals with Unusual Geo-Genetic Patterns
Package Plot Layers for Easier Portability and Modularization
'ggplot' Visualizations for the 'partykit' Package
Robust Image Rendering Support for 'ggplot2'
Publication-Ready PCA, t-SNE, and UMAP Plots
Parallel Coordinate Plots in the 'ggplot2' Framework
Visualizing Pedigrees with 'ggplot2' and 'plotly'
Easy Plotting of Periodic Data with 'ggplot2'
Make 'PICRUSt2' Output Analysis and Visualization Easier
Create Layout Plots of Biological Culture Plates and Microplates
Multiple Summary Statistics for Binned Stats/Geometries
Create Elegant Data Visualisations Using the Grammar of Graphics
'RStudio' Addin for Teaching and Learning 'ggplot2'
Create Ggplots via a Graphical User Interface
Convert Plot to 'grob' or 'ggplot' Object
'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME
Models
A Cross Between a 2D Density Plot and a Scatter Plot
Extra Geometries and Stats for 'ggplot2'
Dots and Their Connections in Polar Coordinate System
Polygons with Holes for the Grammar of Graphics
Icon-Based Population Charts and Plots for 'ggplot2'
A 'ggplot2' Extension Inspired by 'GraphPad Prism'
Annotate Statistical Tests for 'ggplot2'
Compare Big Datasets to the Uniform Distribution
Quickly Explore Your Data Using 'ggplot2' and 'table1' Summary
Tables
An Implementation of Grammar of Graphics for Graphs and Networks
Allows Interactive Visualization of Data Through a Web Browser
GUI
Draw Histograms and Restricted Cubic Splines (RCS)
Scales, Geometries, and Extensions of 'ggplot2' for Election
Mapping
Automatically Position Non-Overlapping Text Labels with
'ggplot2'
Add Some Van Gogh Colors and Overlay Colors on Your 'ggplot()'
Create Sankey and Alluvial Diagrams Using 'ggplot2'
Scatter Plot Combined with Ridgelines in 'ggplot2'
Utilities and Helpers for Single Case Experimental Design (SCED)
using 'ggplot2'
Scientific Journal and Sci-Fi Themed Color Palettes for
'ggplot2'
Plotting Decision Curve Analysis with Coloured Bars
Brain Atlas Data Structures for the 'ggseg' Ecosystem
Additional Brain Surface Meshes for the 'ggsegverse' Ecosystem
Interactive 3D Brain Atlas Visualization
Create a Segmented Total Bar Plot with Custom Annotations and
Labels
Interactive Structural Equation Modeling (SEM) and Multi-Group
Path Diagrams
A 'ggplot2' Extension for Drawing Publication-Ready Sequence
Logos
Galactic and Equatorial Coordinate Implementation for 'ggplot2'
Visualising Output from Sequential Monte Carlo and
Ensemble-Based Methods
A 'ggplot2'-Plot of Composition of Solvency II SCR: SF and IM
New Data Visualisations for SOMs Networks
'ggplot2' Functions to Create Tufte Style Sparklines
Extensions to 'ggplot2' for Radiation Spectra
Multiple Geometric Shape Point Layer for 'ggplot2'
Extension to 'ggplot2' for Plotting Stats
'ggplot2' Based Plots with Statistical Details
Continuous Confidence Interval Plots using t-Distribution
Tools for Outbreak Investigation/Infectious Disease Surveillance
Offers Various Swiss Maps as Data Frames and 'ggplot2' Objects
An Extension to 'ggplot2', for the Creation of Ternary Diagrams
Improved Text Rendering Support for 'ggplot2'
Extra Themes, Scales and Geoms for 'ggplot2'
A 'ggplot' Theme for University of Ljubljana
Create Tibbles and Lists of 'ggplot' Figures for Reporting
Post-Process 'ggplot2' Plots with 'TikZ' Code Using Plot
Coordinates
Grammar of Graphics and Plot Helpers for Time Series
Visualization
Trace and Highlight Groups of Data Points
A 'ggplot2' Extension for Translating Plot Text
Add Trendline and Confidence Interval to 'ggplot'
Create Sector and Other Charts Easily Using Grammar of Graphics
Combination Matrix Axis for 'ggplot2' to Create 'UpSet' Plots
Tidy, 'ggplot2'-Native Visualization for Genomic Variants
Conjuntos de Datos para 'Graficas Versatiles con ggplot2'
Vector Field Visualizations with 'ggplot2'
Create Volcano Plots for Differential Gene Expression Data
Browser-Native 'WebGL' Rendering for R Graphics
A Natural Language Interface to 'ggplot2'
Quantifying Evolution and Selection on Complex Traits
Functional Conditional Independence Testing with the GHCM
Download Weather Station Data from GHCNd
Missing Data Segments Imputation in Multivariate Streams
Exploratory Analysis of Temporal and Spatio-Temporal Health Data
Bayesian Hierarchical Modelling of Spatio-Temporal Health Data
Generalized Hyperbolic Distribution and Its Special Cases
Fit and Simulate Generalised Hypergeometric Ensembles of Graphs
Gene Set Uncertainty in Enrichment Analysis
An Alternative 'Rcpp' Wrapper of 'MeCab'
A General Iterative Clustering Algorithm
Penalised Likelihood Estimation of a Covariance Matrix
API Wrapper for the Natural Gas Transparency Platforms of Gas
Infrastructure Europe
Multivariate Analysis with Optimal Scaling
Access to the Global Inventory of Floras and Traits (GIFT)
Reads in 'Neuroimaging' 'GIFTI' Files with Geometry Information
Group Inverse-Gamma Gamma Shrinkage for Sparse Regression with
Grouping Structure
Random Variate Generator for the GIG Distribution
Gillespie's Stochastic Simulation Algorithm (SSA)
Gillespie's Stochastic Simulation Algorithm for Impatient People
The Interpretation of Adjusted Cp Statistic
Calculate Genetic Interactions for Paired CRISPR Targets
Group Iterative Multiple Model Estimation
Group Iterative Multiple Model Estimation with 'graphicalVAR'
Graphical Utilities for Visualizing and Exploring Data
Performs Genome-Wide Iterative Fine-Mapping for Non-Gaussian
Data using GINA-X
A New Gini Correlation Between Quantitative and Qualitative
Variables
Gini Indices, Variances and Confidence Intervals for Finite and
Infinite Populations
Generalized Inverse Normal Distribution Density and Generation
Generalized Iterative Proportional Fitting for Relational Models
Gaussian Model Invariant by Permutation Symmetry
Download Map Data from GISCO API - Eurostat
Network Analysis on the Norwegian Road Network
Further Capabilities in Geographic Information Science
Store and Retrieve Data.frames in a Git Repository
Extracts Knowledge from 'Git' Repositories
Turn Your Git Commit Messages into a HTML Book
Create Useful .gitignore Files for your Project
Data Version Control for the Targets Package
A Generalized Joint Location and Scale Framework for Association
Testing
Data Sets for Copula Additive Distributional Regression Using R
g-and-k and g-and-h Distribution Functions
Gaines and Kuklinski (2011) Estimators for Hybrid Experiments
Accessing the Official 'Google Knowledge Graph' API
Generalized Kernel Regularized Least Squares
Generalized Kumaraswamy Regression Models for Bounded Data
Generalized Additive and Linear Models (GLAM)
Generalized Linear Autoregressive Moving Average Models
Solve the Graphical Lasso Problem with 'Armadillo'
Variable Selection in Sparse GLARMA Models
Graphical Lasso: Estimation of Gaussian Graphical Models
Animated Glass-Style Tabs and Multi-Select Filter for 'Shiny'
General Linear Ballistic Accumulator Models
An R Package for Multiple-Group Latent Class Analysis
Calculate Textures from Grey-Level Co-Occurrence Matrices
(GLCMs)
Estimation and Use of the Generalised (Tukey) Lambda
Distribution
Fitting Single and Mixture of Generalised Lambda Distributions
Fit GLD Regression/Quantile/AFT Model to Data
Global Livestock Environmental Assessment Model (GLEAM-X)
Learning Interactions via Hierarchical Group-Lasso
Regularization
Phylogenetic Comparative Methods with Uncertainty Estimates
Descriptive Analysis on Three Glioblastoma EHRs Datasets
Generalized Linear Latent Variable Models
'C' and 'Java' Source Code Generator for Fitted Glm Objects
Predicted Values and Discrete Changes for Regression Models
Fitting Generalized Linear Models Using Sparse Matrices
GLM-Based Estimation for Rasch Model Parameters
Bayesian Generalized Linear Models (IID Samples)
All Hierarchical or Graphical Models for Generalized Linear
Model
Fitting Generalized Linear Models Subject to Constraints
Generalized Linear Models for Categorical Responses
Fitting GLMs with Missing Data in Both Responses and Covariates
Fit GLM with LEP-Based Penalized Maximum Likelihood
Generalized Linear Mixed Models via Monte Carlo Likelihood
Approximation
Hierarchical Partitioning of Marginal R2 for Generalized
Mixed-Effect Models
Generalized Linear Mixed Models using Adaptive Gaussian
Quadrature
Fit a Cosinor Model Using a Generalized Mixed Modeling Framework
Generalized Linear Mixed Model Analysis via Expectation
Propagation
Generalized Linear Mixed Models via Fully Exponential Laplace in
EM
Generalized Linear Mixed Models with Robust Random Fields for
Spatiotemporal Modeling
Generalized Linear Models Adjusting for Misrepresentation
Variable Selection for Generalized Linear Mixed Models by
L1-Penalized Estimation
Generalized Linear Models with Clustering
High Dimensional Penalized Generalized Linear Mixed Models
(pGLMM)
Generalized Linear Mixed Model (GLMM) for Binary Randomized
Response Data
Generalised Linear Mixed Model Selection
Bayesian Model Selection for Generalized Linear Mixed Models
General Linear Mixed Models for Gene-Level Differential
Expression
Generalized Linear Mixed Models using Template Model Builder
Lasso and Elastic-Net Regularized Generalized Linear Models
Fit a Penalized Constrained Continuation Ratio Model for
Predicting an Ordinal Response
Nested Cross Validation for the Relaxed Lasso and Other Machine
Learning Models
Add Nonparametric Bootstrap SE to 'glmnet' for Selected
Coefficients (No Shrinkage)
Generalized L-Moments Estimation for Extreme Value Distributions
Data and Code to Accompany Generalized Linear Models, 2nd
Edition
L1 Regularization Path for Generalized Linear Models and Cox
Proportional Hazards Model
Fit a Penalized Continuation Ratio Model for Predicting an
Ordinal Response
Dimension Reduction of Non-Normally Distributed Data
Permutation-Based Inference for Generalized Linear Models
Creates Ideal Data for Generalized Linear Models
(Double) Generalized Linear Models for Spatio-Temporal Data
Generalized Linear Models with Truncated Lasso Penalty
Set of Tools to Data Analysis using Generalized Linear Models
Transfer Learning under Regularized Generalized Linear Models
Model Selection and Multimodel Inference Made Easy
Variable Selection Deviation Measures and Instability Tests for
High-Dimensional Generalized Linear Models
A Collection of Graphic Tools for GLM Diagnostics and some
Extensions
Inhomogeneous K- And Pair Correlation Functions Using Global
Estimators
Generate Functions to Get or Set Global Options
Objective functions for benchmarking the performance of global
optimization algorithms
Identify Global Objects in R Expressions
Download and Measure Global Trends Through Google Search Volumes
Plot 2D and 3D Views of the Earth, Including Major Coastline
Estimating Functions with Multivariate B-Splines
Fitting and Testing Generalized Logistic Distributions
Transformed and Relative Lorenz Curves for Survey Weighted Data
User-Friendly 'shiny' App for Bayesian Species Distribution
Models
Glossaries for Markdown and Quarto Documents
Genome-Wide Association and Linkage Analysis under Heterogeneity
Automated Calibration and Analysis of 'GLS' (Global Location
Sensor) Data
Saturated Model Log-Likelihood for Multinomial Outcomes
Generalized Least Squares with Measurement Error
Generalised Linear Step-Up Procedure for Multiple Hypothesis
Testing
Wrapper Functions for the 'glue' Library
Glucose Variability Measures from Continuous Glucose Monitoring
Data
Methods to Assess Generalized Latent Variable Model Fit
Parsing Glycan Structure Text Representations
Representation for Glycan Compositions and Structures
Genomic Mediation Analysis with Adaptive Confounding Adjustment
Distance and Travel Time Between Two Points from Google Maps
Generalized Measure of Correlation (GMC)
Fast Estimation of Gaussian Mixture Copula Models
Graph Based Multiple Comparison Procedures
Lightweight Graph Based Multiple Comparison Procedures
Accessing a Geometallurgical Database with R
Short Term Forecasting via GMDH-Type Neural Network Algorithms
Binary Classification via GMDH-Type Neural Network Algorithms
Geometric Median, k-Medians Clustering and Robust Median PCA
Generalized Multivariate Functional Additive Models
Inference and Clustering of Functional Data
Gaussian Mixture Graphical Model Learning and Inference
Descriptive Statistics, Transition Plots, and More
Generalized Method of Moments and Generalized Empirical
Likelihood
Generalized Linear Mixed Model Association Tests
Likelihood-Based Boosting for Generalized Mixed Models
Optimal Initial Value for Gaussian Mixture Model
Multinomial Logit Models with Random Parameters
Various R Programming Tools for Model Fitting
Tools for 2D and 3D Plots of Single and Multi-Objective
Linear/Integer Programming Models
Datasets for the Book 'Getting (more out of) Graphics'
Multivariate Polynomials with Rational Coefficients
Generalised Management Strategy Evaluation Simulator
Generalized Mass Spectrum Missing Peaks Abundance Imputation
Interface Between GMT Map-Making Software and R
General Multiple Tests for Univariate and Multivariate
Functional Data
Estimate Gaussian and Student's t Mixture Vector Autoregressive
Models
Joint Models of Survival and Multivariate Longitudinal Data
Estimate Functional and Stochastic Parameters of Linear Models
with Correlated Residuals
Estimate Functional and Stochastic Parameters of Linear Models
with Correlated Residuals and Missing Data
Extended Graphical Model Checks for the Rasch Family of Models
Methods for Fitting Network Time Series Models
Computation of Generalized Nash Equilibria
Goodness of Fit Test for Continuous Distribution Functions
Estimate Natural Mortality for Different Life Stages
Various Non-Additive Models for Genetic Associations
Access the 'Geographic Name Resolution Service'
Read Data from Files Readable by 'gnumeric'
Weighted and Lexicographic Goal Programming Interface
Gene Set Analysis Using the Gene Set Ordinal Association Test
Comprehensive GO Terms Comparison Between Species
Functions for Community Data and Ordinations
Goodness-of-Fit Measures for Categorical Response Models
Goodness-of-Fit Methods for Right-Censored Data
Goodness-of-Fit Testing for Model-Based Clustering
Goodness of Fit Tests Based on Empirical Distribution Functions
Goodness-of-Fit Tests for Functional Data
Goodness-of-Fit Tests for the Gamma Distribution
Goodness-of-Fit Tests for the Inverse Gaussian Distribution
Testing Goodness-of-Fit with the Kernel Density Estimator
Bootstrap-Based Goodness-of-Fit Tests for Parametric Regression
Interactive Document for Working with Goodness of Fit Analysis
Tests of Fit for some Probability Distributions
Classical Goodness-of-Fit Tests for Univariate Distributions
Generalized Orthogonal GARCH (GO-GARCH) Models
Statistical Network Models for Dynamic Network Data
Goldilocks Adaptive Trial Designs for Time-to-Event Endpoints
A Framework for Robust Shiny Applications
Automate the Mapping Between a List of Genes and Gene Ontology
Categories
Animate Text using the 'Animate.css' Library
The gamma-OMP Feature Selection Algorithm
Conducting Maximum Likelihood Estimation with Truncated
Mortality Data
Detection and Reconstruction of Muscle Fibers from diceCT Image
Data
Monte Carlo Goodness-of-Fit Tests for Stochastic Block Models
Association Analysis for Categorical Variables
Scrape and Analyze 'Goodreads' Book Data
Access to 'Google Ads' via the 'Windsor.ai' API
Access to the 'Google Cloud Vision' API for Image Recognition,
OCR and Labeling
Send Error Reports to the Google Error Reporting Service API
Retrieve Information from 'Google Knowledge Graph' API
Call Google's 'Natural Language', 'Cloud Translation', 'Cloud
Speech', and 'Cloud Text-to-Speech' APIs
An Interface to Google's Cloud Natural Language API
Encoding Coordinates into 'Google' Polylines
Working with Google's 'Public Data Explorer' DSPL Metadata Files
R Interface for Google 'Cloud Pub/Sub' REST API
Access Google Sheets using the Sheets API V4
Access the 'Google Tag Manager' API using R
Accesses Google Maps APIs to Retrieve Data and Plot Maps
Visualization of Functional Analysis Data
Algorithms for the Subject Graphs and Network Optimization
Fit Generalized Odds Rate Mixture Cure Model with Interval
Censored Data
Evaluation of Inequality Constrained Hypotheses Using GORICA
Tools for Data Analysis in Experimental Agriculture
Scroll Back to Top Icon in Shiny and R Markdown
Speed Limiter to Control Rate of Execution of Loops
functions to get public survey data in Japan
Bayesian Gower Agreement for Categorical Data
Self-Organizing Maps for Mixed-Attribute Data Using Gower
Distance
Maximum Likelihood Estimation of the Generalized Poisson
Distribution
Unifying Multiple Biplot Visualisations into a Single Display
Gaussian Processes for Pareto Front Estimation and Optimization
Derivative Free Gradient Projection Factor Rotation
Tools for Gaussian Process Modeling in Uncertainty
Quantification
Combining Tree-Boosting with Gaussian Process and Mixed Effects
Models
Comprehensive Statistical Analysis of Plant Breeding Experiments
Differential Item Functioning in Generalized Partial Credit
Models
Gaussian Process Classification as Described in Bachoc et al.
(2020)
Gaussian Process for Functional Data Analysis
Graphical Visualizations Related to Genomic Prediction
Solving Complex Game Problems using Gaussian Processes
Fast Gaussian Process Computation Using Vecchia's Approximation
Utilities for the Open Geospatial Consortium 'GeoPackage' Format
Convert Chip ID of the GPL2015 into GeneBank Accession and
ENTREZID
General Purpose Gaussian Process Modelling
Generalized Partial Linear Models (GPLM)
Various R Programming Tools for Plotting Data
Generalized Partially Linear Tree-Based Regression Model
Analysing and Plotting Genotype-Phenotype Maps
Penalized Likelihood in Gaussian Processes
Gaussian Process Regression for Mortality Rates
Generalized Propensity Score Cumulative Distribution Function
Sequential Clustering Algorithm for Location Data
Generalized Promotion Time Cure Model with Bayesian Shrinkage
Priors
Gaussian Processes on Graphs and Lattices in 'Stan'
A Convenient R Interface with the OpenAI 'ChatGPT' API
Dividing Local Gaussian Processes for Online Learning Regression
Use Large Language Models Directly in your Development
Environment
Identify Text Written by Large Language Models using 'GPTZero'
Maximum Likelihood Estimation of Multiple Membership Mixed
Models Used in Value-Added Modeling
Identify Efficient Crossing Schemes for Gene Pyramiding
Prediction of G Quadruplexes and Other Non-B DNA Motifs
Genome-Wide Robust Analysis for Biobank Data (GRAB)
Probability of Detection for Grab Sample Selection
Granularity-Based Spatially Variable Genes Identifications
Graph-Constrained Estimation and Hypothesis Tests
Helps Grade Assignment Submissions in Common R Formats
Stochastic Quasi-Gradient Differential Evolution Optimization
Gradient Descent LASSO with Stability Selection and Bootstrapped
Confidence Intervals
Easy Graphs for Data Visualisation and Linear Models for ANOVA
Supervised Machine Learning for Textual Data Using Transformers
and 'Quanteda'
Landscape Connectivity, Habitat, and Protected Area Networks
Guidelines for Reporting About Network Data
Graph Release with Assured Node Differential Privacy
Comprehensive Analysis of Nucleotide Conversion Sequencing Data
Inference on Granger-Causality in the Frequency Domain
Granger Causality Testing for Time Series
Graphical Analysis of Variance Using ggplot2
Collection of Shiny Apps for Agricultural Research Data Analysis
A Wrapper of the JavaScript Library 'vis-graph3d'
Build Graphs for Landscape Genetics Analysis
Hierarchical Graph Clustering for a Collection of Networks
A Multi-Platform GUI for Drawing Customizable Graphs in R
Statistical Methodology for Graphical Extreme Value Models
Graphical VAR for Experience Sampling Data
Additional Layout Algorithms for Network Visualizations
A Collection of Graphon Estimation Methods
Generates Mixture Graphs from Dense and Sparse Graphons
Estimating and Displaying Population Attributable Fractions
Models for Correlation Matrices Based on Graphs
Rank in Similarity Graph Edge-Count Two-Sample Test (RISE)
Simulate Expression Data from 'igraph' Networks
Groupwise Regularized Adaptive Sparse Precision Solution
Graceful 'ggplot'-Based Graphics and Other Functions for GAMs
Fitted Using 'mgcv'
Generating Time Series with Diverse and Controllable
Characteristics
Inflators for Australian Policy Analysis
Bayes Nets: 'RHugin' Emulation with 'gRain'
Explore Probability Distributions for Bivariate Temporal
Granularities
One Sector Armington-CES Gravity Model with General Equilibrium
Gravitational and Magnetic Attraction of 3-D Vertical
Rectangular Prisms
Inference in Graphical Gaussian Models with Edge and Vertex
Symmetries
Generate Optimal Row-Column Factorial Experiments
Modified Poisson Regression of Grouped and Right-Censored Counts
Gene Registration from Expression and Time-Courses in R
Gradient-Based Recognition of Spatial Patterns in Environmental
Data
Clustering and Model Selection with the Integrated
Classification Likelihood
Routines for Writing Greek Letters and Mathematical Symbols on
the 'RStudio' and 'RGui'
Sensitivities of Prices of Financial Options and Implied
Volatilities
HM Treasury Green Book Cost-Benefit Analysis Primitives
Combine Categories Using Greenacre's Method
Run 'Stan' Models to Interpret Green Crab Monitoring Assessments
Geospatial Regression Equation for European Nutrient Losses
(GREEN)
Green Index Quantification, Analysis and Visualization
Access and Analyze Global GreenSpace Spatial Data
Gregory Weights for Function Integration
Graph-Based k-Sample Comparisons and Relevance Analysis in High
Dimensions
Mixed-Effects REML Incorporating Generalized Inverses
Efficient Data Filtering and Aggregation Using Grep
Generalized Path Analysis for Social Networks
A Seamless Integration of 'Gretl' and 'R'
Gene ID Mapping for Genotype-Tissue Expression (GTEx) Data
Toolbox for Model Building and Forecasting
Bivariate Copula Functions Based on Regular Grid
Miscellaneous Functions for "Grid" Graphics
Redraw Base Graphics Using 'grid' Graphics
Enrich Figures and Tables with Custom Headers and Footers and
More
Native 'LaTeX' Math Rendering for Grid Graphics
Approximate Optimal Transport Between Two-Dimensional Grids
A Simulation Tool to Determine the Required Sample Size for
Repertory Grid Studies
Improved Text Rendering Support for 'Grid' Graphics
Bayesian Inference for A|B and Bandit Marketing Tests
Genetic-Relationship-Matrix Structural Equation Modelling
(GRMSEM)
Recursive Partitioning for Graded Response Models
General Regression Neural Networks Package
Creating Flexible, Reproducible 'PDF' Reports
Generalized Regression on Orthogonal Components
A Coding Assistant using the Fast AI Inference 'Groq'
Version-Control for CRAN, GitHub, and GitLab Packages
Inferring Group Bayesian Networks using Hierarchical Feature
Clustering
Comparing Two Groups Using Various Descriptive Statistics
Efficient Estimation of Grouped Survival Models Using the Exact
Likelihood Function
Optimal Assignment of Students to Groups
Independent Component Analysis for Grouped Data
Group Response Adaptive Randomization for Clinical Trials
Group Sequential Design Probabilities - With Graphical User
Interface
Multiple Testing Procedure for Grouped Hypotheses
Grouped Weighted Quantile Sum Regression
Wavelet Functional ANOVA Through Markov Groves
Implementation of the Vegetation Model ModVege
Multivariate Normal and Elliptically-Contoured Repeated
Measurements Models
Data Cleaner for Anthropometric Measurements
Simple Metrics to Summarize Growth Curves
Functional Analysis of Phenotypic Growth Data to Smooth and
Extract Traits
Bayesian reconstruction of growth velocity
Estimate Growth Rates from Experimental Data
Toolkit for Data Processing, Quality, and Statistical Models
Penalized Cox Model for High-Dimensional Data with Grouped
Predictors
Fitting User-Specified Models with Group Lasso Penalty
Group Elastic Net Regularized GLMs and GAMs
Regularization Paths for Regression Models with Grouped
Covariates
Group Sequential Analysis of Clinical Trials
String Patterns and Statistical Differences Between Two Groups
of Strings
Testing Gene-Environment Interactions Through Genetic Risk
Scores
River Hydrograph Separation and Analysis
Compute Global Sensitivity Analysis Indices Using Optimal
Transport
Two Functions for Generalized SARIMA Time Series Simulation
Estimate Parameters in the Generalized SBM
Generalized Structure Component Analysis- Latent Class Analysis
& Latent Class Regression
Utilities for Geo-Spatial Cluster Detection and Significance
Classification
Group Sequential Designs with Negative Binomial Outcomes
Simulating Admixed Genotypes Without Replacement
Group Sequential Design with Non-Constant Effect
Sample Size and Simulation for Negative Binomial Outcomes
Dependency-Aware Scenario Exploration for Group Sequential
Designs
Robust Estimation in the Presence of Cellwise and Casewise
Contamination and Missing Data
Creates Group Sequential Trial Designs when Early Outcomes are
Available
Improve the Coherence of Your Time Series Data
Download Google Sheets Using Just the URL
High Efficient Functions to Decode NFL Player IDs
GSL Multi-Start Nonlinear Least-Squares Fitting
Global Sea Level and Oxygen Isotope Data
Group Sequential Designs of Multi-Arm Multi-Stage Trials
Group Sequential Clinical Trial Designs for Composite Endpoints
Global Surface Summary of the Day ('GSOD') Weather Data Client
Base Class and Methods for 'gson' Format
Generalized Supervised Principal Component Regression
Group Sequential Refined Secondary Boundary
Progression Analysis of Disease with Survival using Topological
Data Analysis
Spatial and Spatio-Temporal Geostatistical Modelling, Prediction
and Simulation
Graph-Based Sequential Change-Point Detection for Streaming Data
Utilities for Strings and Function Arguments
Estimation of the Generalized Symmetry Point, an Optimal
Cutpoint in Continuous Diagnostic Tests
Easily Create Presentation-Ready Display Tables
Generalizability Theory for Information Retrieval Evaluation
Automating 'GTAP' Data Processing and Visualization
Convex Optimal Designs for Group Testing Experiments
The Generalized Time-Dependent Logistic Family
New Nonparametric Tests for Multivariate Paired Data and Pair
Matching
Extending 'gt' for Beautiful HTML Tables
Generalized Application of Co-Occurrence Matrices and Haralick
Texture
Estimating Public Transport Emissions from General Transit Feed
Specification (GTFS) Data
Converting Transport Data from GTFS Format to GPS-Like Records
Read and Write General Transit Feed Specification (GTFS) Files
Routing with 'GTFS' (General Transit Feed Specification) Data
General Transit Feed Specification (GTFS) Editing and Analysing
Tools
Simple Generalizability Theory for Crossed and Nested Designs
Tools for Creating Publication-Ready Regression Tables
Query the 'Google Trends for Health' API
Perform and Display Google Trends Queries
Presentation-Ready Data Summary and Analytic Result Tables
Genome and Transcriptome Wide Association Study
Nombres Inscritos en Chile (1920 - 2021)
Access 'The Guardian' Newspaper Open Data API
Bayesian Modal Regression Based on the GUD Family
Maps, Data and Methods Related to Guerry (1833) "Moral
Statistics of France"
Real-Time PCR Data Sets by Guescini et al. (2008)
Adjust Estimates of Learning for Guessing
Graphical Models in Ultrahigh-Dimensional and Error-Prone Data
via Boosting Algorithm
Supervised Dimensional Reduction by Guided Partial Least Squares
Miscellaneous Statistical Functions Used in 'guide-R'
Implementation of Sampling Formulas for the Unified Neutral
Model of Biodiversity and Biogeography, with or without Guild
Structure
General Unilateral Load Estimator for Two-Layer Latent Factor
Models
Bootstrap Analyses of Sampling Uncertainty in Goodness-of-Fit
Statistics
Generalized UniFrac Distances, Distance-Based Multivariate
Methods and Feature-Based Univariate Methods for Microbiome
Data Analysis
Statistical Analysis of Monthly Background Checks of Gun
Purchases
A User-Oriented Statistical Toolkit for Analytical Variance
Estimation
Download and Process Public Domain Works from Project Gutenberg
Fast Calculation of the Likelihood of a Stochastic Survival
Model
Perform Global Vector Autoregression Estimation and Inference
Global Value Chain Decomposition for Value-Added Trade
Global Validation of Linear Models Assumptions
Interactive Exploratory Data Analysis Tool
Manhattan, Q-Q, and PCA Plots using 'ggplot2'
GWAS-to-CRISPR Data Pipeline for High-Throughput SNP Target
Extraction
Identifying Significant SNPs in Genome Wide Association Studies
(GWAS) via Clustering
Exact Hardy-Weinburg Testing for Genome Wide Association Studies
Non-Local Prior Based Iterative Variable Selection Tool for
Genome-Wide Association Studies
Comprehensive and Easy to Use Quality Control of GWAS Results
'REST' 'API' Client for the 'NHGRI'-'EBI' 'GWAS' Catalog
Multi-Site Stochastic Models for Daily Precipitation and
Temperature
Count and Continuous Generalized Variability Indexes
Rewrite of gWidgets API for Simplified GUI Construction
Toolkit Implementation of gWidgets2 for tcltk
Geographically Weighted Logistic Elastic Net Regression
Geographically Weighted Non-Negative Principal Components
Analysis
G-Wishart Normalising Constants for Gaussian Graphical Models
Geographically Weighted Partial Correlation Coefficient
Geographically Weighted Partial Correlation Mapper
Generalized Weighted Quantile Sum Regression
A Hybrid Model for Spatial Prediction Through Local Regression
Generalized Waring Regression Model for Count Data
Fits Geographically Weighted Regression Models with Diagnostic
Tools
GroundWater Spatiotemporal Data Analysis Tool (GWSDAT)
Estimating Genome-Wide Significance for Whole Genome Sequencing
Studies, Either Single SNP Tests or Region-Based Tests
Geographically Weighted Zero Inflated Negative Binomial
Regression
Genotype-by-Environment Interaction in Polygenic Score Models
Run GWAS/GWEIS Scans Using Binary Dosage Files
A Robust Bayesian Meta-Analysis for Estimating the Hubble
Constant via Time Delay Cosmography
R Interface for the 'H2O' Scalable Machine Learning Platform
Machine Learning Model Evaluation for 'h2o' Package
Sample Size Calculation in Hierarchical 2x2 Factorial Trials
Exposes the 'Uber' 'H3' Library to R Packages
Hexagonal Hierarchical Geospatial Indexing System
Species Distribution Modeling with H3 Grids
Software to Perform Haar Fisz Transforms
Tools and Metrics for 3D Surfaces and Objects
Estimation, Simulation and Visualization of Hierarchical
Archimedean Copulae (HAC)
Wrapper for the 'Official Hacker News' API
Iterative Extrapolation of Species' Haplotype Accumulation
Curves for Genetic Diversity Assessment
Analysis and Visualisation of Hydrogen/Deuterium Exchange Mass
Spectrometry Data
Incomplete Block Designs using Hadamard Matrix (HadIBDs)
Analysis of Plant Pathogen Pathotype Complexities, Distributions
and Diversity
Haplotype-Aware Hidden Markov Model for RNA
Authenticated HTTP Request Client for the 'Hakai' API
Highly Adaptive Lasso Conditional Density Estimation
Hierarchical Optimal Matching and Machine Learning Toolbox
A 'shiny' Application for Handwriting Analysis
Handwriting Analysis with Random Forests
Package for Easy Interpretation of Statistical Methods
Convert Chinese Characters into Hanyu Pinyin
Inference of Trait Associations with SNP Haplotypes and Other
Attributes using the EM Algorithm
Inference of Chromosome-Length Haplotypes Using Genomic Data of
Single Gamete Cells
Analyzing Case-Parent Triad and/or Case-Control Data with SNP
Haplotypes
Statistical Analysis of Haplotypes with Traits and Covariates
when Linkage Phase is Ambiguous
Calculate F Statistics Using Mixed Haploid and Diploid Organism
Data
Tool for Clustering Genotypes in Haplotypes
Manipulating DNA Sequences and Estimating Unambiguous Haplotype
Network with Statistical Parsimony
Defining Local Haplotype Variants for Use in Trait Association
and Trait Prediction Analyses
A Unified Time Series Event Detection Framework
Statistical Tests and Graphics for Hardy-Weinberg Equilibrium
Harmonic Mean p-Values and Model Averaging by Mean Maximum
Likelihood
Fast, Sensitive, and Accurate Integration of Single Cell Data
Enhanced R Package for 'GEMPACK' .har and .sl4 Files
'HAR' ('GEMPACK') File Read/Write Utility
Wrangle Phylogenetic Distance Matrices and Other Utilities
Palettes Generated from All "Harry Potter" Movies
Full Featured Implementation of Hash Tables/Associative
Arrays/Dictionaries
Generate Short Unique YouTube-Like IDs (Hashes) from Integers
A Test for Comparing the Predictive Accuracy of Two Sets of
Forecasts
Hasse Diagram of the Layout Structure and Restricted Layout
Structure
Hatemi-J Cointegration Test with Two Unknown Regime Shifts
Survey Indicator Estimation for Complex Survey Designs
One- And Two-Sample Hausdorff Goodness-of-Fit Test
Visualize and Tabulate 'R' Package Dependencies
Import and Export 'SPSS', 'Stata' and 'SAS' Files
Hawkes process simulation and calibration toolkit
Estimation of Hawkes Processes from Binned Observations
Conditional Treatment Effect for Competing Risks
Identifying Foggy and Cloudy Images by Quantifying Haziness
Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan'
Hierarchical Bayesian Benefit-Risk Assessment Using Discrete
Choice Experiment
Hill/Bliss Independence Model for Combination Vaccines
Hierarchical Bayesian Analysis of Recognition Memory
Hierarchical Bayesian Small Area Estimation
Hierarchical Bayes Small Area Estimation Model using 'Stan'
Hierarchical Bayesian Space-Time Models for Gaussian Space-Time
Data
Interval Estimation of Linear Models with Heteroskedasticity
Hierarchical Community Detection by Recursive Partitioning
Design and Analysis of Hierarchical Composite Endpoints
Hierarchical Clustering of Univariate (1d) Data
Hierarchical Cluster Analysis (Learning Didactically)
Regression with a Large Number of Potential Explanatory
Variables
Hierarchical Conformal Prediction for Clustered Data with
Missing Responses
Causal Discovery from Discrete Data using Hidden Compact
Representation
Estimate, Compare, and Visualize Healthcare Resource Utilization
for Real-World Evidence
Group Sequential Design for Historical Control Trial with
Survival Outcome
Using Historical Controls for Designing Phase II Clinical Trials
Access and Work with HCUP Resources and Datasets
'REST' API Client for Accessing Data on 'WEkEO HDA V2'
Bayesian Analysis of Generalized Linear Models with Historical
Data
Bayesian Change Point Detection for High-Dimensional Data
Change-Point Analysis of High-Dimensional Time Series via Binary
Segmentation
Bayesian Mediation Analysis with High-Dimensional Data
High Dimensional Bayesian Ridge Regression without MCMC
Estimation of Conditional Average Treatment Effects with
High-Dimensional Data
High Dimensional Confidence Interval Based on Lasso and
Bootstrap
High Dimensional Supervised Classification and Clustering
Clustering High Dimensional Data with Hidden Markov Model on
Variable Blocks
Detect Change Points in Means of High Dimensional Data
Easy Manipulation of Out of Memory Data Sets
Interface to the 'HDF5' Binary Data Format
High-Dimensional Functional Time Series Analysis
Tests for High Dimensional Generalized Linear Models
A Batch Process for High Dimensional Imputation
Statistical Inference for Noisy Vector Autoregression
Distribution-Free Exact High Dimensional Low Sample Size
k-Sample Tests
ADMM for High-Dimensional Mediation Models
High-Dimensional Regression with Measurement Error
A Multiple Testing Procedure for High-Dimensional Mediation
Hypotheses
Inference for High-Dimensional Mixture Transition Distribution
Models
Benchmarking and Visualization Toolkit for Penalized Cox Models
High-Dimensional Location Testing with Normal-Reference
Approaches
High-Dimensional Orthogonal Maximin Distance Designs
Leland Wilkinson's Algorithm for Detecting Multidimensional
Outliers
Principal Component Analysis in High-Dimensional Data
Hierarchical Dirichlet Process Generalized Linear Models
Fast Algorithm for Penalized Quantile Regression
Highest Density Regions and Conditional Density Estimation
Data for the 'Mastering Health Data Science Using R' Online
Textbook
Multivariate and Functional Spatial Scan Statistics
High Dimensional Stimulation Immune Mapping ('HDStIM')
Fast Algorithm for Support Vector Machine
Generate Samples from Multivariate Truncated Normal
Distributions
Inference on Many Jumps in Nonparametric Panel Regression Models
High Dimensional Time Series Analysis Tools
The Lasso for Tweedie's Compound Poisson Model Using an IRLS-BMD
Algorithm
Analysis of Hydrogen-Deuterium Exchange Mass-Spectrometry Data
Compose Sentences to Describe Comparisons
Explore and Import 'Metopio' Health Atlas Data and Spatial
Layers
Compute Summary Measures of Health Inequality
Financial Projections and Planning for Health Care Practices
Quantifying and Monetizing Health Impacts Attributable to
Exposure
A Comprehensive Collection of Health and Human Motion Datasets
The Machine Learning and AI Modeling Companion to 'healthyR'
The Time Series Modeling Companion to 'healthyR'
Correction of Heaping on Individual Level
Easily Download Heaps of PDF and CSV Files
A Workflow to Process Data Collected with PULSE Systems
Heat exchange calculations during physical activity
Fit Statistic for Binary Dependent Variable Models
Interactive Cluster Heat Maps Using 'plotly' and 'ggplot2'
A Self-Contained Widget for Interactive Phylogenetic Tree
Visualization
Estimators and Algorithms for Heavy-Tailed Distributions
Fit Normal, Student-t or Contaminated Normal Heckman Selection
Models
Estimation and Inference for Heckman Selection Models with
Cluster-Robust Variance
Heckman Selection Models Based on Bayesian Analysis
Markov Models for Health Economic Evaluations
Decode and Validate HEIMS Data from Department of Education,
Australia
Score and Plot the Healthy Eating Index from NHANES Data
Providing 'stringsAsFactors=FALSE' Variants of 'data.frame()'
and 'as.data.frame()'
Datasets from the Hello Data Science Book
Minimal Examples of Using Rust Code in R
Visualizing Hypothesis Tests in Multivariate Linear Models
Companion to the 'xeus-r' 'jupyter' Kernel
'sf'-Based Interface to the 'HERE' REST APIs
Marker-Based Estimation of Heritability Using Individual Plant
or Plot Data
Heritability Estimation from Mixed Models
Efficient Sequential and Batch Estimation of Univariate and
Bivariate Probability Density Functions and Cumulative
Distribution Functions along with Quantiles (Univariate) and
Nonparametric Correlation (Bivariate)
Health Economic Simulation Modeling and Decision Analysis
Heritability-Based Estimation of Sample Size for RNA-Seq Data
Unsupervised Feature Selection using the Heterogeneous
Correlation Matrix
Test of No Main and/or Interaction Effects in Functional Data
Semi-Parametric Estimation with Gaussian Copula
Spatial Functions for Heterogeneity and Climate Variability
Convert Various Meta-Analysis Heterogeneity Measures
Copula Graphical Models for Heterogeneous Mixed Data
Heteroskedastic Gaussian Process Modeling and Design under
Replication
Identifying Modulators of Cellular Responses Leveraging
Intercellular Heterogeneity
Assessing Heterogeneity in the Utility of a Surrogate Marker
Assessing Heterogeneity in Surrogacy Using Censored Data
Testing for a Treatment Effect Using a Heterogeneous Surrogate
Marker
Fisherian and Neymanian Methods for Detecting and Measuring
Treatment Effect Variation
Structural Handling of Finnish Personal Identity Codes
Heuristic Capacitated Vehicle Routing Problem Solver
Heuristics Including Take the Best and Unit-Weight Linear
Fast Kernel Density Estimation with Hexagonal Grid
Equal-Area Hex Grids on the 'Snyder' 'ISEA' 'Icosahedron'
Create a Tile of Logos for Loaded Packages
Integrated Tool for Hairping Extraction of RNA Sequences
Estimate Hierarchical Feature Regression Models
Hysteretic and Gatekeeping Depressions Model
Holonomic Gradient Method and Gradient Descent
Heterogeneous Graphical Model for Non-Negative Data
Identify and Correct Invalid HGNC Human Gene Symbols and MGI
Mouse Gene Symbols
Hierarchical and Geographically Weighted Regression
Statistical Analysis and Data Display: Heiberger and Holland
Bayesian Household Transmission Modeling with 'Stan'
Fitting Household Transmission Model to Estimate Household
Transmission Dynamics of Influenza
Age-Structured Spatio-Temporal Models for Infectious Disease
Counts
Hierarchical Heterogeneity Analysis via Penalization
Hidden Hybrid Markov/Semi-Markov Model Fitting
The Hilbert-Huang Transform: Tools and Methods
Individual-Level, Summary-Level and Single-Step Bayesian
Regression Model
Example HiC and Two 'HiCociety' Outputs for Demonstration and
Testing
The All-Configurations, Maximum-Interaction F-Test for Hidden
Additivity
Create HIDECAN Plots for Visualising Genome-Wide Association
Studies and Differential Expression Results
Calculate Clinical Scores for Hidradenitis Suppurativa (HS), a
Dermatologic Disease
Set Data Visualization Using Hierarchies
Estimation and Tests of Hierarchical F-Statistics
Penalized Regression with Hierarchical Nested Parameterization
Structure
Hierarchical Risk Clustering Portfolio Allocation Strategies
Nonnegative Garrote Method Incorporating Hierarchical
Relationships
High-Dimensional Tests for Two Population Mean Vectors
Testing Two-Sample Mean in High Dimension
Implementation of Voting Rules Electing the Candidate with
Highest Median Grade
The 'HighFive' 'C++' Interface to 'HDF5'
Code Syntax Highlighting using the 'Prism.js' Library
Highlight Conserved Edits Across Versions of a Document
Feature Selection for High Dimensional Survival Data
Design of High-Order Portfolios Including Skewness and Kurtosis
Determining and Evaluating High-Risk Zones
Simultaneous Critical Values for t-Tests in Very High Dimensions
Statistical Inference for Online Learning and Stochastic
Approximation via HiGrad
Hilbert Similarity Index for High Dimensional Data
Create Hillshade Relief Maps Using Ray-Tracing
H-Index Calculator using Data from a Web of Science (WoS)
Citation Report
Tools for Hypothesis Testing Based on Hypergeometric
Intersection Distributions
Parentage Assignment using Bi-Allelic Genetic Markers
Non-Targeted Fluxomics on High-Resolution Mass-Spectrometry Data
Summary Statistics for Histogram/Count Data
Data Sets from the History of Statistics and Data Visualization
Construction of Regular and Irregular Histograms with Different
Options for Automatic Choice of Bins
Non-Longitudinal Bayesian Historical Borrowing Models
Longitudinal Bayesian Historical Borrowing Models
"Hit and Run" and "Shake and Bake" for Sampling Uniformly from
Convex Shapes
Six-Year Chronological Data of HIV and ART Cases in Pakistan
Interactive Dashboard for 'HIV' Data Visualization
Hierarchical Joint Analysis of Marginal Summary Statistics
Conversion Tools for HK80 Geographical Coordinate System
Spatial Extreme Value Analysis with the Hierarchical Model of
Reich and Shaby (2012)
Apps and Data for the Book "Introduction to Statistics"
Diagnostic Tools for Hierarchical (Multilevel) Linear Models
Hierarchical Linear Modeling with Visualization and
Decomposition
Algebraic Operations and Visualisation for Hl-Rhotrices
High-Dimensional Mean Comparison with Projection and
Cross-Fitting
Hidden Markov Cognitive Diagnosis Models for Learning
Fit Statistical Models Using Hamiltonian Monte Carlo
Holistic Multimodel Domain Analysis for Exploratory Machine
Learning
Hierarchical Methods for Differential Equations
Read Human Mortality Database and Human Fertility Database Data
from the Web
Fit the Meta-D' Model of Confidence Ratings Using 'brms'
Hidden Markov Model for Predicting Time Sequences with Mixture
Sampling
Hidden Markov Models with Discrete Non-Parametric Observation
Distributions
Markov Regime Switching Copula Models Estimation and
Goodness-of-Fit
Inference and Estimation of Hidden Markov Models and Hidden
Semi-Markov Models
Analysing Accelerometer Data Using Hidden Markov Models
"Mixture and Hidden Markov Models with R" Datasets and Example
Code
Hidden Markov Models for Reliability and Maintenance
Fit Hidden Markov Models using Template Model Builder
Flux Estimation with Static Chamber Data
Download and Tidy 'HMRC' Statistical Data
Hierarchical Model of Species Communities
Health Metrics and the Spread of Infectious Diseases
Half-Normal Plots with Simulation Envelopes
Hierarchical Neyman-Pearson Classification for Ordered Classes
Higher Order Assortativity for Complex Networks
Download and Visualize Essential Climate Change Data
Covariate Adjustment in RCT by Higher-Order Influence Functions
Higher Order Likelihood Inference Web Applications
Statistics for Holland's Theory of Vocational Choice
Chat Completion and Text Annotation with Local and OpenAI Models
A Tidy Interface for Simulating Multivariate Data
A User-Friendly R 'shiny' Application for Multi-Omics Data
Integration and Analysis
Methods for Closed Testing with Simes Inequality, in Particular
Hommel's Method
Quick Access to Homologene and Gene Annotation Updates
BFV, BGV, CKKS Schema for Fully Homomorphic Encryption
Robust Inference in Difference-in-Differences and Event Study
Designs
Access Men's Basketball Play by Play Data
Transmissions and Receptions in a Hop by Hop Network
Hierarchical Ordered Probit Models with Application to Reporting
Heterogeneity
Calculate Hopkins Statistic for Clustering
Supplemental Functions and Datasets for "Handbook of Regression
Methods"
Horn's (1965) Test to Determine the Number of Components/Factors
Provide Extensions to the Prussian Army Death by Horsekick Data
Building Networks of Hospitals Through Patients Transfers
Hotelling’s T-Squared Statistic and Ellipse
Runtime Namespace Patching Utilities for R Packages
Manipulation of (Large) Memory-Mapped Objects (Vectors, Matrices
and Arrays)
CSS Animations for 'shiny' Button Elements
Calculate How many Imputations are Needed for Multiple
Imputation
High Performance Cluster Models Based on Kiefer-Wolfowitz
Recursion
The One- And Two-Sided Hodrick-Prescott Filter
Superefficient Estimation of Future Conditional Hazards Based on
Marker Information
Miscellaneous Convenience Functions and Dataset
Regularization Paths for Lasso or Elastic-Net Penalized Huber
Loss Regression and Quantile Regression
Better Data Engineering in Human Resources
Additional Themes, Theme Components and Utilities for 'ggplot2'
Nonparametric Assessment Between Competing Risks Hazard Ratios
Group Variable Selection for Quantile and Robust Mean Regression
Half Replicate of Two Level Factorial Run Order with Minimum
Level Changes
Historical, Relational, and Tail Anomaly-Detection Algorithms
Datasets, Functions and Scripts for Semiparametric Regression
Supporting Harezlak, Ruppert & Wand (2018)
A Handbook of Statistical Analyses Using R (1st Edition)
A Handbook of Statistical Analyses Using R (2nd Edition)
A Handbook of Statistical Analyses Using R (3rd Edition)
Calculation of Covariance Between Markers for Half-Sib Families
Hierarchical Bayesian Species Distribution Models
Sets of Numbers Implemented with Hash Tables
Phasing, Pedigree Reconstruction, Sire Imputation and
Recombination Events Identification of Half-sib Families Using
SNP Data
Hidden Smooth Polynomial Regression for Rupture Detection
Estimation of Recombination Rate and Maternal LD in Half-Sibs
Hierarchical Shrinkage Stan Models for Biomarker Selection
Budget Impact Modelling for Health Technology Assessment
Hypothesis Testing for Dependent Variables with Unbalanced Data
Reweighted Marginal Hypothesis Tests for Clustered Data
Causal Inference with Tree-Based Machine Learning Algorithms
Two Dimensional High Throughput 'GoMiner'
Three Dimensional High Throughput 'GoMiner'
Four Dimensional High Throughput 'GoMiner'
Bayesian Logistic Regression with Heavy-Tailed Priors
Convert Local 'HTML' and 'XHTML' Files to 'PDF'
Convert 'HTML' to 'R' with a 'Shiny' App
Facilitates Automated HTML Report Creation
Build Modern Web Applications with 'htmx' and 'plumber2'
Haplotype Trend Regression with eXtra Flexibility (HTRX)
Clustering High-Throughput Transcriptome Sequencing (HTS) Data
Degenerate Hierarchical Time Series Reconciliation
Fitting of Hydrotime Model for Seed Germination Time Course
Hydro Thermal Time Analysis of Seed Germination Using
Generalised Linear Model
Report Errors in Web Applications with 'Problem Details' (RFC
7807)
Perform HTTP Requests and Process the Responses
Get Data from the French National Database on Water 'Hub'Eau'
Ensemble Methods for Combining Hub Model Outputs
Providing Data from the US Department of Housing and Urban
Development
Distinct Colour Palettes Based on 'iwanthue'
Compute HUM Value and Visualize ROC Curves
Calculate Water Vapor Measures from Temperature and Dew Point
High-Performance Stemmer, Tokenizer, and Spell Checker
Models Hurricane Wind Speed, Wind Direction, and Wind Damage
Explore and Map County-Level Hurricane Exposure in the United
States
Easily Create and Style Tables for LaTeX, HTML and Other Formats
Constructing Hierarchical Voronoi Tessellations and Overlay
Heatmaps for Data Analysis
Models and Tests for Departure from Hardy-Weinberg Equilibrium
and Independence Between Loci
Objective Bayesian Testing for the Hardy-Weinberg Equilibrium
Problem
HTML Writer - Outputs R Objects in HTML Format
Hybrid Design for Phase I Dose-Finding Studies
Synthetic Hybrid Electronic Health Record Generation for
SARS-Related Research and CT Views
Analysis of Host-Associated Microbiomes from Hybrid Organisms
An R Package for the Stochastic Simulation of Disease Spreading
in Dynamic Networks
Function that Creates a Heat Map from Hybridization Data
Hybrid Time Series Forecasting Using Error Remodeling Approach
1d Water Level Interpolation along the Rivers Elbe and Rhine
Flood Extents and Duration along the Rivers Elbe and Rhine
Duration Curve Hydrological Model Indexes
Hydrologic Station Catalogs and Time Series from Public APIs
Hydrological Evaluation Metrics and Goodness-of-Fit Summaries
Extract Event Statistics in Hydrologic Time Series
Goodness-of-Fit Functions for Comparison of Simulated and
Observed Hydrological Time Series
Estimating Water Retention and Infiltration Model Parameters
using Experimental Data
Multi-Objective Optimisation with Focus on Environmental Models
Detect and Characterize Sub-Daily Flow Fluctuations
Hidden Markov Modelling of Hydrological State Change
Hydrologic Indices for Daily Time Series Data
Hydrological Tools for Handling Hydro-Meteorological Data
Records
Hydrological Tools for Handling Hydro-Meteorological Data from
Argentina and Chile
Time Series Management and Analysis for Hydrological Modelling
Hydrologic Model Evaluation and Time-Series Tools
N-Dimensional Hyperplane Fitting with Errors
Generalized Additive Models with Hyper Column
Machine Learning of Hyperrectangular Gating Strategies for
High-Dimensional Cytometry
Generalized Hypergeometric Function with Tunable High Precision
Overlap Detection in n-Dimensional Space
Work with Hyperspectral Data, i.e. Spectra + Meta Information
(Spatial, Time, Concentration, ...)
High Dimensional Geometry, Set Operations, Projection, and
Inference Using Kernel Density Estimation, Support Vector
Machines, and Convex Hulls
Tools for Processing and Analyzing Files from the Hydrological
Catchment Model HYPE
Wrapper for the 'Hypothes.is' Web Annotation Service
Estimate Latent Classes on a Mixture of Continuous and
Dichotomous Data
Multicriteria Risk Management using Zero-Sum Games with
Vector-Valued Payoffs that are Probability Distributions
Hybrid Genetic and Simulated Annealing Algorithm for High
Dimensional Linear Models with Interaction Effects
Fit the Hysteretic Threshold Autoregressive Model
Tools for Modeling Rate-Dependent Hysteretic Processes and
Ellipses
Get Pedestrian Frequency Data from the 'Hystreet' Project
Hypothesis Testing Based on Neyman-Pearson Lemma and Likelihood
Ratio Test
Likelihood-Based Inference for Joint Modeling of Correlated
Count and Binary Outcomes with Extra Variability and Zeros
Internationalization Data from the 'Unicode CLDR' in Tabular
Form
Incentives for Inter- And Intra-Party Electoral Competition
Data and Functions for "An Intro. to Accept. Samp. & SPC/R"
Two-Stage Adaptive Dose-Finding Clinical Trial Design
Analysis of Intra Annual Density Fluctuations
Interaction Difference Test for Prediction Models
Iterative Alternating Least Square Estimation for
Large-Dimensional Matrix Factor Model
Formulations of the International Association for the Properties
of Water and Steam
Thermophysical Properties of Water and Steam
Model Selection for Index of Asymmetry Distribution
Compute Effect Sizes and Reliability for Implicit Association
Test (IAT) Data
Scoring Algorithm for the Implicit Association Test (IAT)
Implicit Association Test Scores Using Robust Statistics
Functions and Datasets for the Data Science Course at IBAW
R Wrapper for Istanbul Municipality Open Data Portal
Item Based Collaborative Filtering for Multi-Trait and
Multi-Environment Data
Information Bottleneck Methods for Clustering Mixed-Type Data
HMM Toolkit for Inferring IBD Segments from SNP Genotypes
Design-Based Causal Inference Method for Incomplete Block
Designs
Identity by Descent Probability in Pedigrees
Simulation of Chromosomal Regions Shared by Family Members
Initial Basic Feasible Solution for Transportation Problem
Access the 'IBGE' Aggregate Data API from 'R'
R Client for the Interactive Brokers Client Portal API
Toolkits to Develop Individual-Based Models in Infectious
Disease
Individual Based Model Population Simulation
Generate Personality Insights Sunburst Diagrams
Model Agnostic Instance Level Variable Attributions
R API to Interactive Brokers Trader Workstation
Integrating Biomarker-Based Assessments and Radarchart Creation
Inequality Constrained Inference in Linear Normal Situations
A Copy Number and Expression-Based Classifier for Breast Tumours
Infer Community Assembly Mechanisms by Phylogenetic-Bin-Based
Null Model Analysis
Optimal Designs for Nonlinear Models via ICA
Subsetting using Focused Identification of the Germplasm
Strategy (FIGS)
Calibrates and Reweights Units in Samples
Data-Driven Design of Targeted Gene Panels for Estimating
Immunotherapy Biomarkers
Facilitating Estimation of the Intraclass Correlation
Coefficient
Calculation of Sample Size and Power for ICC
Cox Model with Interval-Censored Starting Time of a Covariate
Multilevel Model Intraclass Correlation for Slope Heterogeneity
Facilitates Clustered Binary Data Generation, and Estimation of
Intracluster Correlation Coefficient (ICC) for Binary Data
Comparison of Dependent Intraclass Correlation Coefficients
Intraclass Correlation Coefficient for Count Data
Computation of the Double-Entry Intraclass Correlation
An Ensemble Method for Interval-Censored Survival Data
Intracluster Correlation Coefficient (ICC) in Clustered
Categorical Data
Estimates the Intraclass Correlation Coefficient for Trajectory
Data
International Classifcation of Diseases (ICD) Data
Metadata Processing for the German Modification of the ICD-10
Coding System
EM by the Method of Weights for Incomplete Categorical Data in
Generlized Linear Models
'ICD' Programs for Injury Categorization in R
Individual Conditional Expectation Plot Toolbox
Download Sea Ice Concentration Data from the NSIDC Climate Data
Record
The Equiplot Graph and Complex Inequality Measures
Analyzing High-Throughput Single Cell Sequencing Data
Regression Models for Interval Censored Data
Accompanion to the Book on Interval Censoring by Bogaerts,
Komarek, and Lesaffre
Study Design and Data Analysis in the Presence of Error-Prone
Diagnostic Tests and Self-Reported Outcomes
Provides User Tokens for Access to ICES Web Services
DATRAS Trawl Survey Database Web Services
Functions to Interact with the ICES Data Submission Utility
(DATSU)
Run Quality Checks on Data Prior to Submission to ICES
Stock Assessment Graphs Database Web Services
Functions to Support the ICES Transparent Assessment Framework
Estimation of Number of Clusters and Identification of Atypical
Units
Information Criteria for Generalized Linear Regression
Fit Generalized Odds Rate Hazards Model with Interval Censored
Data
A Button-Based GUI for Financial and Economic Data Analysis
Log-Concave Distribution Estimation with Interval-Censored Data
Fast Integrative Clustering and Feature Selection for High
Dimensional Data
Empirical Bayes Variable Selection via ICM/M Algorithm
Data Analysis for ODS and Case-Cohort Designs with
Interval-Censoring
Independent Component Analysis Based Extreme Learning Machine
Global Triangular and Penta-Hexagonal Grids Based on Tessellated
Icosahedra
Survival Analysis of Interval-Censored Data
Reproducible Data Retrieval from the ICPSR Archive
Tools for Exploring Multivariate Data via ICS/ICA
Tandem Clustering with Invariant Coordinate Selection
Interval-Censored Sequence Kernel Association Test
Outlier Detection Using Invariant Coordinate Selection
Data Smoothing by Interpolating Cubic Splines
Semiparametric Regression Analysis of Interval-Censored Data
Estimating and Testing the Number of Interesting Components in
Linear Dimension Reduction
Unified Tools for Classical and Bootstrap Confidence Intervals
Indirect Cross-Validation (ICV) for Kernel Density Estimation
Vector Fields from Spatial Time Series of Population Abundance
Datasets and Functions for the Class "Modelling and Data
Analysis for Pharmaceutical Sciences"
R Interface to the US Census Bureau International Data Base API
Update Chinese ID Card Number to Eighteen Digits
Interactive Application for Analyzing Representativeness and
Nonresponse Bias
Agnostic, Idiomatic Data Filter Module for Shiny
Easy Manipulation of IDEAM's Climatological Data
Integrating Data Exchange and Analysis for Networks ('ideanet')
Individual and Group Farm Sustainability Assessments using the
IDEA4 Method
Efficient Designs for Discrete Choice Experiments
Various Methods for Estimating Intrinsic Dimension
Isolate-Detect Method for Multiple Change-Point Detection
Integrated Differential Analysis of Multi Omics Data using a
Joint Mixture Model
Integrative Differential Network Analysis in Genomics
Shiny App. Idiograms with Marks and Karyotype Indices
Conduct Idionomic Analyses for Time Series Modeling
Interpreting Differences Between Mean ACT Scores
Assessment of Individual Identity in Animal Signals
Identification of Dysregulated MiRNAs Based on MiRNA-MiRNA
Interaction Network
A Network Tool to Dissect Spatial Community Ecology
Integrated Discovery of Oncogenic Signatures
Durability of Vaccine Efficacy Against SARS-CoV-2 Infection
'Utilities of Institute of Data Analyses and Process Design
(www.zhaw.ch/idp)'
Imprecise Dirichlet Process for Survival Analysis
Composite Spectra Analysis (CSA) for High-Resolution Mass
Spectrometry Analyses
Intrinsic Peak Analysis (IPA) for HRMS Data
Parser for mzML, mzXML, and netCDF Files (Mass Spectrometry
Data)
United Formula Annotation (UFA) for HRMS Data Processing
Exhaustive Chemical Enumeration for United Formula Annotation
Estimate Global Clustering in Infectious Disease
Convert Files to and from IDX Format to Vectors, Matrices and
Arrays
Irucka Embry's Miscellaneous USGS Functions
Irucka Embry's Miscellaneous USGS Data Collection
Functions to Set and Get the IEEE Rounding Mode
File IO for Intracranial Electroencephalography
Irucka Embry's Miscellaneous Text Collection
Indirect Effects Testing Methods in Mediation Analysis
Interface to the 'OpenGWAS' Database API
Toolkit for Item Factor Analysis with 'OpenMx'
Isolation-Forest Based 'CNV' Detection from 'NGS' Data
Italian Fiscal Code ('Codice Fiscale') Utilities
Autodiff for Influence Function Based Estimates
Simulation-Based Fitting of Parametric Models with Minimum Prior
Information
Intuitionistic Fuzzy Multi-Criteria Decision Making Methods
Client for the Ifo Institute Time Series
Machine Learning Time Series Forecasting
Predictions Using Item-Focused Tree Models
"Smith-Pittman Community Detection Algorithm for 'igraph'
Objects (2024)"
Instagram 2014 Vancouver Top Colour Dataset
Score Taxon-Level IgA Binding in IgA-Seq Experiments
Statistical Tests and Utilities for Genetic Association
Simulate Impact of Different Urban Policies Through a General
Equilibrium Model
Computational Tools for the IG and IGL Copula Families
Regression under Interference in Connected Populations
Interpreting Glucose Data from Continuous Glucose Monitors
Read Binary Files Saved by 'Igor Pro' (Including 'Neuromatic'
Data)
A Collection of Network Data Sets for the 'igraph' Package
Convert iGraph graps to SoNIA .son files
Integrative Gene Set Enrichment Analysis Approaches
For Writing Geneva Graduate Institute Documents
Download Data from the International House Price Database
Access 'Malawi Integrated Household Survey' Data
Identifying Infection with Machine Intelligence
Computing Individual Components of the Gini and the Theil
Indices
Analyzing Data Through of Percentage of Importance Indice
(Production Unknown) and Its Derivations
Datasets to Accompany Wolfe and Schneider - Intuitive
Introductory Statistics
Modeling Within Individual Variability as Predictor
Infinitesimal Jackknife Standard Errors for 'brms' Models
Comprehensive TIFF I/O with Full Support for 'ImageJ' TIFF Files
Utility Functions to Work with Israeli Central Bureau of
Statistics Municipal Data
Indian Alien Flora Information Database Retrieval
Convert Irregular Longitudinal Data to Regular Intervals and
Perform Clustering
Merge and Download International Large-Scale Assessments (ILSA)
Data
Statistics for International Large-Scale Assessments (ILSA)
Analyze Interconnection Structure of Tripartite Interaction
Networks
Incremental Mixture Approximate Bayesian Computation (IMABC)
Binarize Images for Enhancing Optical Character Recognition
Implementation of the Canny Edge Detector for Images
Implementation of the Unsupervised Smooth Contour Line Detection
for Images
Find Corners in Digital Images with FAST-9
Implementation of the Harris Corner Detection for Images
Convolutional Neural Network for Face Detection
Aids in Processing and Plotting Data from a Lemna-Tec
Scananalyzer
Image Statistics Based on Processing Fluency
Image Processing Library Based on 'CImg'
Extra Image Processing Library Based on 'imager'
Deep Learning Models for Image Segmentation
Simple 'htmlwidgets' Image Viewer with WebGL Brightness/Contrast
Tools for Studying Imaginary Cognitive Social Structure
Simulate General Insurance Policies and Losses
IMAGing engINEs, Tools for Application of Image Filters to Data
Matrices
Identify the Racial Complex of Native Corns from Mexico
Relocated Data Oversampling for Imbalanced Data Classification
Mass Cytometry S4 Class Structure Pipeline for Images
Efficiency of Cluster Sampling for Crop Surveys
Index of Multiple Deprivation Data for the UK
Get Movie, Television Data from the 'imdb' Database
Likelihood Methods for Mediation Analysis
An Interface to IMF (International Monetary Fund) Data JSON API
Non-Linear Height Diameter Models for Forestry
Seamless Access to IMF World Economic Outlook (WEO) Data
Infinite Mixtures of Infinite Factor Analysers and Related
Models
Gaussian Mixture Model for Multi-Omics Data Integration
Item Response Models for Multiple Ratings
Iterative Max-Min Entropy Margin-Maximization with Interaction
Terms for Feature Selection
Machine Learning Algorithms Fitting and Validation for Forestry
Multi-Modal Immune Repertoire Analytics for Immunotherapy and
Vaccine Design in R
Machine Learning Immunogenicity and Vaccine Response Analysis
A Unified Data Layer for Large-Scale Single-Cell, Spatial and
Bulk Immunomics
A Comprehensive Toolkit for Clinical HLA Informatics
AI Powered Neural Network Solutions for Regression Tasks
Neural Networks for Predicting Volume of Forest Trees
Calculation and Visualization of the Impact Effect Size Measure
Quantification of Population-Level Impact of Vaccination
Mechanical Loading Prediction Through Accelerometer Data
Calculate Impermanent Loss in Automated Market Maker (AMM)
Liquidity Pools
Imprecise Imputation for Statistical Matching
Array Operations for Arrays of Mismatching Sizes
Convert Between Bookmaker Odds and Probabilities
Analyzing Data Through of Percentage of Importance Indice and
Its Derivations
Download and Manage Open Data from INEGI
Calculate Birth Year-Specific Probabilities of Immune Imprinting
to Influenza
Improved Shrinkage Estimations for Multiple Linear Regression
Imputation of Financial Time Series with Missing Values and/or
Outliers
Ease the Implementation of Imputation Methods
A Collection of Methods for Left-Censored Missing Data
Imputation
Longitudinal Imputation of Categorical Variables via a Joint
Transition Model
Impute Missing Values in a Predictive Context
Imputation Methods for Multivariate Multinomial Data
A General Multivariate Imputation Framework
Impute Missing Rare Earth Element Data in Zircon
Robust Multiple Imputation with Generalized Additive Models for
Location Scale and Shape
Test Bench for the Comparison of Imputation Methods
Multi-Reader, Multi-Case Analysis Methods (ROC, Agreement, and
Other Metrics)
Immune Cell Gene Signatures for Profiling the Microenvironment
of Solid Tumours
Information Matrix Test for Generalized Partial Credit Models
Estimate Orientation of an Inertial Measurement Unit
Model Comparison via the 'InterModel Vigorish' ('IMV')
Volume Prediction of Trees Using Linear and Nonlinear Allometric
Equations
Initialization Algorithms for Partitioning Cluster Analysis
Analysing Inbreeding Based on Genetic Markers
Pipe-Friendly Vector Replacement with Case Statements
Incremental Calculation of Dynamic Time Warping
Incremental Graphlet Counting for Network Optimisation
Compute, Handle, Plot and Model Incidence of Dated Events
Compute, Handle and Plot Incidence of Dated Events
Estimate Incidence and Prevalence using the OMOP Common Data
Model
Implements Empirical Bayes Incidence Curves
Generates Incidence Matrices and Bipartite Graphs
Comparison of Means for the Incomplete Paired Data
Parametric Time-to-Event Analysis with Variable Incubation
Phases
Inductive Node-Splitting Cross-Validation for Community
Detection
A GUI for Dual and Bulk RNA-Sequencing Analysis
Insertion Deletion Analysis While Accounting for Possible
Missing Data
Estimates Weights for Confounding Control for Continuous-Valued
Exposures
Nonparametric Independence Tests Based on Entropy Estimation
Constructing and Analyzing Complex Selection Indices
Tests of Independence Between Innovations of Generalized Error
Models
Influence Diagnostics in Statistical Models
Access Indian Data via Public APIs and Curated Datasets
Composite 'Indicator' Construction and Imputation Data
Relationship Between Species and Groups of Sites
Elicitation of Independent Conditional Means Priors for
Generalised Linear Models
Tools for Football Player Scouting in Indonesia
Access Indonesian Data via Public APIs and Curated Datasets
Tests of Independence and Analysis of Dependence Between Point
Processes in Time
Data, Functions and Support Materials from the Book "industRial
Data Science"
Obtaining Data Published by the National Statistics Institute
Access to Spanish Household Income Distribution Atlas Data
Integrate INEGI’s (Mexican Stats Office) API with R
Measuring Inequality, Concentration, and Poverty
Two-Dimensional Decomposition of the Theil Index and the Squared
Coefficient of Variation
Inequality Measurement, Decomposition, and Poverty Analysis
Performing Inference on Networks with Regularization
Interpolation and Extrapolation for Species Diversity
Interpolation and Extrapolation for Three Dimensions of
Biodiversity
Four-Step Biodiversity Analysis Based on 'iNEXT'
Interpolation and Extrapolation with Beta Diversity for Three
Dimensions of Biodiversity
Access Infectious and Epidemiological Data via 'disease.sh API'
Inferring Cell-Specific Gene Regulatory Network
Inference About the Standardized Mortality Ratio when Evaluating
the Effect of a Screening Program on Survival
Methods for Causal Inference with Interference
Estimate and Account for Tumor Purity in Cancer Methylation Data
Analysis
Inflation Adjustment for Historical Currency Values
Inflation Decomposition, Core Measures, and Trend Estimation
Melt Curve Fitting and Melt Shift Analysis
Detecting Influential Subjects in Longitudinal Data
Tools for Detecting Influential Data in Mixed Effects Models
Case Influence in Structural Equation Models
Identify Influential Observations in Binary Classification
Adaptive Influence-Based Borrowing for Hybrid Control Trials
Software Tools to Quantify Structural Importance of Nodes in a
Network
Identification and Classification of the Most Influential Nodes
Data Exploration with Information Theory (Weight-of-Evidence and
Information Value)
Multiple Imputation for Informative Censoring
Sensitivity Analysis Informed by a Test for Bias
Computing a New Informative Distribution Set of Asset Returns
Information Matrix Test for Regression Models
Information-Theoretic Measures for Revealing Variable
Interactions
Effects and Importances of Model Ingredients
Translate ICD-9 into Injury Severity Score
A Toolkit for Sports Injury and Illness Data Analysis
Download and Analyze Spatial Development Data from 'INKAR'
Bayesian Latent Gaussian Modelling using INLA and Extensions
Multivariate Joint Modeling for Longitudinal and Time-to-Event
Outcomes with 'INLA'
Missing Data and Measurement Error Modelling in INLA
Spatial and Spatio-Temporal Models using 'INLA'
Approximate Bayesian Latent Variable Analysis
Color Schemes for the USGS Idaho National Laboratory Project
Office
Functions to Inline C, C++, Fortran Function Calls from R
Convert Inline Comments to Documentation
Infix Operators for Detection, Subsetting and Replacement
Inattention Detection Pipeline for Psychophysical Tasks
Analyse Text Documents Using Ecological Tools
Statistical Inference for Persistence Homology Data
Quality Control of Climatological Daily Time Series
Dissipation Kinetics Analysis, Half Life Period, Rate Constant,
Plots
Tools to Easily Download Data from INSEE BDM Database
Inset Plots for Spatial Data Visualization
Easy Access to Model Information for Various Model Objects
Probabilistic Verbal Autopsy Coding with 'InSilicoVA' Algorithm
High-Dimensional Changepoint Estimation via Sparse Projection
Validation of Arguments and Objects in User-Defined Functions
Access to Instagram Ads via the 'Windsor.ai' API
Using R to Install Stuff on Windows OS (Such As: R, 'Rtools',
'RStudio', 'Git', and More!)
Pre-Compiled 'CmdStan' Models in R Packages
A Collection of Insurance Datasets Useful in Risk Classification
in Non-life Insurance
Plotting Two- and Three-Way Interactions
Interactive Add-on Functionality for 'intamap'
Semiparametric Competing Risks Regression under Interval
Censoring
Integrating Multiple Modalities of High Throughput Assays Using
Item Response Theory
An Implementation of Interaction Graphs of Aleks Jakulin
Joint Modeling of the Gene-Expression and Bioassay Data, Taking
Care of the Effect Due to a Fingerprint Feature
Tests Checking for Implausible Values in Clinical Trials Data
Interval Estimation by Likelihood Method
A Group of Fun Datasets of Various Sizes and Differing Levels of
Quality
Intensity Analysis of Spatial Point Patterns on Complex Networks
Numerical Solution of Integral Equations
Power Analyses for Interaction Effects in Cross-Sectional
Regressions
Calculate Estimates in Models with Interaction
Comprehensive, User-Friendly Toolkit for Probing Interactions
Calculates Critical Test Statistics to Control False Discovery
Rates in Marginal Effects Plots
Compute Chi-Square Measures with Corrections
Multiple Correspondence Analysis Based on Interpretive
Coordinates
Interaction Analysis of Repeated Measure Data
GUI to Analyse qPCR Results after PMA Treatment or not
Define and Enforce Contracts for Dataframes as Function
Parameters
Estimation, Diagnostics and Visualization of Conditional
Marginal Effects
Coercion Routines for Network Data Objects
Scheduling Interim Analyses in Clinical Trials
App for Scheduling Interim Analyses in Clinical Trials
Converts Tabular Data to Interleaved Vectors
Importing Interlinearized Corpora and Dictionaries as Produced
by Descriptive Linguistics Software
Time Series Intervention Model Using Non-Linear Function
Plot the Effects of Variables in Interaction Terms
A Comprehensive Toolkit for Fast and Efficient Spatial
Interpolation
Fit Interpretable Machine Learning Models
Estimate the Confidence Interval and Interpret Step by Step
Interpreting High Resolution Mass Spectra
Binary Classifier and Regression Model Interpretation Functions
Flexible Tools for Estimating Interactions
Simulation of Inter-Related Genomic Datasets
Weighted Logrank Tests and NPMLE for Interval Censored Data
Time-Weighted Averaging for Interval Data
Analyzing Interval Data in Psychometrics
Tools to Deal with Interval-Valued Responses in Questionnaires
Tools for Working with Points and Intervals
Hypothesis Testing Using the Overlapping Interval Estimates
Tools and Statistical Procedures in Plant Science
A Numerical Implementation of Interval-Valued Kriging
Mediation Analysis using Interventional Effects
Integrative Clustering of Multiple Genomic Dataset
Modeling and Forecasting Financial Intraday Signals
Quantify and Control Reproducibility in High-Throughput
Experiments
An R Package for Factor Model Asset Pricing
Sample Size Planning Based on Intrinsic Kappa Value
Analysis of Time-Ordered Event Data with Missed Observations
Reproducible Integrated Species Distribution Models Across
Norway using 'INLA'
Interval and Enum-Type Representation of Vectors
Analyse Biological Invasion Costs with the 'InvaCost' Database
Inventory Analytics, Pricing and Markdowns
Reverse Engineers Regular Expression Patterns for R Objects
Obtains the Log Likelihood for an Inverse Gamma Stochastic
Volatility Model
Threshold Regression that Fits the (Randomized Drift) Inverse
Gaussian Distribution to Survival Data
In Vitro Toxicokinetic Data Processed with the 'invitroTKstats'
Pipeline
In Vitro Toxicokinetic Data Processing and Analysis Pipeline
Fits Toxicokinetic Models to In Vivo PK Data Sets
Inverse Stable Prior for Widely-Used Exponential Models
Tools for Exploring Multiple Response Data
Graphical Tools for Exploring Data with 'iNZight'
Tools for Exploring Regression Models with 'iNZight'
A Unified Framework for Input-Output Operations in R
Iterated Ordinary Least Squares Regression
Calling Copy Number Alterations in Amplicon Sequencing Data
Network Analysis for Input-Output Tables
Reproducible Input–Output Economics Analysis, Economic and
Environmental Impact Assessment with Empirical Data
Iota Inter Coder Reliability for Content Analysis
Batch IP Data Retrieval and Storage Using 'IP2Location.io'
Lookup Geolocation and Proxy Information using 'IP2Location.io'
API
Lookup 'WHOIS' Information for a Particular Domain
Data Analysis for IP Addresses and Networks
Iterative Pruning Population Admixture Inference Framework
Client for the 'ipbase.com' IP Geolocation API
Tools for Message Passing Between Processes
Kendall's Tau Partial Corr. for Survival Trait and Biomarkers
Map Digitized Survival Curves Back to Individual Patient Data
Spatial Interpolation by Inverse Path Distance Weighting
Add Ipea Editorial Standards to 'ggplot2' Graphics
Data from the Integrated Post-Secondary Education Data System
Transforms Institutional Data into Text Files for IPEDS
Automated Import/Upload
Fast Implementation of the Iterative Proportional Fitting
Procedure in C
List Balancing for Reweighting and Population Synthesis
Client for the 'IPGeolocation.io IP Location API'
Install R Packages or Download File from GitHub via the Proxy
Site
Identification of Parental Lines via Genomic Prediction
Client for the 'iplookupapi.com' IP Lookup API
Functions and Data for the Book 'Integrated Population Models'
Intervention in Prediction Measure for Random Forests
Individual Growth Curve Parameter Calculation using Polynomial
Functions
Intelligent Predicting Response to Cancer Immunotherapy Through
Systematic Modeling
Individual Polygenic Risk Score Uncertainty Estimation
Interfaces to Phylogenetic Software in R
Spatially Explicit Capture-Recapture by Inverse Prediction
Intuitionistic, Pythagorean, and Spherical Fuzzy Similarity
Measure
Introduction to Probability, Statistics and R for Data-Based
Sciences
An R Interface for Downloading, Reading, and Handling IPUMS Data
Inverse Probability Weighted Cox Model with Corrected Sandwich
Variance
Inverse Probability Weighted Estimation of Average Treatment
Effect with Misclassified Binary Outcome
Protein Quantification in Mass Spectrometry-Based Proteomics
Functions to Handle and Preprocess Infrared Spectra
Iterated Racing for Automatic Algorithm Configuration
Plots for Visualizing the Data Produced by the 'irace' Package
Iteratively Reweighted Boosting for Robust Analysis
Correlation Coefficients for Information Retrieval
Regression Methods for Interval-Valued Variables
Collection of Practical Institutional Research Examples and
Tutorials
Tools for Managing Imaging FlowCytobot (IFCB) Data
A Dynamic Bipartite Latent Space Model to Analyse Irish
Companies' Boards from 2003 to 2013
Classes and Methods for Seismic Data Analysis
Native R Kernel for the 'Jupyter Notebook'
Fast Truncated Singular Value Decomposition and Principal
Components Analysis for Large Dense and Sparse Matrices
Generalised Linear Models via Iteratively Reweighted Least
Squares
Improved Random Number Generator Seeding
Access to the Great Numbers of Brazilian Individual Income Tax
(IRPF)
Various Coefficients of Interrater Reliability and Agreement
Computing False Positive Rate from Inter-Rater Reliability
Computing the Extent of Agreement among Raters with
Chance-Corrected Agreement Coefficient (CAC)
Analysis of Longitudinal Data with Irregular Observation Times
Intraclass Correlations for Quantifying Inter-Rater Reliability
Coefficients of Interrater Reliability – Generalized for
Randomly Incomplete Datasets
Item Response Theory and Computerized Adaptive Testing Functions
Items Response Theory Analysis with Steps and Interpretation
Family of Bayesian EMM Algorithm for Item Response Models
Parameter Estimation of Item Response Theory with Estimation of
Latent Distribution
Item Response Theory Analysis with a Graphic User Interface
Theory-Driven Item Response Theory (IRT) Models
A Collection of Functions Related to Item Response Theory (IRT)
Power Analysis for IRT Models Using the Wald, LR, Score, and
Gradient Statistics
Unidimensional Item Response Theory Modeling
Estimation of Tree-Based Item Response Models
Monte Carlo Simulation-Based Sample-Size Planning for Item
Response Theory
Introduction to Sports Analytics using R (ISAR) Data
Overflow Data for Quantitative Peace Science Research
Implementation for the ISA Abstract Model
Companion to the Book "Investigating Statistical Concepts,
Applications, and Methods"
Converts ISCO-08 to Job Prestige Scores, ISCO-88 and Job Name
Datasets for Introduction to Statistical Data Analysis for the
Life Sciences
Parse 'NOAA' Integrated Surface Data Files
Ion Selective Electrodes Analysis Methods
Integrative Dimension Reduction Analysis for Multi-Source Data
Fitting Ising Models Using the ELasso Method
Landscape Construction and Simulation for Ising Networks
Sampling Methods and Distribution Functions for the Ising Model
Stochastic Island Biogeography Theory Made Easy
Reference Data and Helpers for Small Island States and
Territories
Data for an Introduction to Statistical Learning with
Applications in R
Introduction to Statistical Learning, Second Edition
An Introduction to Statistical Modeling of Extreme Values
Calculating Socio Material Territorial Index
Interpretive Structural Modelling Analysis Tools
Index of Local Sensitivity to Nonignorability
Check if an 'externalptr' is a Null Pointer
Functions to Perform Isotonic Regression
Calorific Values and Properties of Natural Gas per ISO 6976:2016
Generate Isolines and Isobands from Regularly Spaced Elevation
Grids
Isotope Origin Clustering and Assignment Tools
Voxel Data Visualization with Isometric Cubes
Calculating Density-Independent Niche Breadth Indices from
Abundance Data
Statistical Toolbox for Radiometric Geochronology
Isoscape Computation and Inference of Spatial Origins using
Mixed Models
Isotonic Regression on Survival Analysis
Active Set and Generalized PAVA for Isotone Optimization
Penalized Isotonic Regression in one and two dimensions
Discovery, Retrieval, and Analysis of Water Isotope Data
Week of the year and weekday according to ISO 8601
Access Data from the Public Security Institute of the State of
Rio De Janeiro
Trial Design in Respiratory Disease Based on the Win Probability
The Iterated Score Regression-Based Estimation
Tools and Data for the International Soil Radiocarbon Database
Obtaining Open Data from Instituto Canario De Estadistica
(ISTAC) API
Interface to the Italian National Institute of Statistics
('ISTAT') API
A Graphical Interface to Perform STOCSY Analyses on NMR Data
Information-Based Stability and Synchrony Measures
The Italian Survey on Household and Wealth, 2008 and 2010
Integral Transformation Methods for SDR in Regression
Automated Item Removal Strategies for Exploratory Factor
Analysis
Iterative Hard Thresholding Extensions to Cyclops
Print Loop Iterations at Exponentially Disparate Intervals
Approximate Probability Densities by Iterated Laplace
Approximations
Efficient Iterator for Permutations and Combinations
itertools2: Functions creating iterators for efficient looping
Information-Theoretic Measures for Spatial Association
Analysis of the International Trade Network
Helper Functions for 'Interactive Tree Of Life'
Methods and Examples from Introduction to the Theory of
Observational Studies
The Interpolate, Truncate, Project (ITP) Root-Finding Algorithm
Improved Trimmed Weighted Hochberg Procedures and Sample Size
Optimization
Running Interrupted Time Series Analysis
Interpreting Time Series and Autocorrelated Data Using GAMMs
Isolation Forest-Based Presence-Only Species Distribution
Modeling
Time Series Analysis Using the Innovations Algorithm
Sensitivity Analysis Tools for Instrumental Variable Estimates
Tests for Instrumental Variable Validity
A Robust Integrated Variance Correlation
Profiling Compliers and Non-Compliers for Instrumental Variable
Analysis
Estimation and Diagnostic Tools for Instrumental Variables
Designs
Double Machine Learning with Instrumental Variables and
Heterogeneity
Ensures Mutually Consistent Beliefs When Using IVs
General to Specific Modeling and Indicator Saturation in 2SLS
Models
Statistical Inference and Sensitivity Analysis for Instrumental
Variables Model
Instrumental Variables: Extrapolation by Marginal Treatment
Effects
Nicely Formatted Contingency Tables and Frequency Tables
Instrumental-Variables Regression by '2SLS', '2SM', or '2SMM',
with Diagnostics
Produces an IVY Plot (Similar to Dot Plot) with/without
Frequencies
Irrigation Water Quality Assessment and Visualizations
Improved Methods for Causal Inference and Missing Data Problems
Framework for Tick Population and Infection Modeling
Interactive 3D Surface Plots for Multi-Factor Interaction
Visualization
R Wrapper for Izmir Municipality Open Data Portal
Simulation-Based Maximum Likelihood Parameter Estimation
Possible Adverse Events/Reactions from the
Vaccinations/Experimental Gene Therapies
Testing Similarity Between Binary Datasets using
Jaccard/Tanimoto Coefficients
A Swift, Versatile Phylogenomic and High-Throughput Sequencing
Simulator
Delete-d Jackknife for Point and Interval Estimation
Correcting Nonparametric Frontier Measurements for Outliers
Statistical Inference for Unsupervised Learning
Jacobi Theta Functions and Related Functions
Jaccard Index for Population Structure Identification
Estimation of Jacquard's Genetic Identity Coefficients
Blind Source Separation Methods Based on Joint Diagonalization
and Some BSS Performance Criteria
Supporting Files and Functions for the Book Bayesian Modelling
with 'JAGS'
Extracting and Visualizing Output from 'jagsUI'
A Wrapper Around 'rjags' to Streamline 'JAGS' Analyses
Convert Between Jalaali (Persian or Solar Hijri) and Gregorian
Calendar Dates
Just Another Latent Space Network Clustering Algorithm
Simple Tools for Examining and Cleaning Dirty Data
Optimized Recommending System Based on 'tensorflow'
Asymmetric Smoothed-Association Matrices via GAM Fits
Access Japanese Data via Public APIs and Curated Datasets
Just a Rather Bayesian Evidence Synthesis
A Metadata and Text Extraction and Manipulation Tool Set
Javanese Teak Above Ground Biomass Estimation
Gradient-Free Optimization Algorithm for Single and
Multi-Objective Problems
An R Interface to the JBrowse 2 Genome Browser
Interconversion Between the Japanese Calendar System and the
Western Calendar
Extended Classification of Weather Types
Colors Palettes for R and 'ggplot2', Additional Themes for
'ggplot2'
Journal Citation Reports ('JCR') Impact Factor by 'Clarivate'
'Analytics'
Risk Calculator for Cardiovascular Disease in Japan
Interface Between the 'JDemetra+' Cruncher and R, and Quality
Report Generator
A Wrapper for the Node.js 'Jdenticon' Library
Monte Carlo Option Pricing Algorithms for Jump Diffusion Models
with Correlational Companies
R Markdown Templates for Journal of Data Science
Visualize Spatiotemporal Tumor Evolution with Jellyfish Plots
Fast Extrapolation of Time Features using K-Nearest Neighbors
Graphical Models Estimation from Multiple Sources
Tools for Analyzing Time Series Data of Just Finance and
Econometrics
Rock Mass Structural Analysis from 3D Mesh of Point Cloud
Package of the German Book "Statistik mit R und RStudio" by
Joerg grosse Schlarmann
Approximate Inclusion Probabilities for Survey Sampling
Cluster-Based Permutation Analysis for Densely Sampled Time Data
Zero-Copy Julia to R Array Bridge via ALTREP
Joint Modeling of Longitudinal and Survival Data
Download Weather Data from Japan Meteorological Agency Website
Read from/Write to Disk Matrices with any Data Type in a Binary
Format
Joint Modeling of Longitudinal and Time-to-Event Data under a
Bayesian Approach
Extended Joint Models for Longitudinal and Time-to-Event Data
Joint Model for Longitudinal and Multiple Time to Events Data
Joint Longitudinal and Survival Model for Big Data
Joint Mean-Covariance Models using 'Armadillo' and S4
Fitting Joint Mean and Dispersion Effects Models
Joint Modeling of Longitudinal and Survival Data - Power
Calculation
Joint Model of Heterogeneous Repeated Measures and Survival Data
Time Series Analysis Toolkit Based on Symbolic Aggregate
Discretization, i.e. SAX
Semi-Parametric Association Surfaces for Joint
Longitudinal-Survival Models
Permutation Tests for Nonparametric Statistics
Connect to the 'jamovi' Statistical Spreadsheet
Visualize Outputs from the 'Johnson-Neyman' Technique
Run Code as an RStudio Job - Free Your Console
Modelling and Simulating Judgments of Frequency
Joint Modelling of Repeated Measurements and Time-to-Event Data
Joint Modelling of Multivariate Longitudinal Data and
Time-to-Event Outcomes
Penalised Multivariate Regression ('Multi-Target Learning')
Exploratory Analysis of Relationships Between Variables
Tidy Tools for Joinpoint Regression Models
Joint Frailty-Copula Models for Tumour Progression and Death in
Meta-Analysis
Joint Analysis and Imputation of Incomplete Data
A Joint Calibration of Totals and Quantiles
Joint Inference for Competing Risks Data Using Multiple
Endpoints
Joint Approximate Diagonalization of a Set of Square Matrices
Multivariate Testing Through Joint Resampling-Based Tests
A Parametric Model for Estimating the Mean Number of Events
Joint Mean and Covariance Estimation for Matrix-Variate Data
Joint N-Mixture Models for Site-Associated Species
Risk Estimation Using the Joint Probability Method
Joint Segmentation of Multivariate (Copy Number) Signals
Prioritize Variables with Joint Variable Importance Plot in
Observational Study Design
Perform Joins or Minus Queries on 'Excel' Files
Probability Distributions and Parameter Estimation
Small Area Population Estimation by Demographics
Multilevel Joint Modelling Multiple Imputation
A Suite of Routines for Working with Jordan Algebras
Unit-Level and Area-Level Small Area Estimation
Add Josa Based on Previous Letter in Korean
JavaScript Object Signing and Encryption
Journal Abbreviations for BibTeX Documents
Formatting Tools for Scientific Journal Writing
Tool for Diagnosis of Tables Joins and Complementary Join
Features
Read and Convert Japanese Municipality Codes
Covariance and Inverse Covariance Matrix Estimation Using Joint
Penalty
Functions for the Grid Square Codes in Japan
Acquiring and Processing Data from Japan Institute for Health
Security
Tools for Easy Use of 'e-Stat', 'RESAS' API, Etc
Joinpoint Model for Relative and Cause-Specific Survival
Obtain 'jQuery' as an HTML Dependency Object
Exchange Commands Between R and 'JavaScript'
Jack-Knife Support for Evolutionary Distinctiveness Indices I
and W
Multimodal Single-Cell Omics Dimensionality Reduction
Item Response Theory Modeling and Scoring for Judgment Data
Basic Finance; NPV/IRR/Annuities/Bond-Pricing; Black Scholes
A 'RStudio' Addin to Send 'JavaScript' Code to the 'V8' Console
Calculates the j-Score Between Two Clustering Assignments
Estimating the Age using Auricular Surface by DNE
Jensen-Shannon Divergence Estimation, Confidence Intervals, and
Distribution Plots
Semiparametric Joint Modeling of Survival and Longitudinal Data
Mediation Analysis Using Joint Significance
'RStudio' Addins and 'Shiny' Modules for Medical Research
Parse Parameters Inside a Docker Container
A 'Base64' Encode/Decode Package with Support for JSON
Output/Input and UTF-8
Convert Between 'R' Objects and Javascript Object Notation
(JSON)
A Simple and Robust JSON Parser and Generator for R
Joint Sparse Optimization via Proximal Gradient Method for Cell
Fate Conversion
Create Tables from Different Types of Regression
Retrieve Information Published on J-STAGE
Create Interactive Trees with the 'jQuery' 'jsTree' Plugin
A Wrapper of the JavaScript Library 'jsTree'
Estimate Parameters of the Best-Fitting JohnsonSU Distribution
Analysis and Presentation of Social Scientific Data
Forecasting Long-Term Growth of the U.S. Stock Market and
Business Cycles
'juice' + 'markdown': Convert 'R Markdown' into 'HTML' with
Inline Styles
Automated and Manual Extraction of Numerical Data from
Scientific Images
Inline CSS Properties into HTML Tags Using 'juice'
Seamless Integration Between R and 'Julia'
A Functionally Oriented Interface for Integrating 'Julia' with R
Translate R Regression Model Formulae to 'Julia' Syntax
Replicability Analysis of High-Throughput Experiments
Create Common Tables and Listings Used in Clinical Trials
The Breakdown of Genomic Ancestry Blocks in Hybrid Lineages
Very Simple Function to Install Packages without Attaching
Human and Machine-Readable Justifications and Justified
Decisions Based on 'YAML'
Justifying Alpha Levels for Hypothesis Tests
Principal Component Analysis (PCA) and Whitening
Student Achievement Data Files for TIMSS 2023 Grade 4
Student Process Data Files for TIMSS 2023 Grade 4
School Context Data Files for TIMSS 2023 Grade 4
Construct Complex Table with 'kable' and Pipe Syntax
Kernel Adaptive Density Estimation and Regression
Programmatic Access to the API for Japanese Diet Proceedings
Analysis of Chronological Patterns from Archaeological Count
Data
Kernel Approaches for Nonlinear Genetic Association Regression
A Statistical Framework for the Analysis of Japanese Kanji
Characters
Quasi Analysis of Variance for K-Functions
Encoding of Sequences Based on Frequency Matrix Chaos Game
Representation
Test the Homogeneity of Kappa Statistics
Agreement of Nominal Scale Raters (with a Gold Standard)
An R-Shiny Application for Calculating Cohen's and Fleiss' Kappa
Non-Additive Measure and Integral Manipulation Functions
Sample Size Estimation Functions for Studies of Interobserver
Agreement
Make Symmetric and Asymmetric ARDL Estimations
Real-Time PCR Data Sets by Karlen et al. (2007)
An Interface for Microclimate Time Series Analysis
DNA Copy Number Analysis for Genome-Wide Tapestri Panels
Rendering Math to HTML, 'MathML', or R-Documentation Format
Kaya Identity Data for Nations and Regions
Khattree-Bahuguna's Univariate and Multivariate Skewness
Conditional Expectation Function Estimation with
K-Conditional-Means
Smooth Test for Equality of Copulas and Clustering Multivariate
Kernel Change Point Detection on the Running Statistics
Kernel Smoothing for Bivariate Copula Densities
Kernel Density Estimation with a Markov Chain Monte Carlo Sample
Kernel Density Estimation with Parametric Starts and Asymmetric
Kernels
Multivariate Kernel Density Estimation with Vine Copulas
Bayesian Analysis of Dynamic Generalized Linear Models
Kernel Distance Metric Learning for Mixed-Type Data
Kinship Decouple and Phenotype Selection (KDPS)
Kernel Estimator and Bandwidth Selection for Density and Its
Derivatives
Arrays with Better Control over Dimension Dropping
Collect, Assemble and Model Air Pollution, Weather and Health
Data
Calculate Solutions to the Kelvin Differential Equation using
Bessel Functions
Kendall Rank Correlation and Mann-Kendall Trend Test
Efficient Implementation of Kendall's Correlation Coefficient
Computation
Simulate and Visualize Kendall Random Walks and Related
Distributions
Kernel-Embedding-of-Probability Test for Elliptical Distribution
A Bridge Between 'keras' and 'tidymodels'
New Kernel-Based Test for Differential Association Analysis
Nonparametric Kernel Estimation of Distribution Function
Distance Weighted Discrimination (DWD) and Kernel Methods
Smoothed Bootstrap and Random Generation from Kernel Densities
Kernel Factory: An Ensemble of Kernel Machines
Kernel Density Estimation for Heaped and Rounded Data
Kernel Smoothing Tools for Philology and Historical Dialectology
Kernel Estimation of Hazard Function in Survival Analysis
Estimating Count Data Distributions with Discrete Optimal
Symmetric Kernel
Kernel Machine Score Test for Semi-Competing Risks
Functions for Kernel Smoothing Supporting Wand & Jones (1995)
Adaptive Kernel Estimators for Point Process Intensities on
Linear Networks
Kernel Functions and Tools for Machine Learning Applications
Bayesian Designs for Early Phase Clinical Trials
Keyboard and Mouse Input Simulation for Windows OS
A Model for Semi-Supervised Keyword Extraction from Word
Embedding Models
Explicit Key Assumptions for Flat-File Data
Lightweight List Extensions that Enforce Unique Keys
Keyword Analysis Using Permutation Tests
Access the System Credential Store from R
Decrypt Passwords from Gnome Keyring, Windows Data Protection
API and macOS Keychain
K-Fold Cross Validation for Factor Analysis
Kalman Filter and Smoother for Exponential Family State Space
Models
Integrated Code Chunk Anchoring and Referencing for R Markdown
Documents
Kalman Filter for Impulse Noised Outliers
Kendall Functional Principal Component Analysis
Kidney Failure Risk Equation (KFRE) Tools
A Tool for Calculating Stoichiometric Equilibrium Constants (Ks)
for Seawater
Kernel Based Gradient Matching for Parameter Inference in
Ordinary Differential Equations
Knowledge Graphs Constructions and Visualizations
Bayesian Sparse Polynomial Chaos Expansion
Methods for Calculating 'KHQ' Scores and 'KHQ5D' Utility Index
Scores
Colour Schemes for Scientific Data Visualization
Kidney-Related Functions for Clinical and Epidemiological
Research
Download, Cache, and Connect to KidSIDES
Simulate and Estimate Close-Kin Dispersal Kernels
Higher-Level Interface of 'torch' Package to Auto-Train Neural
Networks
'shiny' Applications for the 'tesselle' Packages
Relationship-Informed Pedigree and Variant Scoring
Inference About Relationships from DNA Mixtures
Panel Evaluation in Forensic Kinship Analysis
Example Data from the Multi-Modal MRI 'Reproducibility' Resource
Example Functional Imaging Data from the Multi-Modal MRI
'Reproducibility' Resource
Example T1 Structural Data from the Multi-Modal MRI
'Reproducibility' Resource
Korea Investment & Securities (KIS) Open Trading API
a Keep It Simple Species Migration Model
Data Manipulation Functions Implemented in C
Spectral Response of Water Wells to Harmonic Strain and Pressure
Signals
Visualize Contingency Tables Using Kite-Square Plots
A Wrapper for Querying KISTERS 'WISKI' Databases via the 'KiWIS'
API
Kernel Knockoffs Selection for Nonparametric Additive Models
Sample-Based Estimation of Kullback-Leibler Divergence
Kullback-Leibler Divergence and Other Tools to Analyze
Frequencies
Confidence Intervals for the Kaplan-Meier Estimator
k-Means Like Blockmodeling of One-Mode and Linked Networks
Kaplan-Meier Estimator with Constraints for Right Censored Data
-- a Recursive Computational Algorithm
Kernel Measure of Multi-Sample Dissimilarity
Fast K-Mer Counting and Clustering for Biological Sequence
Analysis
Multi-Purpose and Flexible k-Meric Enrichment Analysis Software
Kaplan-Meier Multiple Imputation for the Analysis of Cumulative
Incidence Functions in the Competing Risks Setting
Preserving Attribute Values: Converting KML to Shapefile
K-Means with Simultaneous Outlier Detection
Datasets from Klein and Moeschberger (1997), Survival Analysis
Khmaladze Martingale Transformation Goodness-of-Fit Test
Generate Feasible Samples of a Knapsack Problem
Analysis of Korean National Forest Inventory Database
A General-Purpose Package for Dynamic Report Generation in R
Data Language Engine for 'knitr' / 'rmarkdown'
Generates a Spreadsheet Report from an 'rmarkdown' File
An Accurate kNN Implementation with Multiple Distance Measures
k-Nearest Neighbor Mutual Information Estimator
Time Series Prediction using K-Nearest Neighbors Algorithm
(Parallel)
Interactive Document for Working with KNN Analysis
k Nearest Neighbors with Grid Search Variable Selection
K Nearest Neighbor Forecasting with a Tailored Similarity Metric
The Knockoff Filter for Controlled Variable Selection
Hybrid Analysis of Population and Trio Data with Knockoff
Statistics for FDR Control
GWAS with Trio and Duo Data using Knockoff Statistics for FDR
Control
Discriminating Well Surveyed Spatial Units from Exhaustive
Biodiversity Databases
Knowledge Discovery by Accuracy Maximization
Get Data from the 'KOF Datenservice' API
Test the Kronecker Product Structure in Tensor Factor Models
A Genetic Algorithm for Fixed-Size Subset Selection
Functional Summary and Meta-Analysis of Gene Expression Data
Supervised and Unsupervised Self-Organising Maps
Pick and Plot Key Opinion Leaders from a Network Given
Constraints
Event Classification, Visualization and Analysis of Eye Tracking
Data
Simply Beautiful PDF Letters from Markdown
Quantify the Robustness of Causal Inferences
KONP Tests: Powerful K-Sample Tests for Right-Censored Data
Matching Address Data to Reference Index
Text Analysis with Emphasis on POS Tagging, Readability, and
Lexical Diversity
Language Support for 'koRpus' Package: English
Variable Selection by Revisited Knockoffs Procedures
Korean Statistical Information Service (KOSIS)
Cubic Spline Fitting with Knot Selection
Variables Interpretability with Kernel PCA
Determination of K Using Peak Counts of Features for Clustering
KPI Widgets for Quarto Dashboards with Crosstalk
Method for Clustering Partially Observed Data
Comprehensive R Interface for Accessing Kraken Cryptocurrency
Exchange REST API
A Quantified Implementation of the Kraljic Matrix
Geospatial Kriging with Metropolis Sampling
Kriging-Based Inversion for Deterministic and Noisy Computer
Experiments
Measuring Agreement Using Krippendorff's Alpha Coefficient
Keen and Reliable Interface Subroutines for Bioinformatic
Analysis
Microbiome Oriented Circadian Rhythm Analysis Toolkit
Clock of Regimes for Regime-Switching Fragility Analysis
Retained Component Criterion for Principal Component Analysis
K-Sample Rank Tests and their Combinations
Computing P-Values of the One-Sample K-S Test and the Two-Sample
K-S and Kuiper Tests for (Dis)Continuous Null Distribution
Korea Standard Industrial Classification (KSIC)
Kernel Density Estimation for Random Symmetric Positive Definite
Matrices
Identify Kinase Substrate Relationships Using Dynamic Data
Unbiased Estimators for Cumulant Products and Faa Di Bruno's
Formula
Basic Functions in Knowledge Space Theory Using Matrix
Representation
Co-Tucker3 Analysis of Two Sequences of Matrices
Configurable Function for Solving Families of Nonlinear
Equations
'Tweedie' Compound Poisson Model in the Reproducing Kernel
Hilbert Space
Detailed Development of Ecological Niche Models
Computer Vision with Large Language Models
Read/Write Files in Key-Value-Hierarchy Format
Interface to the Dutch Chamber of Commerce (KvK) API
Calculate and Compare Multiple Definitions of Coefficient of
Determination
Robust Changepoint Detection for Functional and Multivariate
Data
Hierarchical Adaptive 'RT-QuIC' Classification for Complex
Matrices
Utility Functions for Statistical Analysis Report Generation and
Monte Carlo Studies
Kolmogorov-Zurbenko Spatial Smoothing and Applications
Sparse Generalized Linear Model with L0 Approximation for
Feature Selection
Smooth L0 Penalty Approximations for Gaussian Graphical Models
Fast Algorithms for Best Subset Selection
A Splicing Approach to the Inverse Problem of L0 Trend Filtering
Graph/Network Analysis Based on L1 Centrality
Identify Loading Vectors under Sparsity in Factor Models
An L1-Version of the Spectral Clustering
Exploring Friedman's Boosting Algorithm for Regularized Linear
Regression
Robust Structured Regression via the L2 Criterion
L2 Inference for Change Points in High-Dimensional Time Series
Automation and Standardization of Cleaning Clinical Laboratory
Data
Miscellaneous Scripts from the Data Science Laboratory (UCPH)
Ordination and Multivariate Analysis for Ecology
Relabelling MCMC Outputs of Mixture Models
Automate the Production of Custom Labels, Badges, Certificates,
and Other Documents
Label Data Frames, Variables, and Values
Laser Ablation Blast Through Endpoint Detection
Normalize Laboratory Measurements by Age and Sex
Identification, Tuning, Visualisation and Analysis of Labour
Market Areas
Simplex Optimization Algorithms for Laboratory and Manufacturing
Processes
Libreria Del Laboratorio Di Statistica Con R
Data Sets for the Book "Experimental Design for Laboratory
Biologists"
Calculation of Comorbidity and Frailty Scores
Lactation Curve Model Fitting for Dairy Animals
Gliding Box Lacunarity and Other Metrics for 2D Random Closed
Sets
Derive Leaf Angle Distribution (LAD) from Measured Leaf
Inclination Angles
Automated Tool for Vertical Fuel Continuity Analysis using
Airborne Laser Scanning Data
Estimation of Indicators on Social Exclusion and Poverty
Interface to the Lake Multi-Scaled Geospatial and Temporal
Database
Local Approximate Gaussian Process Regression
Converting NDVI to LAI of Field, Proximal and Satellite Data
Calculate Fetch and Wave Exposure for Lake Sampling Points
Tools for the Analysis of Ecosystem Metabolism
Fast Numerical Maximum Likelihood Estimation for Latent Markov
Models
Modeling Data with Functional Programming
Variational Seq2Seq Model with Lambda Transformer for Time
Series Analysis
Create a Runtime for Serving Containerised R Functions on 'AWS
Lambda'
Probabilistic Models to Analyze and Gaussianize Heavy-Tailed,
Skewed Data
Maximum Likelihood Estimation of Latent Variable Models
Statistical Inference via Lancaster Correlation
Analysing Landscape Composition and Structure at Multiple Scales
Landmark Estimation of Survival and Treatment Effect
Topographic Position Index-Based Landform Classification
Landmark Prediction with Multiple Short-Term Events
Landmark Prediction of a Survival Outcome
Radiometric and Topographic Correction of Satellite Imagery
Landscape Metrics for Categorical Map Patterns
Translates R Help Documentation using Large Language Models
Langevin Analysis in One and Two Dimensions
Data Sets and Functions with Analyzing Linguistic Data: A
Practical Introduction to Statistics
Automated Setup and Auto Run for R Language Server
Convenient Access to Los Angeles Open Data API Endpoints
Complete Environment for Bayesian Inference
Processing, Visualizing, and Labeling Americas Barometer Data
Lean Analytics and Robust Exploration Sidekick
Testing Large VARs for the Presence of Cointegration
Estimation of Lifetime Attributable Risk of Cancer from
Radiation Exposure
Least Angle Regression, Lasso and Forward Stagewise
Modelling Interactions in High-Dimensional Data with
Backtracking
Fast High-Dimensional Gibbs Samplers for Bayesian Lasso
Regression
Nonparametric P-Value Estimation for Predictors in Lasso
Sparsed Sliced Inverse Regression via Lasso
Latin American Data via 'RESTful' APIs and Curated Datasets
Evaluation of the Role of Control Variables in Structural
Equation Models
Draws Diagrams Useful for Checking Latent Scales
Inference on LATEs under Network Interference of Unknown Form
Converting Latent Variables into Likert Scale Responses
Bayesian Model Averaging for Univariate Link Latent Gaussian
Models
Fast Computation of Latent Correlations for Mixed Data
Latent Position and Cluster Models for Statistical Networks
Utilities for Scheduling Functions to Execute Later with Event
Loops
Functions to Calculate Common Laterality Statistics in
Primatology
Linear Approach to Threshold with Ergodic Rate for Reaction
Times
Diff TeX, 'rmarkdown' or 'quarto' Files Using the 'latexdiff'
Utility
R Functions for Readable LaTeX Mathematical Expressions
A Framework for Clustering Longitudinal Data
Density Estimation and Nonparametric Regression on Irregular
Regions
Extra Graphical Utilities Based on Lattice
Multi-Resolution Kriging Based on Markov Random Fields
Fit Structural Equation Models to Multiply Imputed Data
Helper Functions for Printing 'lavaan' Outputs
Convenience Functions for Package 'lavaan'
Graphical User Interface with Integrated 'Diagrammer' for
'Lavaan'
Path Diagrams for 'Lavaan' Models via 'DiagrammeR'
Tools for Model Specification in the Latent Variable Framework
Post-Estimation Utilities for 'lavaan' Fitted Models
Latent (Variable) Analysis with Bayesian Learning
Tools for Biostatistics, Public Policy, and Law
Loglikelihood Adjustment for Extreme Value Models
Tilt your Maps and Turn Them into 'ggplot' Plots
Progress Bar with Remaining Time Forecast Method
Delayed Read for 'GDAL' Vector Data Sources
Learn Computer and Data Science using Algorithmic Trading
Latent Budget Analysis for Compositional Data
Latent Binary Bayesian Neural Networks Using 'torch'
Literature-Based Discovery Tools for Biomedical Research
Limited Memory BFGS Minimizer with Bounds on Parameters with
optim() 'C' Interface
Log Binomial Regression Model in Exact Method
Implementation of Logistic Box-Cox Regression
The Length-Biased Power Garima Distribution
Log-Binomial Regression with Constrained Optimization
Latent Class Analysis (LCA) with Familial Dependence in Extended
Pedigrees
Advanced Analysis of Longitudinal Data Using the Concordance
Correlation Coefficient
Adaptive k-Nearest Neighbor Classifier Based on Local Curvature
Estimation
Data sets for package ``LMERConvenienceFunctions''
A Bayesian Multi-Dimensional Couple-Based Latent Risk Model
Extended Mixed Models Using Latent Classes and Latent Processes
Liquid Chromatography/Mass Spectrometry (LC/MS) Quality
Assessment
Simple Tools to Compute Landscape Connectivity Metrics
A General Framework for Latent Classify and Profile Analysis
Ordinal Outcomes: Generalized Linear Models with the Log Link
Bayesian Joint Latent Class and Regression Models
Univariate and Bivariate Latent Change Score Modelling
Collapsed Gibbs Sampling Methods for Topic Models
Linkage Disequilibrium of Ancestry (LDA) and LDA Score (LDAS)
Analysis of Data from Limiting Dilution Assay (LDA) with or
without Cellular Cooperation
Selection of Statistically Similar Research Groups
Prototype of Multiple Latent Dirichlet Allocation Runs
Oblique Classification Trees with Uncorrelated Linear
Discriminant Analysis Splits
Latent Dirichlet Allocation Coupled with Time Series Analyses
Interactive Visualization of Topic Models
Lan-DeMets Method for Group Sequential Boundaries
Linkage Disequilibrium Corrected by the Structure and the
Relatedness
Longitudinal Drift-Diffusion Mixed Models (LDDMM)
Hidden Markov Model for Financial Time-Series Based on Lambda
Distribution
Calculating Linkage Disequilibrium (LD) in Human Population
Groups of Interest
Testing Hypotheses About the Microbiome using the Linear
Decomposition Model
Estimate and Simulate from Location Dependent Marked Point
Processes
Linkage Disequilibrium Shrinkage Estimation for Polyploids
Medtronic Brain Sense Local Field Potencial Analysis
Learning Equations for Automated Function Discovery
Rapid Digital Image Analysis of Leaf Area
Provides Drill Down Functionality for 'leaflet' Choropleths
High-Performance 'WebGl' Rendering for Package 'leaflet'
Create Interactive Web Maps with the JavaScript 'Leaflet'
Library
Extra Functionality for 'leaflet' Package
Leaflet Map Plugin for Drawing and Editing
Include Tables, Images and Graphs in Leaflet Pop-Ups
Silhouette to Area Ratio of Tilted Surfaces
Data Leakage Detection Tools for Machine Learning
Localized Ensemble of Approximate Gaussian Processes
Latent Effect Adjustment After Primary Projection
Border and Area Estimation of Data Measured with Additive Error
Functions for Learning Bayesian Inference
Data and Functions to Accompany the Book "Learning R"
Elemental Descriptive and Inferential Statistics
OECD PISA Datasets from 2000-2022 in an Easy-to-Use Format
'R6'-Based Flexible Framework for Permutation Tests
Functions, Data Sets and Vignettes to Aid in Learning Principal
Components Analysis (PCA)
Population Genetic Simulations & Numerical Analysis
Datasets and Code Examples from P. J. Aphalo's "Learn R" Book
Learn Supervised Classification Methods Through Examples and
Code
Learning and Communicating Linear Mixed Models Without Data
Modelling Pathways and Movement Potential Within a Landscape
Leave-Out Variance Component Estimation for Two-Way Fixed
Effects Models
Decompose Life Expectancy by Age (and Cause)
Utilities for Importing Data from Plain Text Accounting Files
Laboratory of Teaching to Statistics and Mathematics
Historical and Ahistorical Population Projection Matrix Analysis
Interface to the Comparative Legislators Database
Latent Environmental & Genetic InTeraction (LEGIT) Model
Grab Longitudinal Employer-Household Dynamics (LEHD) Flat Files
R Implementation of Leiden Clustering Algorithm
Implements the Leiden Algorithm via an R Interface
R and C/C++ Wrappers to Run the Leiden find_partition() Function
Length-Based Multispecies Analysis by Numerical Simulation
Create Simple 'Shiny' Applications as Packages
Implements Parsimonious Finite Mixtures of Multivariate
Elliptical Leptokurtic-Normals
Less Code with More Comprehensive Results
Non-Smooth Regularization for Structural Equation Models
Vectorised Nested if-else Statements Similar to CASE WHEN in
'SQL'
Data Handling and Analysis in Macroecology
Find Related Items and Lexical Dimensions in a Lexicon
Plot Lexis Diagrams for Demographic Purposes
Extractive Summarization of Text with the LexRank Algorithm
Log Fold Change Distribution Tools for Working with Ratios of
Counts
Estimation of the Local False Discovery Rates by Type II Maximum
Likelihood Estimation
Estimating Local False Discovery Rates Using the Method of
Moments
Estimating Local False Discovery Rates Using Empirical Bayes
Methods
Generation and Analysis of 3-Level and 5-Level Factorial Block
Designs
Quality Control for Label-Free Proteomics Expression Data
Calculation of Low Flow Statistics for Daily Stream Flow Data
Locally Gaussian Distributions: Estimation and Methods
Simulation and Estimation of Log-GARCH Models
Implementation of Learning Gamma CUSUM (Cumulative Sum) Control
Charts
Collection of Tools for LGD Rating Model Development
Tests for Genetic Association/Gene-Environment Interaction in
Longitudinal Studies
Example Datasets for a Learning Guide to R
Set-Based Tests for Genetic Association in Longitudinal Studies
Lagrangian Multiplier Smoothing Splines for Smooth Function
Estimation
A Set of Methods for Longitudinal Data Objects
Fit Sex-Specific Life History Models with Missing
Classifications
Various Utilities for Library Science/Assessment and Cataloging
Linear Test Statistics for Permutation Inference
Open Source Geometry Engine ('GEOS') C API
'Imath' Computer Graphics Linear Algebra Static Library
Linear Predictive Models Based on the LIBLINEAR C/C++ Library
Static Library and Headers for 'OpenEXR' Image I/O
Libraries, Data Dictionaries, and a Data Step for R
Linearized Bregman Algorithms for Generalized Linear Models
Install, Update, Load Packages from CRAN, 'GitHub', and
'Bioconductor' in One Step
Library Snapshot for Packages and Dependencies in Use by Current
Session
The LIC Criterion for Optimal Subset Selection
Reads Raw Files from Li-COR Gas Analyzers
Forest Analysis with Airborne Laser Scanning (LiDAR) Data
Airborne LiDAR Data Manipulation and Visualization for Forestry
Applications
Real-Time PCR Data Sets by Lievens et al. (2012)
Financial and Actuarial Mathematics for Life Contingencies
Manage the Life Cycle of your Package Functions
Framework for Traditional Life Insurance Contracts
Modelling Traditional Life Insurance Contracts
Life and Fertility Tables Specially for Insects
Interactive 'shiny' Application for Constructing Life Tables
'shiny' Application for Life Table and Fertility Analysis
Wavelet Lifting Estimators of the Hurst Exponent for Regularly
and Irregularly Sampled Time Series
Containerize R Markdown Documents for Continuous Reproducibility
A Bootstrap Proportion Test for Brand Lift Testing
Process Data from Wearable Light Loggers and Optical Radiation
Dosimeters
From 'Rmarkdown' and 'Quarto' Files to Tibble and Back
A Curated Collection of Georeferenced and Spatial Datasets
Implementation of the 'Lights Out' Puzzle Game
Methods for Maximum Likelihood Estimation
Likelihood Contribution Models for Heterogeneous Observation
Types
Likelihood-Based Statistical Inference in the Fisherian
Tradition
Likelihood Analyses for Common Statistical Tests
Managing Results from Maximum Likelihood Estimation
Easy Analysis and Visualization of Likert Scale Data
Synthesise and Correlate Likert Scale and Rating-Scale Data
Based on Summary Statistics
Metabolomics Personalized Pathway Analysis Tool
For Implementation of Feed Reduction, Learning Examples, NLP and
Code Management
Working with 'LimeSurvey' Surveys and Responses
Differential Analysis of Rhythmic Transcriptome Data
Quantify Rhythmicity and Differential Rhythmicity in Genomic
Data
Perform Polynomial Evaluation of Linearity
Binning and Plotting of Linearly Referenced Data
Static Univariate Frequentist and Bayesian Linear Calibration
Linear Biomarker Combination: Empirical Performance Optimization
Functions to Explore L-Systems (Lindenmayer Systems)
Lineage Frequency Dynamics from Genomic Surveillance Counts
Minimum Distance Estimation in Linear Regression Model
Tagging and Validating Epidemiological Data
Bayesian Analysis of Epidemic Data Using Line List and Case
Count Approaches
'HTMLWidget' Wrapper of 'LineUp' for Visual Analysis of
Multi-Attribute Rankings
Fast Linguistic Distance and Alignment Computation
Interlinear Glossed Linguistic Examples and Abbreviation Lists
Generation
Easy Linguistics Document Writing with R Markdown
Linking Geographic Information Systems, Remote Sensing and Other
Command Line Tools
Clustering Communication Networks Using the Stochastic Topic
Block Model Through Linkage.fr
Linked Emulator of a Coupled System of Simulators
Access to 'LinkedIn' Ads via the 'Windsor.ai' API
Link Interactive Plots and Tables in 'shiny' Applications
Bivariate Correlations Calculation and Visualization
Generate Concentration-Time Profiles from Linear PK Systems
Linear Regression and Model Selection Framework
Interactive Interpretation of Linear Regression Models
Manipulation of Linear Systems of (in)Equalities
Lipid Annotation for LC-MS/MS DDA or DIA Data
Integrative Visualizations of the Lipidome
Elegant Tools for Processing and Visualization of Lipidomics
Data
Computes and Visualize Lipinski's Parameters
Implements Queue, PriorityQueue and Stack Classes
Longitudinal Integration Site Analysis Toolkit
Statistical Methods for the Item Count Technique and List
Experiment
Incomplete Array with Arbitrary R Objects as Indices
A Toolbox for Working with R Arrays in a Functional Programming
Style
'htmlwidget' for Interactive Views of R Lists
Latent Interaction Testing for Genome-Wide Studies
Likelihood-Based Inference for Time Series Extremes
Lightweight Portable Message Queue Using 'SQLite'
Fast Serializable Random Forests Based on 'ranger'
Automatically Fetching References Metadata from Literature
Databases
Dataset and Tools to Research the Riddle of Literary Quality
Fits a Collection of Curves to Single-Cohort Decomposition Data
Liu Regression with Liu Biasing Parameters and Statistics
Local Interpretable (Model-Agnostic) Visual Explanations
Extract, Convert, and Merge 'pdf' Files from 'zip' Files
Convert Video Files to 'mp3' Format, Merge or Trim Audio Files
using 'FFmpeg'
Leveraging Learning to Automatically Manage Algorithms
Interface for Large Language Models via 'llama.cpp'
Logit Leaf Model Classifier for Binary Classification
Language Model Agents in R for AI Workflows and Research
'LLM'-Assisted Data Cleaning with Multi-Provider Support
LLM-Powered Code Generation, Error Fixing, and Chat for
'RStudio'
Reasoning and Acting Workflow for Automated Data Analysis
Unified Interface for Large Language Model Interactions
Large Language Model (LLM) Tools for Psychological Text Analysis
Interface for Large Language Model APIs in R
'shiny' App for TRAPD/ISPOR Survey Translation with LLMs
Data Analysis of Liquid-Liquid Systems using R
Add Standardized Regression Coefficients to Linear-Model-Objects
A Self-Adaptive Approach for Demodulating Multi-Component Signal
Linear Fixed/Mixed Effects Models for Diallel Crosses
Linear Mixed-Effects Models using 'Eigen' and S4
Information Matrices for 'lmeStruct' and 'glsStruct' Objects
Model Selection and Post-Hoc Analysis for (G)LMER Models
Bootstrap Methods for Nested Linear Mixed-Effects Models
Perform Permutation Test on General Linear and Mixed Linear
Regression
Add Smoothing Spline Modelling Capability to `nlme`
Functions for Estimation and Inference of Selection in
Age-Structured Populations
Filter Methods for Parameter Estimation in Linear and Non Linear
Regression Models
Helper Functions for Linear Model Analysis
Fit Latent Multivariate Mixed Effects Location Scale Models
Sparse High-Dimensional Linear Mixed Modeling with a Partitioned
Empirical Bayes ECM Algorithm
Linear Mixed Models with Sparse Matrix Methods and Smoothing
Repeated Measurement Models for Discrete Times
Inference for Linear Models with Nuisance Parameters
Advanced L-Moment Fitting of Distributions
L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments,
and Many Distributions
(Precipitation) Frequency Analysis and Variability with
L-Moments from 'lmom'
Regional Frequency Analysis using L-Moments
Easy Import of the EU Labour Market Policy Data
An Algorithm for Gene Co-Expression Analysis
Data and Functions Used in Linear Models and Regression with R:
An Integrated Approach
Linear Ridge Regression with Ridge Penalty and Ridge Statistics
Exact Variable-Subset Selection in Linear Regression
Non-Parametric Causal Effects of Feasible Interventions Based on
Modified Treatment Policies
A Package to Visualize Linear Models Features and Play with Them
Long Non-Coding RNA Differential Expression Analysis
LncRNA Identification and Analysis Using Heterologous Features
LogNormal Response Time Item Response Theory Models
Perform Logistic Normal Multinomial Clustering for Microbiome
Compositional Data
Estimation and Testing for a Lognormal-Pareto Mixture
Loadings for Principal Component Analysis and Partial Least
Squares
Interact with the 'US Senate Lobbying Disclosure API'
Generalized Spline Mixed Effect Models for Longitudinal Breath
Data
Access and Process 'LOBSTER' High-Frequency Data
Local Bootstrap Methods for Various Networks
Nonparametric Methods for Generating High Quality Comparative
Effectiveness Evidence
Local Likelihood Inference for Conditional Copula Models
Localization Processes for Functional Data Analysis
Estimation of Marginal Treatment Effects using Local
Instrumental Variables
Running Local LLMs with 'llama.cpp' Backend
LIME-Based Explanations with Interpretable Inputs Based on
Ceteris Paribus Profiles
Package for Sequence Analysis by Local Score
Detection and Localization of Executable Files
Identification of Location Game Equilibria in Networks
Geographically-Conscious Taxonomic Assignment for Metabarcoding
Local Regression, Likelihood and Density Estimation
Test of Stationarity and Localized Autocovariance
Datasets for "Statistics: UnLocking the Power of Data"
Locally Sparse Estimator of Generalized Varying Coefficient
Model for Asynchronous Longitudinal Data
A Logistic Regression Model for Testing Microbial Differential
Abundance
Fast Implementation of (Local) Population Stratification Methods
Low-Rank Decomposition of Brain Connectivity Matrices with
Uniform Sparsity
Dependency-Free Access to PNG Image Files
Genome-Wide Association Analysis of a Biomarker Accounting for
Limit of Detection
Data Sets from "Lectures on Econometrics" by Chirok Han
Text Rendering with Bitmap and Vector Fonts
A Fast and Lightweight Logging System for R, Based on 'log4j'
Log File Analysis in International Large-Scale Assessments
Relative Risk Regression Using the Log-Binomial Model
Log-Concave Density Estimation in Arbitrary Dimensions
Maximum Likelihood Estimation of a Log-Concave Density Based on
Censored Data
Estimate a Log-Concave Probability Density from Iid Observations
Estimate a Log-Concave Probability Mass Function from Discrete
I.i.d. Observations
A Lightweight, Modern and Flexible Logging Utility
Salary Analysis by the Swiss Federal Office for Gender Equality
Binning Variables to Use in Logistic Regression
Identifying Interactions Between Binary Predictors
Logistic Regression with Misclassification in Dependent
Variables
A Copula Based Extension of Logistic Regression
Automatically Runs 18 Logistic Models-14 Individual Logistic
Models and 4 Ensembles of Models
Linear and Logistic Regression-Based Reliable Change Index
Functional Principal Components Logistic Regression
Functions for the Logitnormal Distribution
Logit Models w/Preference & WTP Space Utility Parameterizations
Computing Log-Transformed Kernel Density Estimates for Positive
Data
Double Log Normal Distribution Functions
Log-Multiplicative Models, Including Association Models
Estimation of a Lognormal - Generalized Pareto Mixture
Functions for the Lognormal Distribution
Natural Logarithms of the Gamma Function for Large Values
An Interface for Running 'NetLogo' Simulations
Access to the Hebrew, Greek, and English Version of the Bible
A Logging Utility Focus on Clinical Trial Programming Workflows
Routines for Logspline Density Estimation
Fast Stirling Numbers of the Second Kind
Kernel Regression Smoothing with Local or Global Plug-in
Bandwidth
Longitudinal Dataframes into Arrays for Machine Learning
Training
Recursive Partitioning for Longitudinal Data and Right Censored
Data Using Baseline Covariates
Model-Based Clustering and Classification for Longitudinal Data
A Tool for 'Covariate'-Sensitive Longitudinal Analysis on
'omics' Data
Longitudinal Decomposition of Health Expectancy by Age and Cause
Statistical Methods for the Analysis of Excess Lifetimes
High Dimensional Longitudinal Data Analysis Using MCMC
Decision Tree Analysis for Longitudinal Measurement Data
Nonparametric Predictive Model for Sparse and Irregular
Longitudinal Data
Statistics for Long-Memory Processes (Book Jan Beran), and
Related Functionality
Longitudinal Consensus Clustering with 'flexmix'
Sample Size Calculations for Longitudinal Data
Viral Quasispecies Comparison from Long-Read Sequencing Data
Time-Dependent Prognostic Accuracy with Multiply Evaluated Bio
Markers or Scores
Recursive Partitioning of Longitudinal Data
Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian
Models
Leave One Out Kernel Density Estimates for Outlier Detection
Data Used to Illustrate 'Loon' Functionality
Automatically Create a 'Shiny' App Based on Interactive 'Loon'
Widgets
A Collection of Tools to Conduct Levins' Loop Analysis
Comprehensive Feedback Loop Detection in ODE Models
Loop Functions for Extreme Value Distributions
Integration and Analysis of Chromatin Loop Data
Lowest Radial Distance Method of Marginal Likelihood Estimation
Bridging Log-Odds Ratios and Correspondence Analysis via
Closeness-of-Concordance Measures
Logistic Ordinal Regression Differential Item Functioning using
IRT
LOw Rand and sparsE Covariance matrix estimation
The Lorentz Transform in Relativistic Physics
Imputation of High-Dimensional Count Data using Side Information
Lightweight One-Line Resolving Microbial Ecology Program
Missing Morphometric Data Simulation and Estimation
A Simple Way to Specify Symmetric, Block Diagonal Matrices
Bayesian Inference in Regression Discontinuity Designs
A Collection of Lovecraftian Tales and Texts
Local Partial Autocorrelation Function Estimation for Locally
Stationary Wavelet Processes
Local Political Actor Network Diachronic Analysis Tools
Detecting New Signals under Background Mismodelling
Lassoed Principal Components for Testing Significance of
Features
Boundary Adaptive Local Polynomial Conditional Density Estimator
Local Polynomial Density Estimation and Inference
Nonparametric Smoothing of Laplacian Graph Spectra
Ecological Inference by Linear Programming under Homogeneity
Local Polynomial Estimators of the Intensity Function and Its
Derivatives
Local Projections Impulse Response Functions
LP Nonparametric High Dimensional K-Sample Comparison
Local Partial Likelihood Estimation and Simultaneous Confidence
Band
Linear Parametric Models Applied to Hydrological Series
Measurement Error Analysis and Correction Under Identification
Restrictions
Merging Linkage Maps by Linear Programming
Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs
R Interface to 'lp_solve' Version 5.5.2.0
Learned Pattern Similarity and Representation for Time Series
Robust Group Variable Screening Based on Maximum Lq-Likelihood
Estimation
A Package for Processing Lexical Response Data
Estimate and Test Exponential vs. Pareto Distributions
Sources an R "Module" with Caching & Encapsulation, Returning
Exported Vars
Low Rank Matrix Factorization S3 Objects
Low Rank Correction Quantile Variational Bayesian Algorithm for
Multi-Source Heterogeneous Models
Power and Sample Size Calculation for Non-Proportional Hazards
and Beyond
Likelihood Ratio Tests and Confidence Intervals
Locally Stationary Two-Dimensional Wavelet Process Estimation
Scheme
A Multiscale Test of Spatial Stationarity for LS2W Processes
Applied Latent Semantic Analysis (LSA) Functions
Daten, Beispiele und Funktionen zu 'Large-Scale Assessment mit
R'
Functions to Facilitate the Simulation of Large Scale Assessment
Data
Interface Tools for 'LSD' Simulation Results Files
Impulse-Response Function Analysis for Agent-Based Models
Sensitivity Analysis Tools for 'LSD' Simulations
Constrained Least Squares and Generalized QR Factorization
Bootstrap Methods for Regression Models with Locally Stationary
Errors
Solving Least Squares or Quadratic Programming Problems under
Equality/Inequality Constraints
Semi-Confirmatory Structural Equation Modeling via Penalized
Likelihood or Least Squares
Estimation of the log Likelihood of the Saturated Model
Fitting Latent Space Item Response Models using Joint Maximum
Likelihood Estimation
American options pricing with Least Squares Monte Carlo method
Value American and Real Options Through LSM Simulation
'C++' Header Library for Ordinary Differential Equations
Nonparametric Estimation and Inference Procedures using
Partitioning-Based Least Squares Regression
Lysate and Secretome Peptide Feature Plotter
Linear Splines with Convenient Parametrisations
Companion to "Learning Statistics with R"
The Accelerated Failure Time Model to Right Censored Data Based
on Least-Squares Principle
Land Surface Temperature Retrieval for Landsat 8
Data and Software for "Lessons in Statistical Thinking"
Determining the Number of Factors in Exploratory Factor Analysis
by LSTM
Estimation of Low Rank Plus Sparse Structured Vector
Auto-Regressive (VAR) Model
Simulation and Spectral Estimation of Locally Stationary Wavelet
Packet Processes
Semi-Supervised Algorithm for Document Scaling
Functions to Replicate the Center for Disease Control and
Prevention's 'LTAS' Software in R
Collection of Artistic and Nature-Inspired Color Palettes
Latent Transition Cognitive Diagnosis Model with Covariates
Educational Dataset Examples from the Long Term Ecological
Research Program
Extract Color Palettes from Photos and Pick Official LTER
Palettes
Tools Developed by the Long Term Ecological Research Community
Implementation of Several Phenotype-Based Family Genetic Risk
Scores
Left-Truncated Mixtures of Gamma, Weibull, and Lognormal
Distributions
Longitudinal Targeted Maximum Likelihood Estimation
LTPD and AOQL Plans for Acceptance Sampling Inspection by
Variables
Survival Trees to Fit Left-Truncated and Right-Censored and
Interval-Censored Survival Data
Lightweight Sparklines for a LaTeX Document
Package to Download and Create the DB of LUCAS Data Harmonized
Printing Floating Point Numbers in a Human-Friendly Format
Calculations of Luck in Structured Population Models
Light Use Efficiency Model to Estimate Biomass and YIELD with
and Without Vapour Pressure Deficit
Supporting Functions Maintained by Zhen Lu
Resistant Clustering via Chopping Up Mutual Reachability Minimum
Spanning Trees
Comprehensive Luminescence Dating Data Analysis
Calculate Lunar Phase & Distance, Seasons and Related
Environmental Factors
Latent Variable Gaussian Process Modeling with Qualitative and
Quantitative Input Variables
Perform Inference on Summaries of Longitudinal
Algorithm-Agnostic Variable Importance
Langa-Weir Classification of Cognitive Function for 2022 HRS
Data
Simulate Evapotranspiration and Soil Moisture with the SVAT
Model LWF-Brook90
Bindings to Selected 'liblwgeom' Functions for Simple Features
Exact Spike Train Inference via L0 Optimization
Movement to Behaviour Inference using Random Forest
Multi-Modal Similarity Matrix Factorization for Integrative
Multi-Omics Data Analysis
Multi-Modal Similarity Matrix Joint Factorization
Multi-Modal Matrix Joint Factorization for Integrative
Multi-Omics Data Analysis
Package About Data Manipulation in Pure Base R
Maximum Approximate Bernstein/Beta Likelihood Estimation
Behavioural Studies of Large Language Models
Molecular Acquisition, Cleaning, and Evaluation in R 'MACER'
Retrieve Data from MacLeish Field Station
Measures of Uncertainty for Model Selection
A Tool for Mapping the Distribution of the Biomes and Bioclimate
Colombian Macro-Financial Time Series Generator
Draw Ordered Oxford Grids and Chord Diagrams
Fresh Water Quality Analysis Based on Macrozoobenthos
Mediation Analysis for Count and Zero-Inflated Count Data
Persian Text Mining Tool for Frequency Analysis, Statistical
Analysis, and Word Clouds
Persian Text Mining Tool for Co-Occurrence Network
'MADGRAD' Method for Stochastic Optimization
Fast Data Aggregation, Modification, and Filtering with Pipes
and 'data.table'
Multi Variate Multi Response ADMM with Interaction Effects
Automatic Differentiation of Multivariate Operations
MHC Allele-Based Differencing Between Populations
May All Data be Reproducible and Transparent (MADRaT) *
Functions to Support Data Management and Processing Using the
Maelstrom Research Approach
A Flexible Microarray Data Simulation Model
Hypothesis Tests and Confidence Intervals for Median Absolute
Deviations
Diagnosis of Metabolic Dysfunction Associated Fatty Liver
Disease
Interface for Masked Autoregressive Flows
Data Class and Tools for Handling Spatial-Temporal Data
Mixed Model Association Test for GEne-Environment Interaction
HM Treasury Magenta Book Policy Evaluation Primitives
Pretty Scientific Plotting with Minor-Tick and Log Minor-Tick
Support
Magic Functions to Obtain Results from for Loops
Advanced Graphics and Image-Processing in R
GUI Tools for Interactive Image Processing with 'magick'
Clustering and Prediction using Multi-Task Gaussian Processes
with Common Mean
R-Client for Interacting with the 'UCSF Data Library'
A Pipeline for Meta-Genome Wide Association
Implements the O'Connell-Dobson-Schouten Estimators of Agreement
for Multiple Observers
A Graphical User Interface for Microarray Data Analysis and
Annotation
Exact Matching and Matching-Adjusted Indirect Comparison (MAIC)
Performing Matched-Adjusted Indirect Comparisons (MAIC)
Multimodal Access and Interactive Data Representation
Multilevel Analysis of Individual Heterogeneity and
Discriminatory Accuracy
Get Mailchimp Data via the 'Windsor.ai' API
Mail Merge Using R Markdown Documents and 'gmailr'
Creates a Friendly User Interface for Emails Sending in 'shiny'
Meta Analysis Instrumental Variable Estimator
k-Means Algorithm with a Majorization-Minimization Method
Create Dummy Variables from Categorical Data
Intuitive Construction of Joint Priors for Variance Parameters
Exploring and Testing the Toolchain and System Libraries
Maki Cointegration Test with Structural Breaks
Multiple Approximate Kernel Learning (MAKL)
Machine Learning Assisted Network Inference
An R Interface to Open-Access Malaria Data, Hosted by the
'Malaria Atlas Project'
Dereplicate and Cherry-Pick Mass Spectrometry Spectra
Quantitative Analysis of Mass Spectrometry Data
MALDI Mass Spectrometry Data Robust Pre-Processing and Analysis
Run Multiple Large Language Model Predictions Against a Table,
or Vectors
An R Wrapper for the Java Mallet Topic Modeling Toolkit
Islas Malvinas, Georgias Del Sur y Sándwich Del Sur
Access to the List of Mammal Species of Colombia
Providing the Kubernetes-Like Functions for the Non-Kubernetes
Cloud Service
Multivariate Analysis for Neuroimaging Data
Building Mandalas from Parametric Equations of Classical Curves
Access and Process Data and Documents of the Manifesto Project
An R Interface to the 'ROPTLIB' Library for Riemannian Manifold
Optimization
Add Even More Interactivity to Interactive Charts
Manly Mixture Modeling and Model-Based Clustering
Computing Mann-Whitney Effect Based on Copulas
Tools for Normalizing and Comparing ChIP-seq Samples
Resampling-Based Analysis of Multivariate Data and Repeated
Measures Designs
Multivariate Asymptotic Non-Parametric Test of Association
A Machine-Learning Based Tool to Automate the Identification of
Biological Database IDs
Missingness Alleviation for Network Analysis
Spatiotemporal Nutrient Balance Analysis Across Agricultural and
Municipal Systems
Environmental Phillips Curve Analysis with Multiple Instrumental
Variables and Networks
Mediation, Moderation and Moderated-Mediation After Model
Fitting
Publication-Ready Tables for 'manymome' Results
Many Ways to Make, Modify, Mark, and Measure Myriad Networks
Many Data on State and State-Like Actors in the International
System
Multiple Testing Procedures of Cox (2011) and Wong and Cox
(2007)
Tools for Matrix Algebra, Optimization and Inference
Mapping Markers to the Nearest Genomic Feature
MAP-Bayesian Estimation of PK Parameters
Tools for Plotting Canadian Choropleth Maps and Choropleth
Alternatives
China Administrative Divisions Geospatial Shapefile Data
Multivariate Age-Period-Cohort (MAPC) Modeling for Health Data
Interactive Maps Using 'Mapbox GL JS' and 'Deck.gl'
Interactive Editing of Spatial Data in R
Mapping Smoothed Effect Estimates from Individual-Level Data
Interactive Maps with 'Mapbox GL JS' and 'MapLibre GL JS'
Create Contour Polygons from Regular Grids
High-Performance 'WebGL' Mapping Widgets for R
Efficient Monitoring of Global Biodiversity Portfolios
Spatial Visualisation of Admixture on a Projected Map
Construct Mapper Graphs for Topological and Exploratory Data
Analysis
Topological Data Analysis: Mapper Algorithm
Create Maps Forecasting Risk of Pest Occurrence
Mapping Calculator for EQ-5D Utility Scores
Functions for Transforming Categorical Variables
'sf'-Compatible Interface to 'Google Maps' APIs
Print Maps, Draw on Them, Scan Them Back in
Local Adaptation and Evaluation of Raster Maps
Geographic Display of Survey Data Statistics
Mapping, Pruning, and Graphing Tree Models
Interactive Viewing of Spatial Data in R
Focus-Glue-Context Fisheye Transformations for Spatial
Visualization
The Maraca Plot: Visualizing Hierarchical Composite Endpoints
Robust Marginal Bayesian Variable Selection for Gene-Environment
Interactions
Migration and Range Change Estimation in R
Marginal Hazard Ratio Estimation in Clustered Failure Time Data
Estimation of Meiotic Recombination Rates Using Marey Maps
Approximate Marginal Inference for Regression-Scale Models
Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis
Tests
Max-Type Test for Marginal Correlation with Bootstrap
Build Network Based on Linear Mixed Models from EHRs
Shiny Module for a Markdown Input with Result Preview
Mark-Recapture Analysis for Survival and Abundance Estimation
Marker Gene Detection via Penalized Principal Component Analysis
Market Matching and Causal Impact Inference
Tidy Calculation of Marketing Metrics Plus Quick Analysis
Estimation Methods for Markets in Equilibrium and Disequilibrium
Markov Chain Models for Phylogenetic Trees
Easy Handling Discrete Time Markov Chains
Markov Chain-Based Cost-Optimal Control Charts
Mixture of Markov Chains with Support of Higher Orders and
Multiple Sequences
Methods for Checking the Markov Condition in Multi-State
Survival Data
Statistical Significance of the Markowitz Portfolio
Mark Correlation Functions for Spatial Point Patterns
Marginal Modeling for Exposure Data with Values Below the LOD
Import, Plot and Analyze Bathymetric and Topographic Data
Matching on Poset-Based Average Rank for Multiple Treatments
(MARMoT)
A Parallelized General-Purpose Optimization Based on
Marquardt-Levenberg Algorithm
Markdown Parser and Renderer for R Graphics
Plots a Tree-Like Representation of a Numerical Variable
(Marradi's Tree)
A Hybrid Spatial Model for Capturing Spatially Varying
Relationships Between Variables in the Data
Marginal Mediation Effects with Zero-Inflated Compositional
Mediator
Mandallaz' Model-Assisted Small Area Estimators
Generating Cluster Masks for Single-Cell Dimensional Reduction
Plots
Likelihood Models for Systems with Masked Component Cause of
Failure
Masked-Cause Likelihood Models for Series Systems with Arbitrary
Hazard Components
Visual Class for Vectors with Non-Publishing Requirements
Support Functions and Datasets for Venables and Ripley's MASS
Competitive Gene Sets Test with the Mann-Whitney-Wilcoxon Test
Calculate Mass Properties and Uncertainties of Tree Structures
Body Mass Estimation Equations for Vertebrates
Quality Control and Analysis of Massachusetts Water Quality Data
Maximum Likelihood and Markov Chain Monte Carlo (MCMC) Methods
for Pedigree Reconstruction and Analysis
Model-Averaged Tail Area (MATA) Confidence Interval and
Distribution
Estimate Group Average Treatment Effects with Matching
Multivariate and Propensity Score Matching with Balance
Optimization
Processing Time Series Data Using the Matching Pursuit Algorithm
Nonparametric Preprocessing for Parametric Causal Inference
Combining Matching and Linear Regression for Causal Inference
Optimal Multilevel Matching using a Network Algorithm
Tidy Access to Women's Tennis Association (WTA) Data
Pattern Matching and Enumerated Types in R
Matching and Weighting Multiply Imputed Datasets
A Code Converter from the Matlab/Octave Language to R
Assess Mating Potential in Space and Time
Translate R Expressions to 'MathML' and 'LaTeX'/'MathJax'
Support for the 'Mathpix' API (Image to 'LaTeX')
Mathematics PhD Genealogy Data and Plotting
An Interface for MATLAB using System Calls
Matrix Functions for Teaching and Learning Linear Algebra and
Multivariate Statistics
Model Averaging-Assisted Optimal Transfer Learning
Generates Raven-Like Matrices According to Rules
Sparse and Dense Matrix Classes and Methods
Collection of Functions for Matrix Calculations
Determines Clustering Threshold Based on Similarity Values
Matrix eQTL: Ultra Fast eQTL Analysis via Large Matrix
Operations
Parsimonious Families of Hidden Markov Models for Matrix-Variate
Longitudinal Data
Model-Based Clustering via Matrix-Variate Mixture Models
Modelling with Sparse and Dense Matrices
Working with Matrices over Finite Prime Fields
Simulations of Matrix Variate Distributions
Creating, Manipulating and Annotating Matrix Ensemble
Functions that Apply to Rows and Columns of Matrices (and to
Vectors)
Fast Statistical Hypothesis Tests on Rows and Columns of
Matrices
Literature Matrix Synthesis Tools for Epidemiology and Health
Science Research
An Implementation of Matrix Mathematics that Respects Row and
Column Names
Clustering with Matrix Gaussian and Matrix Transformation
Mixture Models
Decision Models with Multi Attribute Utility Theory
'FASTA' ML and ‘altall’ Sequences from IQ-TREE .state Files
Efficient Bootstrap Methods for Block Maxima
The Group Sequential Max-Combo Test for Comparing Survival
Curves
Perform Phonological Analyses using Maximum Entropy Optimality
Theory
Selecting the Best Set of Relevant Environmental Variables along
with the Optimal Regularization Multiplier for Maxent Niche
Modeling
Space-Filling Design under Maximin Distance
Inference for Maximin Effects in High-Dimensional Settings
Testing Maximal Interaction in Two-Mode Clustering via a
Permutation Based Procedure
Maximum Likelihood Estimation and Related Tools
Model Species Distributions by Estimating the Probability of
Occurrence Using Presence-Only Data
Maximum Matching for General Weighted Graph
Fitting 'Maxent' Species Distribution Models with 'glmnet'
Maximizing Polyclonal Selection Gains Using Integer Programming
Orthogonal Data Projections with Maximal Skewness
Apply a PCA Like Procedure Suited for Multivariate Extreme Value
Distributions
Machine Learning Method Based on Isolation Kernel Mean Embedding
Manage Spatial Metadata for Known Locations
Thematic Plots for Mazama Spatial Datasets
Spatial Data Download and Utility Functions
Core Functionality for Environmental Time Series
Mediation Analysis for Zero-Inflated Mediators
Monotonic Association on Zero-Inflated Data
The Use of Marginal Distributions in Conditional Forecasting
Multiblock Exploratory and Predictive Data Analysis
Maxwell Boltzmann Bose Einstein Fermi Dirac Distribution and
Destruction Rate Modelling
Statistical Functions for the
Maxwell-Boltzmann-Bose-Einstein-Fermi-Dirac (MBBEFD) Family of
Distributions
Multivariate Bias Correction of Climate Model Outputs
Companion Package for the Book "Model-Based Clustering and
Classification for Data Science"
Moment-Based Estimation for Hierarchical Models
Spatial Designs for Ecological and Environmental Surveys
Run Time-Course Model-Based Network Meta-Analysis (MBNMA) Models
Estimation and Inference for Structural Breaks in Linear
Regression Models
Exploration of Multiple Biomarker Responses using Effect Size
Mixed Regression Models with Generalized Log-Gamma Random
Effects
Multivariate Bayesian Sparse Group Selection with Spike and Slab
Multivariate Bayesian Model with Shrinkage Priors
Multivariate Bayesian Structural Time Series
Bayesian Variable Selection Methods for Multivariate Data
A Comprehensive Microbiome Data Processing Pipeline
Tools for Two-Dimensional Monte-Carlo Simulations
Markov Chain Analysis for Structural Behaviour and Stability
Optimal Nonparametric Testing of Missing Completely at Random
Multivariate Cauchy Distribution; Kullback-Leibler Divergence
Monte Carlo Simulation for Surface Backscattering
Matrix Computation Based Identification of Prime Implicants
Visualizing Class Specific Heterogeneous Tendencies in
Categorical Data
Estimate Recurrent Event Burden with Competing Risks
Benchmarking for Multi-Criteria Decision Analysis
Maximum Likelihood Estimation for Generalized Linear Mixed
Models
Machine Coded Genetic Algorithms for Real-Valued Optimization
Problems
Markov Chain Gaussian Fields Simulation and Parameter Estimation
Warnes and Raftery's 'MCGibbsit' MCMC Run Length and Convergence
Diagnostic
Multivariate Covariance Generalized Linear Models
Monte Carlo Hypothesis Tests with Sequential Stopping
Multiplicative Competitive Interaction (MCI) Model
Estimating the Minimal Clinically Important Difference
Metabolic Pathway Completeness and Abundance Calculation
Multinomial Logit Models for Categorical Responses and Discrete
Choices
Gaussian Mixture Modelling for Model-Based Clustering,
Classification, and Density Estimation
Estimating and Testing Intergenerational Social Mobility Effect
Mapping First Moment and C-Statistic to the Parameters of
Distributions for Risk
Posterior Distribution of Extreme Value Models in R
Ensemble Sampler for Affine-Invariant MCMC
Precision of Discrete Parameters in Transdimensional MCMC
Markov Chain Monte Carlo Small Area Estimation
Tools to Visualize, Manipulate, and Summarize MCMC Output
Estimating Subnational Public and Private Contraceptive Supply
Shares Over Time
A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem
Estimating Public and Private Sector Contraceptive Market Supply
Shares
Multiple Criteria Optimization Algorithms and Related Functions
Monte Carlo Solution of First Order Differential Equations
Creates New Folders and Loads Standard Practices for Monterey
County Office of Education
Objects and Methods for Multi-Companion Matrices
Multiple Comparisons Using Normal Approximation
A Simplified Interface for Running Commands on Parallel
Processes
Design and Analysis of Dose-Finding Studies
Improved Inference in Multiple Comparison Procedure – Modelling
A Supplement to the 'DoseFinding' Package for the General Case
Simulation-Based Design and Analysis of Dose-Finding Trials
Testing Generalized Linear Hypotheses for Generalized Linear
Model Parameters by Profile Deviance
Progress Bars and Messages for Parallel Processes
Model Context Protocol Servers and Clients
Classical Test Theory Item Analysis for Multiple-Choice Tests
Processing and Analyzing of Diagnostics Trials
Method Comparison Regression - Mcr Fork for M- And MM-Deming
Regression
Monte Carlo Simulations of Time Changes in Sequences
Determine the Optimal Number of Clusters
Visualize Results of Statistical Hypothesis Tests
Monte Carlo Statistical Simulation Tools Using a Functional
Approach
Tools to Process the Munich ChronoType Questionnaire (MCTQ)
Selecting Bandwidth for Kernel Density Estimator with Minimum
Distance Method
Produces Markdown Log File with a Built-in Function Call
Various Methods for the Two Sample Problem in D>1 Dimensions
Markdown Parser Implemented using the 'MD4C' Library
Mixture and Flexible Discriminant Analysis
Inferring Causal Network from Mixed Observational Data Using a
Directed Acyclic Graph
Multivariate Data Analysis for Chemometrics
A Native Lazy Analytical Backend for MongoDB
Martingale Dependence Tools and Testing for Mixture Cure Models
Modified Detecting Deviating Cells Algorithm in
Pharmacovigilance
Measuring the Difference Between Two Empirical Distributions
Missing Data Imputation Using Gaussian Copulas
Various Methods for the Goodness-of-Fit Problem in D>1
Dimensions
Multivariate Double Hierarchical Generalized Linear Models
Multi-Dimensional MA Normalization for Plate Effect
Inference of Quadratic Functional for Moderate-Dimensional OLS
Graph-Constrained Regression with Enhanced Regularization
Parameters Selection
Web Scraping and Bibliometric Analysis of MDPI Journals
Improved Score Tests for Generalized Linear Models
High Density Genetic Linkage Mapping using Multidimensional
Scaling
Searching for Optimal MDS Procedure for Metric and
Interval-Valued Data
Interactive Document for Working with Multidimensional Scaling
and Principal Component Analysis
Complement to 'Modern Data Science with R'
Analyse and Visualise Multi Electrode Array Burst Data
A Computationally Efficient Mean Shift Implementation
Make Quick Descriptive Tables for Continuous Variables
Bayesian Psychometric Measurement Using 'Stan'
Diagnostics for Lists of Codes Based on Measurements
Send Data from R to the Measurement Protocol
Tools for Educational and Psychological Measurement
Performance Measures for Statistical Learning
Detection and Control of Tree-Ring Widths on Scanned Image
Sections
Maximum Entropy Bootstrap for Time Series
Scalar-on-Function Regression with Measurement Error Correction
Fit the Mixture of Experts Latent Position Cluster Model to
Network Data
Compare Microbial Networks of 'trans_network' Class of
'microeco' Package
Measurement Error Correction in Linear Models with a Continuous
Outcome
Decipher Microbial Turnover along a Gradient
MEchanistic Clustering - Treatment eXposure Framework
Comprehensive Medical, Disease, Treatment, and Drug Datasets
Multi Calculator to Compute Scores of Adherence to Mediterranean
Diet
Load and Use 'MedDRA' Data for Clinical Trials
Bayesian Methods for Identifying the Most Harmful Medication
Errors
Extraction of Medication Information from Clinical Text
Flexible Mediation Analysis Using Natural Effect Models
Power and Sample Size Calculations for Clinical Trials
Mediation Analysis Based on the Product Method
Simulation-Based Sensitivity Analysis for Causal Mediation
Studies
A Unified and Longitudinally Aware Framework for ICD-Based
Comorbidity Assessment
Tools for Obtaining and Cleaning Medicare Public Use Files
Prints a Random Quote from Marcus Aurelius' Book Meditations
Morphological and Structural Features of Medicinal Leaves
Access and Search MedRxiv and BioRxiv Preprint Data
Large Scale Single Mediator Hypothesis Testing
Mixtures of Exponential-Distance Models with Covariates
Access Drug Regulatory Data via FDA and Health Canada APIs
Statistical Framework for Co-Mediators of Zero-Inflated
Single-Cell Data
Analysis of Data with Measurement Error Using a Validation
Subsample
Multivariate Data Handling in Ecology and Biogeography
Multivariate Data Handling with S4 Classes and Sparse Matrices
Perform MEFM Estimation on Matrix Time Series
Interactive Model Exploration using 'GGobi'
Matching Event Data by Location, Time and Type
The Moving Epidemic Method Web Application
Spatial Pattern Detection in Genetic Distance Data Using Moran's
Eigenvector Maps
Management of Survey Data and Presentation of Analysis Results
Hashmaps and Memoization (in-Memory Caching of Repeated
Computations)
R Markdown and Bookdown Templates to Publish Documents
A 'rmarkdown' Template that Can be Highly Customized
Quantifying Ecological Memory in Palaeoecological Datasets and
Other Long Time-Series
Data Sets from Mixed-Effects Models in S
Clustering and Visualizing Distance Matrices
Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models
AI-Driven Code Generation, Explanation and Execution for Data
Analysis
'Mergen' Studio: An 'RStudio' Addin Wrapper for the 'Mergen'
Package
Tools to Merge Hardware Event Monitors (HEMs) Coming from
Separate Subexperiments into One Single Dataframe
Gradient Boosting for Generalized Additive Mixed Models
Performing Monte Carlo Expectation Maximization Random Forest
Imputation for Biological Data
Tools for Analyzing Mixed Effect Regression Models
Download and Process Oklahoma Mesonet Data
Generalized Maximum Entropy Estimation for Smooth Transition and
Kink Regression Models
Conveniently Issue Messages, Warnings, and Errors
Mediation with External Summary Statistic Information
Create Messy Data from Clean Data Frames
Employs String Distance Tools to Help Clean Categorical Data
Computes the Variance-Covariance Matrix of Multidimensional
Parameters Using M-Estimation
Meta-Analyses for Simultaneously Estimating Individual Means
Meta-Analysis for Diagnostic Test Studies
An Interactive Visualisation of Meta-Analysis as a Physical
Weighing Machine
Meta-Analysis for Within-Study and/or Across-Study Biases
BLUE for Combining Location and Scale Information in a
Meta-Analysis
Bayesian Model Averaging for Random and Fixed Effects
Meta-Analysis
Deconvolution and Alignment of 1d NMR Spectra
Probabilistic Latent Variable Models for Metabolomic Data
Datasets and Functions for Reproducing Meta-Analyses
A Biomarker Validation Approach for Classification and
Predicting Survival Using Metabolomics Signature
Basic Functions to Investigate Metabolomics Data Matrices
Simplex-Structured Matrix Factorisation for Metabolomics
Analysis
Data Sets and Code for "Meta-Analysis with R"
Normalize Metabolomic Data using QC Signal
Bayesian Meta-Analysis Using Basic Uncertain Pooling
Meta-CART: A Flexible Approach to Identify Moderators in
Meta-Analysis
Tools for Parsing, Manipulating, and Graphing Taxonomic
Abundance Data
Analysis of the 'Elements of Metacommunity Structure'
Visualize 'Confounder' Control in Meta-Analyses
An Automatic Suite for Estimation of Various Effect Size
Measures
Meta-Analytic Effect Size Calculation for Pre-Post Designs with
Correlation Imputation
A Centralized Metadata Object Focus on Clinical Trial Data
Programming Workflows
Evaluate Periodicity in Large Scale Data
Covariate-Sensitive Analysis of Cross-Sectional High-Dimensional
Data
Extract and Summarise Data from Published Figures
Multivariate Meta-Analysis of Dynamic Model Estimates
Tools to Read, Analyze and Visualize Metadynamics HILLS Files
from 'Plumed'
Tools to Read, Analyze and Visualize Metadynamics 3D HILLS Files
from 'Plumed'
Automated Intuitive Package for Meta-Ensemble Learning
Functional Shannon Entropy for Virome Mutational Analysis
Metapopulation Simulations for Conserving Salmon Through
Portfolio Optimization
Exploring Heterogeneity in Meta-Analysis using Random Forests
Analysis of Metafrontier Models for Efficiency and Productivity
Fused Lasso Approach in Regression Coefficient Clustering
Meta-Analysis of Generalized Additive Models
Meta-Analysis for Detecting Genotype x Environment Associations
Comprehensive Research Synthesis Tools for Systematic Reviews
and Meta-Analysis
Meaningful Grouping of Studies in Meta-Analysis
A Multivariate Meta-Analysis Model for High-Dimensional Data
Transforms Statistical Measures Commonly Used for Meta-Analysis
Privacy-Preserving Meta-Analysis via Low-Rank Basis Hunting
Assessment of Inconsistency in Meta-Analysis using Decision
Thresholds
Landscape and Range Expansion Simulation
Meta-Analysis of Correlated Genetic Association Studies
Likelihood Inference in Meta-Analysis and Meta-Regression Models
Adverse Events Analysis Using 'metalite'
Interactive Table of Descriptive Statistics in HTML
Longitudinal Meta-Analysis with Robust Variance Estimation and
Sensitivity Analysis
Read and Analyze 'MetIDQ&trade;' Software Output Files
Meta-Analysis of Diagnosis and Prognosis Research Studies
Tidy and Streamlined Metabolomics Data Workflows
Handling and Representing Trophic Networks in Space and Time
Natural Language Processing for Meta Analysis
Metaheuristic and Gradient-Based Optimization for Neural Network
Training and Continuous Problems
Meta-Analysis of Studies with Non-Statistically Significant
Unreported Effects
Custom 'MetaphoneBR' Phonetic Encoding for Brazilian Names
Meta-Analysis of Quantiles and Functions of Quantiles
Framework to Build Mechanistic and Metabolic Constrained Species
Distribution Models
Meta-Population Compartmental Model for Respiratory Virus
Diseases
Regression Models for Meta Signal Detection Theory
Meta-Analysis using Structural Equation Modeling
Statistical Methods for Sensitivity Analysis in Meta-Analysis
Meta Analysis for SNP-Set (Sequence) Kernel Association Test
Meta Clustering with Similarity Network Fusion
Pool Literature-Based and Individual Participant Data Based
Spline Estimates
Subtracting Summary Statistics of One or more Cohorts from
Meta-GWAS Results
Reproducible Survey Data Processing with Step Pipelines
Meta-Analysis of a Single Survival Curve
Support Vector Regression with Metaheuristic Algorithms
Optimization
HTML Metadata Tags for 'R Markdown' and 'Shiny'
Enable the Use of 'metacore' to Help Create and Check Dataset
Utility Functions for Conducting and Interpreting Meta-Analyses
Computing Variances and Covariances, Visualization and Missing
Data Solution for Multivariate Meta-Analysis
Forest Plots, Funnel Plots, and Visual Funnel Plot Inference for
Meta-Analysis
Meta-Analytical Implementation to Identify Who Benefits Most
from Treatments
Color Palettes Inspired by Works at the Metropolitan Museum of
Art
RFSI & STRK Interpolation for Meteo and Environmental Variables
Computation and Visualization of Energetic and Vortical
Atmospheric Quantities
Access to Spanish Meteorological Stations Services
Fitting and Plotting Tools for the Maximum Entropy Theory of
Ecology (METE)
E-Value in the Omics Data Association Studies
Analysis of Agreement in Method Comparison Studies
Identify and Rank CpG DNA Methylation Conservation Along the
Human Genome
Simulate DNA Methylation Dynamics on Different Genomic
Structures along Genealogies
Functional Segmentation of the Methylome
Evaluating Bias and Precision in Method Comparison Studies
Advanced Method Optimization for Spectra-Generating Sampling and
Analysis Instrumentation
Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent
Pattern Encoding
Tools for Easier Analysis of Meteorological Fields
Mine Metrics from Common Places on the Web
Weighted Metrics and Performance Measures for Machine Learning
Washington Metropolitan Area Transit Authority API
A Shiny App for Sample Size Estimation in Metabolomic
Experiments
Interface with the Meteo France Synop Data API
Fitting the Metastatistical Extreme Value Distribution MEVD
A Fixed Memeory Moving Expanding Window Average
Color Palettes Inspired by Works of Mexican Painters and
Muralists
Access Mexican Data via APIs and Curated Datasets
Mexican Politics-Inspired Color Palette Generator
Identifying Master Gene Regulators from Gene Expression and
DNA-Binding Data
Measuring Ecosystem Multi-Functionality and Its Decomposition
Fast Covariance Estimation for Multivariate Sparse Functional
Data
Download Archived Meteorological Data from 'Meteo-France'
Multi-Factor Curve Analysis for Grouped Data in 'R'
Compute and Illustrate the Multiple Facets of Functional
Diversity
Leadership-Inference Framework for Multivariate Time Series
Maximal Fat Oxidation and Kinetics Calculation
Multivariable Fractional Polynomial Models with Extensions
Multivariate Functional Principal Component Analysis for Data
Observed on Different Dimensional Domains
Optimal Row-Column Designs for Asymmetrical Factorial
Experiments
Estimation and Diagnostics for Many-Facet Measurement Models
Model-Free Sure Independent Screening Procedures
Marginal Effects, Odds Ratios and Incidence Rate Ratios for GLMs
Simulating, Estimating and Diagnosing MGARCH (BEKK and mGJR)
Processes
Mixed GAM Computation Vehicle with Automatic Smoothness
Estimation
Visualisations for Generalized Additive Models
Marginal Analysis of Misclassified Longitudinal Ordinal Data
Multivariate Generalised Gaussian Distribution; Kullback-Leibler
Divergence
Multivariate Response Generalized Linear Models
Model Averaging for Multivariate GLM with Null Models
Estimating Time-Varying k-Order Mixed Graphical Models
Interact with the Maxar 'MGP' Application Programming Interfaces
Interact with the Maxar MGP Streaming API
Estimate Functional Principal Components from Sparse Data
Safe, Multiple, Simultaneous String Substitution
Multiscale Geographically Weighted Negative Binomial Regression
Displays GWR (Geographically Weighted Regression) and Mixed GWR
Output and Map
GWR, Mixed GWR with Spatial Autocorrelation and Multiscale
GWR/GTWR (Top-Down Scale Approaches)
Nonparametric and Semiparametric Methods for Multivariate
Failure Time Data
Analysis of MHC Data in Non-Model Species
Multilevel Hidden Markov Models Using Bayesian Estimation
Approximate Algorithm for Horseshoe Prior
Modified Hodrick-Prescott Filter with Optimal Smoothing
Parameter Selection
Inference for Hidden Markov and Semi-Markov Models
Multiple Hypotheses Testing for Discrete Data
Multiple Hypotheses Testing for Multiple Families/Groups
Structure
Bayesian Model Selection in Logistic Regression for the
Detection of Adverse Drug Reactions
Missing Data Imputation and Model Checking
A Modular, Integrated Approach to Maximum Entropy Distribution
Modeling
Analysis of Antimicrobial Minimum Inhibitory Concentration Data
Multiple Imputation in Causal Graph Discovery
Multivariate Imputation by Chained Equations
Some Additional Multiple Imputation Functions, Especially for
'mice'
Data and Statistical Analyses after Multiple Imputation
Demand Analysis with the Almost Ideal Demand System (AIDS)
Analysis with the Constant Elasticity of Substitution (CES)
Function
Econometric Production Analysis with Ray-Based Distance
Functions
Symmetric Normalized Quadratic Profit Function
Fast Imputations Using 'Rcpp' and 'Armadillo'
Multiple Imputation by Chained Equations with Multilevel Data
Multiple Imputation by Chained Equations with Random Forests
The Works (in Luxembourguish) of Michel Rodange
Multivariate Independent Comparison of Observations
Promotion Time Cure Model with Mis-Measured Covariates
Do 16s Data Analysis and Generate Figures
Estimates Growth Parameters from Models and Plots the Curve
Statistical Methods for Microbiome Compositional Data
Biomarker Validation for Microbiome-Based Survival
Classification and Prediction
Utilities for Official Spanish Microdata
Microbial Community Ecology Data Analysis
Linked Micromap Plots for U. S. and Other Geographic Areas
Discrete Time Simulation of Mosquito-Borne Pathogen Transmission
Create Simple and Elegant Modal Dialogs in 'shiny'
Determining Vitamin and Mineral Status of Populations
Microplots (Sparklines) in 'LaTeX', 'Word', 'HTML', 'Excel'
Process-Based Modelling of Microbial Populations
Discrete Event Simulation in R and C++, with Tools for
Cost-Effectiveness Analysis
Interface to the 'Microsoft 365' Suite of Cloud Services
Synthetic Control Methods with Micro- And Meso-Level Data
The Computing of Monotonic Spline Bases and Constrained
Least-Squares Estimates
Modified Iterative Cumulative Sum of Squares Algorithm
Order Selection in Vector Autoregression by Mean Square
Information Criteria
Bayesian Platform Design with Subgroup Efficacy
Exploration(MIDAS-2)
Simulating Realistic Microbiome Data using 'MIDASim'
Estimation and Prediction Methods for High-Dimensional Mixed
Frequency Time Series Data
Multiple Imputation by Distance Aided Donor Selection
Tools and Methods for Working with MIDFIELD Data in 'R'
Microstructure Information from Diffusion Imaging
Nearly Exact Sample Size Calculation for Exact Powerful
Nonrandomized Tests for Differences Between Binomial
Proportions
A 'tidymodels' Engine and Other Extensions for the 'midr'
Package
A Decision-Making System for Multiple Imputation
Learning from Black-Box Models by Maximum Interpretation
Decomposition
Multiple Comparisons Procedures Based on Studentized Midrange
and Range Distributions
Performance Criteria Modeler for Discrete Trial Training
Multiple Imputation for Exploratory Factor Analysis
Estimate Migratory Connectivity for Migratory Animals
Impute Missing Values and Fitting Linear Mixed Effect Model
Tools for Estimating, Measuring and Working with Migration Data
Manage 'CDISC' 'ADaM' Dataset Specifications in 'YAML' Format
Inferential Methods for Multimodal and Other Networks
Create Credit State Migration (Transition) Matrices
Graphical User Interface to the 'mi' Package
Learning Causal or Non-Causal Graphical Models Using Information
Theory
IPW and Mean Score Methods for Time-Course Missing Data
Exploratory Factor Analysis Using Model Implied Instrumental
Variables
Model Implied Instrumental Variable (MIIV) Estimation of
Structural Equation Models
User-Friendly R Package for Supervised Machine Learning
Pipelines
Calculates Microbial Lag Duration (on the Population Level) from
Provided Growth Curve Data
Multiple-Instance Learning with Support Vector Machines
Association Tests for Microbial Lineages on a Taxonomic Tree
Mixed Logistic Regression for Genome-Wide Analysis Studies
(GWAS)
Multiple-Instance Logistic Regression with LASSO Penalty
Multivariate Imputation by Mahalanobis Distance Optimization
Data Wrangling for Antimicrobial Resistance Studies
Mixture of Multilayer Integrator Stochastic Block Models
Algorithm to Compute Monitor Independent Movement Summary Unit
(MIMS-Unit)
Calculate MIMS Dissolved Gas Concentrations Without Getting a
Headache
Minimally Changed Two-Level Half-Fractional Factorial Designs
Multivariate Model Based Inference for Domains
Data sets included in Utts and Heckard's Mind on Statistics
Extract and Analyze Median Molecule Intensity from 'citrus'
Output
A Bayesian Design for Minimum Effective Dosing-Finding Trial
Maximal Information-Based Nonparametric Exploration for Variable
Analysis
All Possible Minimally Changed Factorial Run Orders
Lightweight Framework for Orchestrating Multi-Agent Large
Language Models
Minimization Methods for Ill-Conditioned Problems
Create a Mini Version of CRAN Containing Only Selected Packages
Create Simple Yet Powerful HTML Documents with Light Weight CSS
Frameworks
Build a Minimalist Gene Ontology (GO) Database (GODB)
Generate Optimal Designs of Accelerated Life Test using
PSO-Based Algorithm
Implementation of Remez Algorithm for Polynomial and Rational
Function Approximation
Survival Distributions with Piece-Wise Constant Hazards
Implementation of the minMSE Treatment Assignment Method for One
or Multiple Treatment Groups
Quantitatively Analyze Minor Political Parties
R Interface to the Levenberg-Marquardt Nonlinear Least-Squares
Algorithm Found in MINPACK, Plus Support for Bounds
Derivative-Free Optimization Algorithms by Quadratic
Approximation
Effect Sizes for Meta-Analysis of Interactions from Factorial
Experiments
Encode "License-Plates" from Sequences and Decode Them Back
Extension to the 'Lolog' Package for 'Triadic' Network
Statistics
Streamlined Data Processing Tools for Genomic Selection
Multidimensional Iterative Proportional Fitting and Alternative
Models
An Open-Source Tool for Visualization of Climate Mitigation
Scenarios
Minimalist Async Evaluation Framework for R
Diagnostic Tool by Multiple Imputation for Regression
Discontinuity Designs
Left-Censored Recurrent Events Survival Models
Measurement Invariance Assessment Using Random Effects Models
and Shrinkage
Microbiome Regression-Based Kernel Association Tests
Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples
Computerized Adaptive Testing with Multidimensional Item
Response Theory
Linear Regression and Logistic Regression with Missing
Covariates
Miscellaneous Functions for Data and Geospatial Work
Miscellaneous Useful Functions Including LaTeX Tables, Kalman
Filtering, QQplots with Simulation-Based Confidence Intervals,
Linear Regression Diagnostics and Development Tools
Misclassified Interval Censored Time-to-Event Data
Computation of Generalized Linear Models with Misclassified
Covariates Using Side Information
Miscellaneous Functions for Metabarcoding Analysis
Variable Selection for Multiply Imputed Data
Multiple Imputation with Sequential Penalized Regression
Partial Replacement Imputation Estimation for Missing Covariates
Find Range of Cronbach Alpha with a Dataset Including Missing
Data
Ensemble Conditional Trees for Missing Data Imputation
Intuitive Missing Data Imputation Framework
Change Point Detection with Missing Values
Simulating and Analyzing Time to Event Data in the Presence of
Population Mortality
Comparing Observed and Imputed Values under MAR and MCAR
Nonparametric Missing Value Imputation using Random Forest
Missing Value Imputation using Random Forest for Prediction
Settings
Handles Missing Dates and Data and Converts into Weekly and
Monthly from Daily
Missing Outcome Data in Health Economic Evaluation
Handling Missing Values with Multivariate Data Analysis
Testing Homoscedasticity, Multivariate Normality, and Missing
Completely at Random
Joint Sparse Regression & Network Learning with Missing Data
Missing Plot Technique in Design of Experiment
Methods and Reproducible Workflows for Partial Least Squares
with Missing Data
Classify Missing Data as MCAR, MAR, or MNAR
Handling Missing Data in Stochastic Block Models
Self-Organizing Maps with Built-in Missing Data Imputation
Access the Michigan Substance Use Vulnerability Index (MI-SUVI)
Serial Interval and Case Reproduction Number Estimation
Tools for Multiple Imputation in Multilevel Modeling
Quantification of Mitochondrial DNA Heteroplasmy
Tools for Multiple Imputation of Missing Data
Cybersecurity MITRE Standards Data and Digraphs
Estimation/Multiple Imputation for Mixed Categorical and
Continuous Data
Multivariate Normal Mixture Models and Mixtures of Generalized
Linear Mixed Models Including Model Based Clustering
Observed Fisher Information Matrix for Finite Mixture Model
Mixed Effects Cumulative Link and Logistic Regression Models
Mixture Model for the Deconvolution of Thermal Decay Curves
Cluster High Dimensional Categorical Datasets
Bayesian Longitudinal Regularized Quantile Mixed Model
Sparse Canonical Correlation Analysis for High-Dimensional Mixed
Data
Generate and Analyze Mixed-Level Blocked Factorial Designs
Mixed-Effects Diffusion Models with General Drift
Tests of Randomness and Tests of Independence
Mixed, Low-Rank, and Sparse Multivariate Regression on
High-Dimensional Data
Tools for Discrete Multivariate Mixed Membership Models
Statistical Tools for the Analysis of Psychophysical Data
Estimation Methods for Stochastic Differential Mixed Effects
Models
Evaluation of the FIM in NLMEMs using MCMC
Fractional Factorial Designs with Alias and Trend-Free Analysis
Model Based Clustering, Classification and Discriminant Analysis
Using the Mixture of Generalized Hyperbolic Distributions
Mixture of Multiple Highly Variable Feature Selection Methods
Omics Data Integration Using Kernel Methods
Simulated Maximum Likelihood Estimation of Mixed Logit Models
for Large Datasets
Mixture of Longitudinal Factor Analysis Methods
Mixed Model ANOVA and Statistics for Education
Tools for Multilayer and Single Layer Network Modeling
Classification with Matrix Variate Normal and t Distributions
An Extended Mixed-Effects Framework for Meta-Analysis
Mixed Poisson Regression for Overdispersed Count Data
Simulation-Based Power Analysis for Mixed-Effects Models
Finite Mixture Modeling for Raw and Binned Data
Plotting and Average Theta Functions for Multiple Class Mixed
Rasch Models
A Random-Forest-Based Approach for Imputing Clustered Incomplete
Data
Mixtures of Multivariate Shifted Asymmetric Laplace (SAL)
Distributions
Mixture Models: Parametric, Semiparametric, and Robust
Simulating Data to Study Performance of Clustering Algorithms
Fitting Finite Mixture of Scale Mixture of Skew-Normal
Distributions
Mixtures of Power Exponential and Skew Power Exponential
Distributions for Use in Model-Based Clustering and
Classification
Sequential Quadratic Programming for Fast Maximum-Likelihood
Estimation of Mixture Proportions
Clustering Using Mixtures of Sub Gaussian Stable Distributions
Parameter Estimation for Stable Distributions and Their Mixtures
Tools for Analyzing Finite Mixture Models
Dose Response Curve Fitting and Mixture Toxicity Assessment
A Statistical Framework for Comparing Sets of Trees
Modelling Continuous Report Visual Short-Term Memory Studies
Mixture Models for Clustering and Classification
Fitting of Univariate Mixture Distributions to Data using
Various Approaches
Robust and Flexible Model-Based Clustering for Data Sets with
Missing Values at Random
Large-Scale Hypothesis Testing by Variance Mixing
Variable Length Markov Chains with Covariates
Dynamic Multi-Species Size Spectrum Modelling
2D and 3D Movement-Based Kernel Density Estimates (MKDEs)
Matrix Kendall's Tau and Matrix Elliptical Factor Model
Kinetic Evaluation of Chemical Degradation Data
A Modern K-Means (MKMeans) Clustering Algorithm
Power Analysis and Sample Size Calculation
Efficient Multi-Level k-Circulant Supersaturated Designs
Supervised Learning with Mandatory Splits and Seeds
Maximum Likelihood Inference on Multi-State Trees
Variational Autoencoder Models for IRT Parameter Estimation
Abstract Classes for Building 'scikit-learn' Like API
Bias Correction Methods for Models Using Synthetic Data
Create 'ggplot2' and 'gt' Visuals with Major League Baseball
Logos
Major League Baseball Player Statistics Calculator
Causal Inference Methods for Multilevel and Clustered Data
Latent Class Item Response Theory (LC-IRT) Models under
Within-Item Multidimensionality
Classification Models with Copula Functions
Collection of Machine Learning Datasets for Supervised Machine
Learning
Exploratory Data Analysis and Manipulation of Multi-Label Data
Sets
R Ultimate Multilabel Dataset Repository
Resampling Algorithms for Multi-Label Datasets
Maximum Likelihood Estimation of Various Univariate and
Multivariate Distributions
Machine Learning Algorithms with Unified Interface and Confusion
Matrices
Asymptotic Efficient Closed-Form Estimators for Multivariate
Distributions
Computation of the MLE for Bivariate Interval Censored Data
Maximum Likelihood Estimates of Gaussian Processes
MLE for Normally Distributed Data Censored by Limit of Detection
Multilevel Exponential-Family Random Graph Models
High Dimensional Mediation Analysis using Local False Discovery
Rates
Iterative Proportional Fitting Algorithms for Nested Structures
Datasets for Use with Salvan, Sartori and Pace (2020)
Single and Multiple Imputation with Automated Machine Learning
Cell Type Annotation Using Large Language Models
R6-Based ML Learners for 'mlexperiments'
Maximum Likelihood Estimation of DNA Methylation and
Hydroxymethylation Proportions
Maximum Likelihood Models and Tools for Estimation, Prediction,
and Testing
Probing, Plotting, and Interpreting Multilevel Interaction
Effects
Estimating Frequencies, Prevalence and Multiplicity of Infection
Integrating Morphological Modeling and Machine Learning for
Decision Support
Power Analysis and Data Simulation for Multilevel Models
Examples from Multilevel Modelling Software Review
Bayesian Model Averaging for Multinomial Logit Models
'Rcpp' Integration for the 'mlpack' Library
Maximum Likelihood Estimation of the Niche Preemption Model
Multi-Label Prediction Using Gibbs Sampling (and Classifier
Chains)
A Power Analysis Toolbox to Find Cost-Efficient Study Designs
Algorithms for Class Distribution Estimation
Analysis and Visualisation of Benchmark Experiments
Collection of Machine Learning Data Sets for 'mlr3'
Fairness Auditing and Debiasing for 'mlr3'
Extending 'mlr3' to Functional Data Analysis
Filter Based Feature Selection for 'mlr3'
Preprocessing Operators and Pipelines for 'mlr3'
Resampling Algorithms for 'mlr3' Framework
Support for Spatial Objects Within the 'mlr3' Ecosystem
Spatiotemporal Resampling Methods for 'mlr3'
Easily Install and Load the 'mlr3' Package Family
Composable Preprocessing Operators and Pipelines for Machine
Learning
Model-Based Optimization for 'mlr3' Through 'mlrMBO'
Bayesian Optimization and Model-Based Optimization of Expensive
Black-Box Functions
Stepwise Regression with Assumptions Checking
Long-Run Variance Estimation in Time Series Regression
Unified S3 Interface to Machine Learning Models
Efficient Estimation of Bayesian SBMs & MLSBMs
Use the MLS Junk Generator Algorithm to Generate a Stream of
Pseudo-Random Numbers
Machine Learning Models for Soil Properties
Machine Learning and Mapping for Spatial Epidemiology
Multilevel Supervised Topic Models with Multiple Outcomes
Support Compatibility Between 'Maelstrom' R Packages and 'Opal'
Environment
R6-Based ML Survival Learners for 'mlexperiments'
Most Likely Transformations: Documentation and Regression Tests
Multilevel Latent Time Series Models with 'R' and 'Stan'
Mean Length-Based Estimators of Mortality using TMB
Gene Expression Datasets for the 'MM2S' Package
Inference of Linear Mixed Models Through MM Algorithm
Multiple Mediation Analysis for Big Data Sets
Data for Mathematical Modeling and Applied Calculus
An R Package of Minorization-Maximization Algorithm via the
Assembly--Decomposition Technology
Mathematical Morphology in Any Number of Dimensions
Processing of Accelerometry Data with 'GGIR' in mMARCH
Arbitrary Dependency Mixed Multivariate Bayesian Models
Multistate Model Bias-Corrected Robust Variance
Multistage MCMC Method for Detecting DMRs
Modeling Complex Longitudinal Data in a Quick and Easy Way
Minimal Multilocus Distance (MMD) for Source Attribution and
Loci Selection
Multivariate Multinomial Distribution Approximation and
Imputation for Incomplete Categorical Data
Robust Estimation of Copulas by Maximum Mean Discrepancy
Detecting Differentially Variable Genes Using the Mixture of
Marginal Distributions
Estimation of Multinormal Mixture Distribution
Calculate Standardized Morphine Milligram Equivalent Doses
Multi-Study Multi-Modality Generalized Factor Model
Bayesian Informative Hypotheses Evaluation Web Applications
Cluster Adjusted t Statistic Applications
Microbe-Metabolite Interactions-Based Metabolic Profiles
Predictor
Informative Hypothesis Testing Web Applications
Fitting Markov-Modulated Linear Regression Models
Simultaneous Inference for Multiple Linear Contrasts in GEE
Models
Multi-Omic Spectral Clustering using the Flag Manifold
Modern Measures of Population Differentiation
Modeling Multivariate Origins Determinants - Evolutionary
Lineages in Ecology
Implementation of Marker-Assisted Mini-Pooling with Algorithm
Integrative Analysis of Several Related Data Matrices
Access to Teaching Materials from a ZIP File or GitHub
Moment-Matching Approximation for t-Distribution Differences
Convert Dates to MMWR Day, Week, and Year
Clustering Data with Non-Ignorable Missingness using
Semi-Parametric Mixture Models
Diagnostic Tools for a Multivariate Negative Binomial Regression
Model
Multiplex Network Differential Analysis (MNDA)
Modeling Group Differences and Moderation Effects in Statistical
Network Models
Muscle Near-Infrared Spectroscopy Processing and Analysis
Interactive Shiny Presentation for Working with Multinomial
Logistic Regression
Multivariate Nonparametric Methods. An Approach Based on Spatial
Signs and Ranks
A Generator of Multivariate Non-Normal Random Numbers
The Multivariate Normal and t Distributions, and Their Truncated
Versions
Optical Response of Metallic Nanoparticles (Drude + Rayleigh)
Affine Invariant Tests of Multivariate Normality
Spatial Simulation and Scale-Dependent Analysis of Biodiversity
Changes
Multi-Objective Clustering Algorithm Guided by a-Priori
Biological Knowledge
Multi-Objective Optimization for Collecting Cluster Alternatives
Lightweight and Self-Contained Modules for Code Organization
Extraction of Bands from MODIS Surface Reflectance Product MOD09
NRT
Moderation Analysis for Two-Instance Repeated Measures Designs
Association of Covariance for Detecting Differential
Co-Expression
Parametric Modal Regression with Right Censoring
Parametric Modal ARIMA Models using the SKD Family
Multiscale Analysis for Density Functions
Stratified and Personalised Models Based on Model-Based Trees
and Forests
Estimation of Model-Based Predictions, Contrasts and Means
More Data Sets Useful for Modeling Examples
Generate Model Diagrams for Linear Mixed Effect Models
Make Static HTML Website for Predictive Models
Provide Tools to Register Models for Use in 'tidymodels'
Classes and Methods for Training and Using Binary Prediction
Models
Model-Free Estimation of a Psychometric Function
Functions to Assess the Business Impact of Churn Prediction
Models
Compare Models with Cross-Validated Log-Likelihood
Modeling and Map Production using Random Forest and Related
Stochastic Models
Create Model Matrix and Save the Transforming Parameters
A Model Object Framework for Regression Analysis
Modelling Functions that Work with the Pipe
Compare Nested and Non-Nested Structural Equation Models
Modelling Infectious Disease Superspreading from Contact Tracing
Data
Interactive Studio for Explanatory Model Analysis
Summary Tables and Plots for Statistical Models and Data:
Beautiful, Customizable, and Publication-Ready
Testing Infrastructure for Broom Model Generics
The Tidymodels Extension for Time Series Modeling
Ensemble Algorithms for Time Series Forecasting with Modeltime
Resampling Tools for Time Series Forecasting
Tools and Classes for Statistical Models
Modern Resampling Methods: Bootstraps, Wild, Block, Permutation,
and Selection Guidance
An Implementation of Two Modern Education-Based Value-Added
Models
Mode Estimation, Even in the Multimodal Case
Modeling and Analysis of Stochastic Systems
Multivariate Outlier Detection and Imputation for Incomplete
Survey Data
Modified Versions of Mann Kendall and Spearman's Rho Trend Tests
Fast and Efficient Access to MODIS Earth Observation Data
Interface to the 'MODIS Land Products Subsets' Web Services
Calculating Marginal Effects and Levels with Errors
Community Structure Detection via Modularity Maximization
'MatLab'-Style Modeling of Optimization Problems
Latent Interaction (and Moderation) Analysis in Structural
Equation Models (SEM)
Building Regression and Classification Models
Estimate ED50 Based on Modified Turning Point Method
Gaussian Parsimonious Clustering Models with Covariates and a
Noise Component
Mixture-of-Experts Wishart Models for Covariance Data
The Marshal–Olkin Generalized Inverse Weibull Distribution
A Serialization-Style Flattening and Description for JSON
Dental Surface Complexity Measurement Tools
Armadillo Client for the Armadillo Service
'OpenID Connect' Discovery and Authentication
Multiple Objective Latin Hypercube Design
Model Selection with Bayesian Methods and Information Criteria
Moment-Matching Methods for Weighted Sums of Chi-Squared Random
Variables
Moments, Cumulants, Skewness, Kurtosis and Related Tests
Maximum Likelihood Analysis of Animal Movement Behavior Using
Multivariate Hidden Markov Models
Moments of Folded and Doubly Truncated Multivariate
Distributions
An R API Wrapper for the Monash University Probabilistic Footy
Tipping Competition
A Simple Graphical Representation of the Relative Occurrence and
Co-Occurrence of Events
Mongolian 'NSO' 'PXWeb' Data and Boundaries (Tidy Client)
Monitoring Overall Survival in Pivotal Trials in Indolent
Cancers
Multi-Layer Perceptron Neural Network with Optional Monotonicity
Constraints
Monotonic Binning for Credit Rating Models
Shiny User Interface for 'monobin' Package
Easily Create, View and Use Monochrome Colour Palettes
Perform Monothetic Clustering with Extensions to Circular Data
Estimation for MVN and Student-t Data with Monotone Missingness
Explore Monophyly of Taxonomic Groups in a Phylogeny
Bayesian Monotonic Regression Using a Marked Point Process
Construction
Nonparametric Estimation and Inference of a Monotone Hazard
Ratio Function
Test for Monotonicity in Expected Asset Returns, Sorted by
Portfolios
Nonparametric Bootstrap Test for Regression Monotonicity
Monte Carlo Simulation for Structural Equation Modeling
Core Mathematical Functions for Multi-Objective Optimization
Multi-Objective Optimal Design of Experiments
R Markdown format for 'Moodle' XML cloze quizzes
Easily Create Fully Randomized 'Moodle' Test Questions
Helper Functions to Work with 'Moodle' Data
Functions and Datasets for the Book by Keon-Woong Moon
Predicting Moonlight Intensity for a Given Time and Location
Graphical Visualizations for Multi-Objective Optimization
Mean Squared Out-of-Sample Error Projection
Collection of Datasets Pertaining to Loop 1 "Mopac"
Basic Quality Data Assurance for Epidemiological Research
Interpretation Tools for Partial Least Squares Regression
3D Segmentation of Voxels into Morphologic Classes
Calculations and Visualisations Related to Geometric
Morphometrics
Morphometric Maps, Bone Landmarking and Cross Sectional Geometry
Geometric Morphometric Tools to Align, Scale, and Compare
"Shape" of Menstrual Cycle Hormones
Analysis of Regionalization Patterns in Serially Homologous
Structures
Simulate Discrete Character Data along Phylogenetic Trees
Historical Agricultural Data from the University of Illinois
Modelling Reproduction and Survival Data in Ecotoxicology
Bayesian Inference of Binary, Count and Continuous Data in
Toxicology
Identifying Potential Mortalities and Expelled Tags in Aquatic
Acoustic Telemetry Arrays
Analysis of Archaeological Mortality Data
The Double-Gap Life Expectancy Forecasting Model
Parametric Mortality Models, Life Tables and HMD
A Framework for Various Types of Mortality / Life Tables
Estimation and Projection of Age-Specific Mortality Rates
Obtain Data from the Society of Actuaries 'Mortality and Other
Rate Tables' Site
Simulation and Moment Computation for Order Statistics
Project MOSAIC Statistics and Mathematics Teaching Utilities
R-Language Based Calculus Operations for Teaching
Common Utilities for Other MOSAIC-Family Packages
Marshall-Olkin Shock Models with Semi-Independent Time
Moving Sum Based Procedures for Changes in the Mean
Learning Hybrid Bayesian Networks using Mixtures of Truncated
Basis Functions
Effect Size and Confidence Interval Calculator
Utilities for Managing a 'Motherduck' Database
Motif-Based Spectral Clustering of Weighted Directed Networks
Analyzing Paired Neuron Discharge Times for Time-Domain
Synchronization
Mountain Plots, Folded Empirical Cumulative Distribution Plots
Mouse Trajectory Analyses for Behavioural Scientists
Visualizing and Analyzing Animal Track Data
Processing and Analysing Animal Trajectories
Calculation of Slope-Dependant Accumulated Cost Surface,
Least-Cost Paths, Least-Cost Corridors, Least-Cost Networks
Related to Human Movement Across the Landscape
Study Design Toolbox for Movement Ecology Studies
Visualizing and Quantifying Space Use Data for Groups of Animals
Animal Movement Modelling using Hidden Markov Models
Analysis and Visualisation of Musical Audio and Video Movement
Synchrony Data
Estimate Wind Speeds from Bird Trajectories
Visualizing the Decision Rules Underlying Binary Classification
Mixtures of von Mises-Fisher Distributions
Metodos Predictivos de Aprendizaje Estadistico (Statistical
Learning Predictive Methods)
Easily Handling Data from the ‘m-Path’ Platform
Process and Analyse Data from m-Path Sense
Treatment Allocation in Clinical Trials by the Maximal Procedure
Multivariate Process Capability Indices (MPCI)
Data Sets and Scripts for Modeling Psychophysical Data in R
A Two-Step Approach to Testing Overall Effect of
Gene-Environment Interaction for Multiple Phenotypes
Computation of Multidimensional Poverty Index (MPI)
Calculate Alkire-Foster Multidimensional Poverty Measures
Graphical Model Stability and Variable Selection Procedures
An R Package for Facilitating Large-Scale Latent Variable
Analyses in Mplus
Automate Latent Growth Mixture Modelling in 'Mplus'
Parallel Processing Automation for 'Mplus'
Decision Trees with Structural Equation Models Fit in 'Mplus'
Simulation of Matrix Population Models with Defined Life History
Characteristics
Most Probable Number and Other Microbial Enumeration Techniques
Symbolic Computation and More with Multivariate Polynomials
Power Analysis via Monte Carlo Simulation for Correlated Data
Estimating Through the Maximum Product Spacing Approach
Modelling Phylogenetic Signals using Eigenvector Maps
Monetary Policy Shock Series for Empirical Macroeconomics
Mass-Preserving Spline Functions for Soil Data
Analyze Multinomial Processing Tree Models
Data Sets from Montgomery, Peck and Vining
Standardized Comparison of Workflows in Mass Spectrometry-Based
Bottom-Up Proteomics
Modelling and Quantitative Methods in Fisheries
Actuarial Risk Modeling and Life Contingencies
Multiple Regression with Multivariate Adaptive Shrinkage
Penalized Inverse-Variance Weighted Estimator for Mendelian
Randomization
Fitting Multivariate Bidirectional Mendelian Randomization
Networks Using Bayesian Directed Cyclic Graphical Models
Machine-Readable Data Analysis Results with Function Wrappers
Ratios of Coefficients in the General Linear Model
Bayesian Summary Data Models for Mendelian Randomization Studies
Scale Space Multiresolution Analysis of Random Signals
Multi-Visit Closed Population Mark-Recapture Estimates
Multivariate Regression with Covariance Estimation
Outlier Detection of Functional Data Based on the Minimum
Regularized Covariance Trace Estimator
Methods for Analyzing Multiple Response Categorical Variables
(MRCVs)
Global Testing for Multivariate Regression Discontinuity Designs
Fits Regression Models When the Outcome is Partially Missing
Access Data from Marine Regions: Gazetteer & Data Products
Markov Random Field Models for Image Analysis
Fitting and Predicting Large-Scale Nonlinear Regression Problems
using Multi-Resolution Functional ANOVA (MRFA) Approach
Markov Random Fields with Additional Covariates
Depth Measures in Multivariate, Regression and Functional
Settings
Multi-Response (Multivariate) Interpretable Machine Learning
ROI-Based Transformation of Neuroimages into High-Dimensional
Data Frames
Multi-Reader Multi-Case Analysis of Variance
Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests
Sample Size Estimations for Planning Multi-Reader Multi-Case
(MRMC) Studies Without Pilot Data
A Causal Mediation Method with Methylated Region (MR) as the
Mediator
Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for GWAS
Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for
Genome-Wide Association Study with Graphical User Interface
Parallelized Minimum Redundancy, Maximum Relevance (mRMR)
PC Algorithm with the Principle of Mendelian Randomization
Multiply Robust Estimation in Causal Survival Analysis with
Treatment Noncompliance
Minimal Clinically Important Difference and Response Shift
Effect for Health-Related Quality of Life
MDL Multiresolution Linear Regression Framework
Regression Analysis for Very Large Data Sets via Merge and
Reduce
Model-Robust Standardization in Cluster-Randomized Trials
Model-Robust Standardization for Longitudinal Cluster-Randomized
Trials
Assessing Proximal, Distal, and Mediated Causal Excursion
Effects for Micro-Randomized Trials
A Sample Size Calculator for Micro-Randomized Trials
Sample Size Calculator for MRT with Binary Outcomes
Multi-Resolution Thin-Plate Splines on the Sphere
Multivariate Fay Herriot Models for Small Area Estimation
Multivariate Small Area Estimation using Hierarchical Bayesian
Method
Multi-Step Adaptive Estimation Methods for Sparse Regressions
Estimate Sample Size to Detect Bacterial Contamination in a
Product Lot
Data Sets for Courses at the Münster School of Business
Hazard of Multi-Stage Clonal Expansion Models
Chart Generation for 'Microsoft Word', 'Microsoft Excel' and
'Microsoft PowerPoint' Documents
Automated Classification of Mass Spectra
Multivariate Synthetic Control Method Using Time Series
Combine Data from Positive and Negative Ionization Mode Finding
Common Entities
Multiscale Change Point Detection via Gradual Bandwidth
Adjustment in Moving Sum Processes
Analyzing Gene Tree Quartets under the Multi-Species Coalescent
Tests of Multispecies Coalescent Gene Tree Simulator Output
R Client for the Microsoft Cognitive Services Text Analytics
REST API
R Client for the Microsoft Cognitive Services 'Text-to-Speech'
REST API
R Client for the Microsoft Cognitive Services Web Language Model
REST API
Bayesian Inference for Multivariate Stochastic Differential
Equations
Metabolite Set Enrichment Analysis for Loadings
Spectral Entropy for Mass Spectrometry Data
Data and Functions for the Book Modern Statistical Graphics
Degrees of Freedom of Elastic Net, Adaptive Lasso and
Generalized Elastic Net
Extends Messages, Warnings and Errors by Adding Levels and Log
Files
An R Package for Exploring Molecular Signatures Database
MSigDB Gene Sets for Multiple Organisms in a Tidy Data Format
Plotting Mutational Signatures and Mutational Spectra
Micro Simulation Model for Cervical Cancer Prevention
Bayesian Monotonic Single-Index Regression Model with the Skew-T
Likelihood
Multiscale Inference for Nonparametric Time Trend(s)
Multi-State Markov and Hidden Markov Models in Continuous Time
Functions and Datasets for "Methods of Statistical Model
Estimation"
Mine Sustainability Modeling Group (MSMG) 'SimaPro' CSV
Optimizer
Model Selection Based on Machine Learning (ML)
Descriptive Statistics Functions for Numeric Data
Multivariate Statistical Methods with R Applications
Data Sets and Functions Used in Multivariate Statistics: Old
School by John Marden
CORe Multiple Sclerosis Outcomes Toolkit
Sparse Principal Component Analysis with Multiple Principal
Components
A Modified Sequential Probability Ratio Test (MSPRT)
Library Search Against Electron Ionization Mass Spectral
Databases
Helper Functions for Second Primary Cancer Analyses
Tools to Work with Microsoft SQL Server Databases via 'RODBC'
Automated Test Assembly for Multistage Tests Using Mixed-Integer
Linear Programming
Data Preparation, Estimation and Prediction in Multi-State
Models
A Collection of DIF Tests for Multistage Tests
Hypothesis Testing for Markov Switching Models
Multivariate Symmetric Uncertainty and Other Measurements
Michigan State University (MSU) Palettes and Themes
Single Valued Neutrosophic Kruskal-Wallis and Mann Whitney Tests
Convenient Access to MTA Open Data API Endpoints
Multi-Trait Analysis of Rare-Variant Association Study
Bayesian Estimation of Multivariate Threshold Autoregressive
Models
My Toolbox for Assisting Document Editing and Data Presenting
Maximum Tangent Likelihood Estimation for Robust Linear
Regression and Variable Selection
A Procedure for Multicollinearity Testing using Bootstrap
'DuckDB'-Backed Query Client for 'MTGJSON' Card Data
Sample Size and Power for Association Studies Involving
Mitochondrial DNA Haplogroups
Unsupervised Multi-Task and Transfer Learning on Gaussian
Mixture Models
Survival Prediction with Multi-Task Logistic Regression
Multi-Task Prediction using Stacking Algorithms
Ranking using Probabilistic Models and Treatment Choice Criteria
All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS)
and Estimating Multivariate Volatility Models
Multidimensional Top Scoring for Creativity Research
Multivariate Time Series Data Imputation
Accessing the Red List of Montane Tree Species of the Tropical
Andes
Methods in Mahalanobis-Taguchi (MT) System
Multiple Counting Process Structure for Survival Analysis
Generate MUAC and BMI z-Scores and Percentiles for Children and
Adolescents
Data on Freedom of Information Act Requests
Relative Risk Based on the Ratio of Median Unbiased Estimates
Multi-Fidelity Emulator for Computer Experiments with Tunable
Fidelity Levels
Multisource Graph Synthesis with EHR Data
Hazard Function Estimation in Survival Analysis
'Material UI' for 'shiny' Apps and 'Quarto'
Exploring Data with Tree Data Structures
'MUI X Tree View' for 'shiny' Apps and 'Quarto'
Enrichment Analysis Using Multiple Ontologies and False
Discovery Rate
Functions for Pre-Processing Data for Multivariate Data
Visualisation using Tours
Create, Modify and Visualize Multi-Layered Networks
Some Multivariate Analyses using Structural Equation Modeling
Regression and Clustering in Multivariate Response Scenarios
Analysis of Designed High-Dimensional Data using the
Comprehensive MultANOVA Framework
Multivariate Analysis Using Biplots in R
Finite-Sample Tail Bound of Likelihood Ratio Test under
Multinomial Sampling
Simultaneous Inference in General Parametric Models
Multivariate Version of the Diebold-Mariano Test
Multiple Equivalence Tests and Simultaneous Confidence Intervals
Optimal Exact Tests for Multiple Binary Endpoints
GEE Solver for Correlated Nominal or Ordinal Multinomial
Responses
Multi Action Button for 'Shiny' Applications
Apply Functions to Multiple Multidimensional Arrays or Vectors
Finite Difference Method for Multi-Asset Option Valuation
Multicountry Term Structure of Interest Rates Models
Multiple Bias Analysis in Causal Inference
Sensitivity Analysis for Multiple Biases in Meta-Analyses
Multiblock Data Fusion in Statistics and Machine Learning
Tests for a Structural Change in Multivariate Time Series
Evaluating Multinomial Order Restrictions with Bridge Sampling
A Companion to the Multi-CAST Collection
Multiple Canonical Correlation Analysis (Kernel and Functional)
A Generic Convex-Hull-Based Model Selection Method
Build MultiClass Pair-Based Classifiers using TSPs or RF
Flexible Modeling of Multivariate Count Data via the
Multivariate Conway-Maxwell-Poisson Distribution
High-Dimensional Covariate-Augmented Overdispersed Multi-Study
Poisson Factor Model
Collinearity Detection in a Multiple Linear Regression Model
Permutations of Multisets in Cool-Lex Order
Multivariate Difference Between Two Groups
Multi-Omic Differentially Expressed Gene-Gene Pairs
Deploy File Changes Across Multiple 'GitHub' Repositories
Multivariate Analysis and Visualization for Biological Data
Multi-Criteria Design of Experiments for Optimal Design
Multivariate Functional Additive Mixed Models
Multiple Contrast Tests for Functional Data
Multiverse Analyses for Conditioning Data
Multiscale Fisher's Independence Test for Multivariate
Dependence
Analysis of Ecological Drivers on Ecosystem Multifunctionality
Read Fixed Width Format Files Containing Lines of Different Type
Variable Selection in Sparse Multivariate GLARMA Models
Probability Models and Statistical Analysis of Random
Multigraphs
Fitting and Forecasting of Grey Model for Multivariate Time
Series Data
Analyze Outbreak Models of Multi-Group Populations with
Vaccination
MultiGroup Method and Simulation Data Analysis
Group-Sequential Procedures with Multiple Hypotheses
Enables Efficient Joining of Data File on Common Fields using
the Unix Utility Join
Estimation and Inference for Multi-Kink Quantile Regression
Landscape Analysis at Multiple Spatial Scales
Transitive Index Numbers for Cross-Sections and Panel Data
Multidimensional Latent Class Item Response Theory Models
Estimate Bayesian Multilevel Models for Compositional Data
Utility Functions for Multilevel Mediation Analysis
Regularized Bayesian Estimator for Two-Level Latent Variable
Models
Multilevel and Mixed Effects Model Diagnostics and Effect Sizes
Estimates and Plots Single-Level and Multilevel Latent Class
Models
Multifile Record Linkage and Duplicate Detection
Capture-Mark-Recapture Analysis using Multiple Non-Invasive
Marks
Causal Mediation Analysis in Presence of Multiple Mediators
Uncausally Related
Fit Mixture Models Using the Expectation Maximisation (EM)
Algorithm
Information Assessment for Individual Modalities in Multimodal
Regression Models
Harmonizing Various Comorbidity, Multimorbidity, and Frailty
Measures
MULTIplex NEtworks with Shared Structure
Analysis and Mining of Multilayer Social Networks
Bayesian Network Meta-Analysis of Individual and Aggregate Data
Multi-Species N-Mixture (MNM) Models with 'nimble'
Clustering Multinomial Count Data under the Presence of
Covariates
Bayesian Inference for Multinomial Models with Inequality
Constraints
Provides Test Functions for Multivariate Integration
Solution Methods for Multi-Objective Markov Decision Processes
Fits Multivariate Spatio-Temporal Occupancy Model
Generation of Multivariate Ordinal Variates
Infrastructure to Assemble Multi-Panel Figures (from Grobs)
A Package to Test for Multi-Trait Association
Estimating Multiple Breakpoints for a Sequence of Realizations
of Bernoulli Variables
Test and Detection of Explosive Behaviors for Time Series
Addressing Detection Limits by Cumulative Probability Models
(CPMs)
Interrupted Time Series with a Control and Multiple
Interventions
Weighted Cox-Regression for Nested Case-Control Data
Asymptotic Covariance Matrix of Regression Models for Multiple
Outcomes
Additive and Multiplicative Null Models for Multiple Stressor
Data
Algebraic Tools for the Analysis of Multiple Social Networks
Multiplier Data Envelopment Analysis and Cross Efficiency
Analysis of Data from Multiple-Response Questionnaires
High-Dimensional Multi-Study Robust Factor Model
Calculate Multivariate Richness via UTC and sUTC
Fast Cross-Validation for Multi-Penalty Ridge Regression
Reinforcement Learning Tools for Multi-Armed Bandit
Multiply Robust Methods for Missing Data Problems
Multiscale Systematic Conservation Planning Across Nested H3
Grids
Selecting Combinations of Predictors by Leveraging Multiple AUCs
for an Ordered Multilevel Outcome
Estimation of Accuracy in Multisite Machine-Learning Models
Causal Mediation Analysis in Multisite Trials
Measures, Tests and Removes Multivariate Skewness
Clustering a Data Set using Multi-SOM Algorithm
Spline-Based Nonlinear Modeling for Multilevel and Longitudinal
Data
Spectral Analysis Tools using the Multitaper Method
Analyzing and Visualizing Multidimensional Plant Traits
Functions for the Courses Multivariate Analysis and Computer
Intensive Methods
Penalized Estimation of Multiple-Subject Vector Autoregressive
Models
Measuring Multivariate Dependence Using Distance Multivariance
Models Multivariate Cases Using Random Forests
Univariate and Multivariate Trend Testing
Extensible Data Structures for Multivariate Analysis
Cooperative Learning for Multi-View Analysis
Estimation of Multivariate Long-Memory Models Parameters
Model Multivariate Ordinal Responses Including Response Styles
Analyze Nominal Response Data with the Multinomial-Poisson Trick
Bayesian Multivariate Conway-Maxwell-Poisson Regression Model
for Correlated Count Data
Permutation Tests for Multivariate Survival Analysis
Multivariate Generalized Gaussian Distribution, Multivariate t
Distribution, Multivariate Cauchy Distribution, Statistical
Divergence
Common Multiple Testing Procedures and Gatekeeping Procedures
Variable Importance Measures for Multivariate Random Forests
Computation of the Multivariate Marine Recovery Index
Rich Inline Text for 'grid' Graphics and 'flextable'
Interpolate Munsell Renotation Data from Hue Value/Chroma to
CIE/RGB
Multiple Ploidy Estimation Tool for all Species Compatible with
Flow Cytometry
Murphy Diagrams for Forecast Comparisons
Murty's Algorithm for k-Best Assignments
Monetary Unit Sampling and Estimation Methods, Widely Used in
Auditing
Extract Muscle Synergies from Electromyography
Conversion of Nuclear Magnetic Resonance Spectra in Audio Files
Validate and Convert Mutational Impacts Using Standard Genomic
Dictionaries
A Graphical User Interface for the MuToss Project
Decipher Mutational Signatures from Somatic Mutational Catalogs
Computation and Decomposition of the Mutual Information Index
MultiClass Visualizable Classification using Combination of
Projections
Multivariate Methods with Unbiased Variable Selection
An Introduction to Applied Multivariate Analysis with R
Statistical Methods for Analysing Multivariate Abundance Data
Krippendorff's Alpha for Multi-Valued Data
Modelling Multivariate Binary Data with Blocks of Specific
One-Factor Distribution
Workspace Organization, Code and Documentation Editing, Package
Prep and Editing, Etc
Correlation Coefficients for Multivariate Data
Multivariate Variance Components Tests for Multilevel Data
Multivariate (Dynamic) Generalized Additive Models
Multivariate Probabilities of Scale Mixtures of Multivariate
Normal Distributions via the Genz and Bretz (2002) QRSVN Method
Multivariate Generalized Linear Mixed Models for Ranking Sports
Teams
Causal Inference using Multivariate Generalized Propensity Score
Influence Measures and Diagnostic Plots for Multivariate Linear
Models
Compute and Visualize Bivariate Associations
Multivariate, Locally Stationary Wavelet Process Estimation
Imputation Methods for Multivariate Locally Stationary Time
Series
Multivariate Genome Wide Marginal Epistasis Test
Multivariate Meshes and Histograms in Arbitrary Dimensions
Multivariate and Univariate Meta-Analysis and Meta-Regression
A General Framework of Multivariate Mixed-Effects Selection
Models
Multi-State Adaptive Dynamic Principal Component Analysis for
Multivariate Process Monitoring
Multivariate Comparative Tools for Fitting Evolutionary Models
to Morphometric Data
Nelson-Aalen Estimator of the Cumulative Hazard in Multistate
Models
Bayesian Analysis Framework for MVN (Mixture) Distribution
Fast Multivariate Normal and Student's t Methods
Moving Grid Adjustment in Plant Breeding Field Trials
Matrix-Variate Non-Gaussian Linear Regression Models
Simultaneously Impute the Missing and Censored Values
ML Estimation for Multivariate Normal Data with Missing Values
Powerful Tests for Multivariate Normality
Normality Test for Multivariate Variables
Generate New Multivariate Normal Samples from Permutations
Goodness of Fit Tests for Multivariate Normality
Multi-View Orthogonal Projection Regression for Multi-Modality
Integration
Multivariate Outlier Detection Based on Robust Methods
Publication Bias Tests for Meta-Analysis of Diagnostic Accuracy
Test
Multivariate Product Distributions for Elliptically Contoured
Distributions
Multivariate Peaks-over-Threshold Modelling for Spatial Extreme
Events
Compute the Coefficient of Determination for Vector or Matrix
Outcomes
Methods for High-Dimensional Multi-View Learning
Generalized Shapiro-Wilk test for multivariate normality
Matrix-Variate Skew Linear Regression Models
Multivariate Stochastic Linear Ornstein-Uhlenbeck Models for
Phylogenetic Comparative Hypotheses
Bayesian Inference for the Multivariate Skew-t Model
Estimation and Testing for the Multivariate t-Distribution
Estimate Diet Proportions Using Multivariate Tweedie Model
Causal Inference in Spatiotemporal Event Data
Solvers for Maximum Weight Connected Subgraph Problem and Its
Variants
Cross-References Lake Identifiers Between Different Data Sets
Create Maps of Malawi Administrative Boundaries
Spatial Boundary Data for Malawi Administrative Levels
A Functional Data Analysis Package for Spatial Single Cell Data
Efficient Mixed-Level k-Circulant Supersaturated Designs
Measurement Model of Derivatives in 'OpenMx'
Apply Normalization Methods to Multiplexed Images
Specify 'OpenMx' Models with a 'lavaan'-Style Syntax
Stepwise Variable Selection Procedures for Regression Analysis
Chi-Squared Test for Goodness of Fit and Independence Test
Integrative Immunoinformatics for Mycobacterial Diseases in R
Platform
Color Palettes for Mycobacterium Tuberculosis Data Visualization
Automatic Correlation and Regression Test in a 'data.frame'
Graph of Daily and Cumulative Downloads of your Packages
Transcriptomic Scoring for Human Skeletal Muscle Health
Compare Two Data Frames and Summarize Differences
Port of the 'Scilab' 'n1qn1' Module for Unconstrained BFGS
Optimization
Handling Methods for Naver News Text Crawling
Fast and Scalable Approximate k-Nearest Neighbor Search Methods
using 'N2' Library
Read Cancer Records in the NAACCR Format
Exact Derivatives via Automatic Differentiation
Wraps 'libnabo', a Fast K Nearest Neighbour Library for Low
Dimensions
Network-Adjusted Covariates for Community Detection
Nondetects and Data Analysis for Environmental Data
Data Analysis for Censored Environmental Data
Browse Microdata Catalogs Using 'NADA' REST API
IRT Parameters for the National Assessment of Education Progress
Flexible Options for Handling Missing Values
Operations to Ease Data Analyses Specific to Nigeria
Empirical Extrapolation of Time Feature Patterns
High Performance Implementation of the Naive Bayes Algorithm
Nonparametric Additive Instrumental Variable Estimator and
Related IV Methods
Create Visual Citations for Presentations and Posters
Using Needleman-Wunsch to Match Sample Names
Named Entity Recognition in Texts using 'NameTag'
Data Structures, Summaries, and Visualisations for Missing Data
Interface to the 'nanoarrow' 'C' Library
Lightweight Toolkit for Messaging, Concurrency and the Web
Performs Quality Control, Data Normalization, and Batch Effect
Correction for 'NanoString nCounter' Data
Nanosecond-Resolution Time Support for R
Non-Local Alternative Priors in Psychology
Network Meta-Analytic Predictive Prior for Mid-Trial SoC Changes
A Flexible and Robust Sys.sleep() Replacement
Nonlinear Cointegrating Autoregressive Distributed Lag Model
Neural AutoRegressive Fractionally Integrated Moving Average
Model
Subset- And Name-Aware Array Utility Functions