The 'RQuantLib' package makes parts of 'QuantLib' accessible from R
The 'QuantLib' project aims to provide a comprehensive software framework
for quantitative finance. The goal is to provide a standard open source library
for quantitative analysis, modeling, trading, and risk management of financial
assets.
Enables researchers to conduct multivariate statistical analyses
of survey data with randomized response technique items from several designs,
including mirrored question, forced question, and unrelated question. This
includes regression with the randomized response as the outcome and logistic
regression with the randomized response item as a predictor. In addition,
tools for conducting power analysis for designing randomized response items
are included. The package implements methods described in Blair, Imai, and Zhou
(2015) ''Design and Analysis of the Randomized Response Technique,'' Journal
of the American Statistical Association
<http://graemeblair.com/papers/randresp.pdf>.
Analyzes and predicts from matrix population models in the way of the Ramas (c) software
Replication Rate (RR) is the probability of replicating a statistically significant association in genome-wide association studies. This R-package provide the estimation method for replication rate which makes use of the summary statistics from the primary study. We can use the estimated RR to determine the sample size of the replication study, and to check the consistency between the results of the primary study and those of the replication study.
Software for genomic prediction with the RR-BLUP mixed model. One application is to estimate marker effects by ridge regression; alternatively, BLUPs can be calculated based on an additive relationship matrix or a Gaussian kernel.
rrBlupMethod6 -- Re-parametrization of mixed model
formulation to allow for a fixed residual variance when using
RR-BLUP for genomwide estimation of marker effects and linear
transformation of the adjusted means proposed by Piepho et
al.(2011)
Robust Location and Scatter Estimation and Robust
Multivariate Analysis with High Breakdown Point.
Robust multivariate methods for high dimensional data including
outlier detection, PCA, PLS and classification.
Robust Location and Scatter Estimation and Robust
Multivariate Analysis with High Breakdown Point for Incomplete
Data.
Make use of the hardware random number accessed by the 'RdRand'
instruction in recent Intel CPUs (Ivy Bridge and later).
'DRNG' is "Digital Random Number Generator".
Provides implementations of several popular recommendation systems. They can process standard recommendation datasets (user/item matrix) as input and generate rating predictions and recommendation lists.  Standard algorithm implementations included in this package are: Global/Item/User-Average baselines, Item-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according to the standard offline evaluation methodology for recommender systems using measures such as MAE, RMSE, Precision, Recall, AUC, NDCG, RankScore and coverage measures. The package is intended for rapid prototyping of recommendation algorithms and education purposes.
R client interface to the "Redis" key-value database.
'IUCN' Red List (<http://apiv3.iucnredlist.org/api/v3/docs>) client.
The 'IUCN' Red List is a global list of threatened and endangered species.
Functions cover all of the Red List 'API' routes. An 'API' key is required.
'OpenRefine' (formerly 'Google Refine') is a popular, open source data cleaning software. This package enables users to programmatically trigger data transfer between R and 'OpenRefine'. Available functionality includes project import, export and deletion.
An R and Repast integration tool for running individual-based
(IbM) simulation models developed using 'Repast Simphony' Agent-Based framework
directly from R code. This package integrates 'Repast Simphony' models within
R environment, making easier the tasks of running and analyzing model output
data for automated parameter calibration and for carrying out uncertainty and
sensitivity analysis using the power of R environment.
Feature Selection with Regularized Random Forest. This
package is based on the 'randomForest' package by Andy Liaw.
The key difference is the RRF function that builds a
regularized random forest.
Collection of functions for fitting distributions to given data or
by known quantiles. Two main functions fit.perc() and fit.cont() provide
users a GUI that allows to choose a most appropriate distribution without
any knowledge of the R syntax. Note, this package is a part of the 'rrisk'
project.
This package offers methods to perform robust regularized
linear discriminant analysis.
Functions for creating and manipulating RNA secondary structure plots.
Univariate and multivariate methods to analyze
randomized response (RR) survey designs (e.g., Warner, S. L. (1965).
Randomized response: A survey technique for eliminating evasive answer
bias. Journal of the American Statistical Association, 60, 63–69).
Besides univariate estimates of true proportions, RR variables can be used
for correlations, as dependent variable in a logistic regression (with or
without random effects), as predictors in a linear regression, or as
dependent variable in a beta-binomial ANOVA. For simulation and bootstrap
purposes, RR data can be generated according to several models.
The RSP markup language makes any text-based document come alive.  RSP provides a powerful markup for controlling the content and output of LaTeX, HTML, Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. 'Today's date is <%=Sys.Date()%>'.  Contrary to many other literate programming languages, with RSP it is straightforward to loop over mixtures of code and text sections, e.g. in month-by-month summaries.  RSP has also several preprocessing directives for incorporating static and dynamic contents of external files (local or online) among other things.  Functions rstring() and rcat() make it easy to process RSP strings, rsource() sources an RSP file as it was an R script, while rfile() compiles it (even online) into its final output format, e.g. rfile('report.tex.rsp') generates 'report.pdf' and rfile('report.md.rsp') generates 'report.html'.  RSP is ideal for self-contained scientific reports and R package vignettes.  It's easy to use - if you know how to write an R script, you'll be up and running within minutes.
Point and interval estimation of linear parameters with data
obtained from complex surveys (including stratified and clustered samples)
when randomization techniques are used. The randomized response technique
was developed to obtain estimates that are more valid when studying
sensitive topics. Estimators and variances for 14 randomized response
methods for qualitative variables and 7 randomized response methods for
quantitative variables are also implemented. In addition, some data sets
from surveys with these randomization methods are included in the package.
Advanced response surface analysis. The main function RSA computes
and compares several nested polynomial regression models (full polynomial,
shifted and rotated squared differences, rising ridge surfaces, basic
squared differences). The package provides plotting functions for 3d
wireframe surfaces, interactive 3d plots, and contour plots. Calculates
many surface parameters (a1 to a4, principal axes, stationary point,
eigenvalues) and provides standard, robust, or bootstrapped standard errors
and confidence intervals for them.
The package contains all the data sets related to the book
written by the maintainer of the package.
Robust Small Area Estimation. Robust Basic Unit- and Area-Level Models
Provides access to geocomputing and terrain analysis
functions of the geographical information system (GIS) 'SAGA' (System for
Automated Geoscientific Analyses) from within R by running the command
line version of SAGA. This package furthermore provides several R functions
for handling ASCII grids, including a flexible framework for applying local
functions (including predict methods of fitted models) and focal functions to
multiple grids. SAGA GIS is available under GPLv2 / LGPLv2 licence from
http://sourceforge.net/projects/saga-gis/.
Performs parameter estimation for geostatistical data using a resampling-based stochastic approximation (RSA) method.
Contains functions that are useful for pre- and post-processing the tree output from the MCMC-based C++ program sampletrees. The program sampletrees is used to sample gene genealogies conditional on either phased or unphased SNP genotype data. More information about sampletrees can be found at http://stat.sfu.ca/statgen/research/sampletrees.html . Pre-processing tasks involve creating the settings file, the haplotype estimation files (if input data is genotype), and error checking the settings. Post-processing involves reading in the MCMC output from a run of sampletrees and computing summary statistics.
Resampling Stats (http://www.resample.com) is an add-in for
running randomization tests in Excel worksheets. The workflow is (1) to define
a statistic of interest that can be calculated from a data table, (2) to
randomize rows ad/or columns of a data table to simulate a null hypothesis
and (3) and to score the value of the statistic from many randomizations. The
relative frequency distribution of the statistic in the simulations is then
used to infer the probability of the observed value be generated by the null
process (probability of Type I error). This package intends to translate this
logic for R for teaching purposes. Keeping the original workflow is favored over
performance.
Tools to create, evaluate, critique,
revise, track progress, and communicate a detailed wilderness or urban
search plan to management. This package uses and creates csv files in the R
working directory to document inputs and results. It also creates a series
of PDF and PNG files to accomplish communication of the plan. The program
creates and revises search plans using Bayesian models. The package
includes functions bestsearch(), searchstatus() and searchme() to model the
number of searchers and hours required to search an area, calculate the
probability of detection, probability of success, and project the best plan
given limited resources.
SaTScan(TM) (http://www.satscan.org) is software for finding regions in
Time, Space, or Time-Space that have excess risk, based on scan statistics, and
uses Monte Carlo hypothesis testing to generate P-values for these regions.  The
rsatscan package provides functions for writing R data frames in
SaTScan-readable formats, for setting SaTScan parameters, for running SaTScan in
the OS, and for reading the files that SaTScan creates.
This package implements a statistical tool for modeling multivariate relationships using a stepwise cluster analysis (SCA) method.
Performs the Rao-Scott Cochran-Armitage by Slices trend test (RSCABS) used
in analysis of histopathological endpoints. It has functions for both command line
operations along with a built in GUI.
The Scala interpreter is embedded in R and callbacks to R from the embedded interpreter are supported.  Conversely, the R interpreter is embedded in Scala.  Scala versions in the 2.11.x series are supported.
The SciMark 2.0 benchmark was originally developed in Java as a benchmark for numerical and scientific computational performance. It measures the performance of several computational kernels which are frequently occurring in scientific applications. This package is a simple wrapper around the ANSI C implementation of the benchmark.
Client for Rserve, allowing to connect to Rserve instances and issue commands.
Programmatic deployment interface for 'RPubs', 'shinyapps.io', and
'RStudio Connect'. Supported content types include R Markdown documents,
Shiny applications, plots, and static web content.
Uses Elsevier Scopus API to download information about authors and their citations.
A method to download Department of Education College Scorecard data
using the public API. It is based on the dplyr model of
piped commands to select and filter data in a single chained function call.
An API key from the U.S. Department of Education is required.
rscproxy library provides an interface to R used by third
party applications, most notable, but not limited to,
statconnDCOM, ROOo and other systems.
Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for  a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.
Ray Shooting Depth functions are provided for bivariate analysis.
Set of classes and methods to read data and metadata documents
exchanged through the Statistical Data and Metadata Exchange (SDMX) framework,
currently focusing on the SDMX XML standard format (SDMX-ML).
an implementation of the analysis about seed components
from borenstein 2008
Estimate the percentage of seeds in a seedlot that contain stacks
of genetically modified traits.  Estimates are calculated using a
multinomial group testing model with maximum likelihood estimation of the
parameters.
Multiple interactive codes to view and analyze seismic data, via spectrum analysis, wavelet transforms, particle motion, hodograms.  Includes general time-series tools, plotting, filtering, interactive display.
The RSelenium package provides a set of R bindings for the
Selenium 2.0 WebDriver using the JsonWireProtocol. Selenium automates web
browsers (commonly referred to as browsers). Using RSelenium you can
automate browsers locally or remotely.
A robust procedure is implemented to estimate means and covariance matrix of multiple variables with missing data using Huber weight and then to estimate a structural equation model.
Analyses sentiment of a sentence in English and assigns score to it. It can classify sentences to the following categories of sentiments:- Positive, Negative, very Positive, very negative,
Neutral or Sarcasm. For a vector of sentences, it counts the number of sentences in each
category of sentiment.In calculating the score, negation and various degrees
of adjectives are taken into consideration. It deals only with English sentences.
Rserve acts as a socket server (TCP/IP or local sockets)
which allows binary requests to be sent to R. Every
connection has a separate workspace and working
directory. Client-side implementations are available
for popular languages such as C/C++ and Java, allowing
any application to use facilities of R without the need of
linking to R code. Rserve supports remote connection,
user authentication and file transfer. A simple R client
is included in this package as well.
Slow Feature Analysis in R, ported to R based on the
matlab versions SFA toolkit 1.0 by Pietro Berkes and SFA toolkit
2.8 by Wolfgang Konen for matlab.
This package provides functions for calculating
associations between two genes with five correlation
methods(e.g., the Gini correlation coefficient [GCC], the
Pearson's product moment correlation coefficient [PCC], the
Kendall tau rank correlation coefficient [KCC], the Spearman's
rank correlation coefficient [SCC] and the Tukey's biweight
correlation coefficient [BiWt], and three non-correlation
methods (e.g., mutual information [MI] and the maximal
information-based nonparametric exploration [MINE], and the
euclidean distance [ED]). It can also been implemented to
perform the correlation and clustering analysis of
transcriptomic data profiled by microarray and RNA-Seq
technologies. Additionally, this package can be further applied
to construct gene co-expression networks (GCNs).
Robust estimation of sparse inverse covariance matrix via the gamma-divergence.
Functions for estimating models using a Hierarchical Bayesian (HB) framework. The flexibility comes in allowing the user to specify the likelihood function directly instead of assuming predetermined model structures. Types of models that can be estimated with this code include the family of discrete choice models (Multinomial Logit, Mixed Logit, Nested Logit, Error Components Logit and Latent Class) as well ordered response models like ordered probit and ordered logit. In addition, the package allows for flexibility in specifying parameters as either fixed (non-varying across individuals) or random with continuous distributions. Parameter distributions supported include normal, positive/negative log-normal, positive/negative censored normal, and the Johnson SB distribution. Kenneth Train's Matlab and Gauss code for doing Hierarchical Bayesian estimation has served as the basis for a few of the functions included in this package. These Matlab/Gauss functions have been rewritten to be optimized within R. Considerable code has been added to increase the flexibility and usability of the code base. Train's original Gauss and Matlab code can be found here: http://elsa.berkeley.edu/Software/abstracts/train1006mxlhb.html See Train's chapter on HB in Discrete Choice with Simulation here: http://elsa.berkeley.edu/books/choice2.html; and his paper on using HB with non-normal distributions here: http://eml.berkeley.edu//~train/trainsonnier.pdf.
Fits models to longitudinal network data
Robust and efficient feature selection algorithm to
identify important features for predicting survival risk.
The method is based on subsampling and averaging linear models
obtained from the (preconditioned) Lasso algorithm, with an extra
shrinking procedure to reduce the size of signatures. An
evaluation procedure using subsampling is also provided.
This package provides a way to transform an image into a mosaic composed from a set of smaller images (tiles). It also contains a simple function for creating the tiles from a folder of images directly through R, without the need of any external code. At this moment only the JPEG format is supported, either as input (image and tiles) or output (mosaic transformed image).
Functions for interacting with the Adobe Analytics API V1.4
(https://api.omniture.com/admin/1.4/rest/).
This package contains a function RSKC which runs the robust sparse K-means clustering algorithm.
Implements the "Stemming Algorithm for the Portuguese Language" <DOI:10.1109/SPIRE.2001.10024>.
Functions that simplify the R interface the 'SLURM' cluster workload
manager, and automate the process of dividing a parallel calculation across
cluster nodes.
Provides functions to generate response-surface designs, fit first- and second-order response-surface models, make surface plots, obtain the path of steepest ascent, and do canonical analysis.
Aims at loading Facebook and Instagram advertising data from
Smartly.io into R. Smartly.io is an online advertising service that enables
advertisers to display commercial ads on social media networks. The package
offers an interface to query the Smartly.io API and loads data directly into R
for further data processing and data analysis.
It manages snow and weather local time series as provided by MeteoIO (<http://models.slf.ch/docserver/meteoio/html/index.html>, <http://www.slf.ch/ueber/organisation/schnee_permafrost/projekte/MeteoIO/index_EN>, <https://www.openhub.net/p/MeteoIO>). MeteoIO is a C/C++ Open Source library which "has been designed to accomodate both the needs of carefully crafted simulations for a specific purpose/study and for the needs of operational simulations that run automatically and unattended". It is integrated in physical spatially-distributed models and tackles several issues with weather input/output data. Here a SMET S4 class object is defined and can be imported from/ exported to a SMET ini files of MeteoIO , allowing interoperability from R to MeteoIO and other SMET-compliant software.
Read and analyse Root System Markup Language (RSML) files, used to
store plant root system architecture data. More information can be found
at the address <http://rootsystemml.github.io/>.
The Stuttgart Neural Network Simulator (SNNS) is a library
containing many standard implementations of neural networks. This
package wraps the SNNS functionality to make it available from
within R. Using the RSNNS low-level interface, all of the
algorithmic functionality and flexibility of SNNS can be accessed.
Furthermore, the package contains a convenient high-level
interface, so that the most common neural network topologies and
learning algorithms integrate seamlessly into R.
A programmatic interface to various SNP datasets
on the web: openSNP, NBCI's dbSNP database, and Broad Institute SNP
Annotation and Proxy Search. Functions are included for searching for
SNPs for the Broad Institute and NCBI. For OpenSNP, functions are
included for getting SNPs, and data for genotypes, phenotypes,
annotations, and bulk downloads of data by user.
An implementation of the use of efficient score statistics
in genome-wide SNP set analysis with complex traits. Three standard score statistics
(Cox, binomial, and Gaussian) are provided, but the package is easily extensible to
include others. Code implementing the inferential procedure is primarily written in C++ and
utilizes parallelization of the analysis to reduce runtime. A supporting function offers
simple computation of observed, permutation, and FWER and FDR adjusted p-values.
Provides easier interaction with
Socrata open data portals http://dev.socrata.com.
Users can provide a 'Socrata' data set resource URL,
or a 'Socrata' Open Data API (SoDA) web query,
or a 'Socrata' "human-friendly" URL,
returns an R data frame. Converts dates to 'POSIX'
format and manages throttling by 'Socrata'.
Users can upload data to Socrata portals directly
from R.
General Non-linear Optimization Using Augmented Lagrange Multiplier Method.
Somoclu is a massively parallel implementation of self-organizing maps.  It exploits multicore CPUs and it can be accelerated by CUDA. The topology of the map can be planar or toroid and the grid of neurons can be rectangular or hexagonal .
Based on (optionally sparse) quadratic optimization with the main algorithms implemented in C. Includes features for easy processing of many (smaller) records. The algorithm has been tested on fairly large optimization problems with up to a few million variables and several hundred thousand restrictions.
Conducts a spatially-explicit, simulation-based power analysis for detecting trends in population abundance through occupancy-based modeling. Applicable for evaluating monitoring designs in conservation and ecological settings.
R interface to the 'Spectra' library
<http://yixuan.cos.name/spectra/> for large scale eigenvalue and SVD
problems. It is typically used to compute a few
eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues,
which is usually more efficient than eigen() if k << n. This package
provides the 'eigs()' function which does the similar job as in 'Matlab',
'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function
to calculate the largest k singular values and corresponding
singular vectors of a real matrix. Matrices can be given in either dense
or sparse form.
Conversion between attitude representations: DCM, Euler angles, Quaternions, and Euler vectors.
Plus conversion between 2 Euler angle set types (xyx, yzy, zxz, xzx, yxy, zyz, xyz, yzx, zxy, xzy, yxz, zyx).
Fully vectorized code, with warnings/errors for Euler angles (singularity, out of range, invalid angle order),
DCM (orthogonality, not proper, exceeded tolerance to unity determinant) and Euler vectors(not unity).
Also quaternion and other useful functions.
Based on SpinCalc by John Fuller and SpinConv by Paolo de Leva.
Provides functions for estimating power or sample size for RNA-Seq studies. Empirical approach is used and the data is assumed to be count in nature. The underlying distribution of data is assumed to be Poisson or negative binomial. The package contains 6 function; 4 functions provide estimates of sample size or power for Poisson and Negative Binomial distribution; 2 functions provide plots of power for given sample size or sample size for given power.
Calculates a newly defined coefficient of determination, aka R^2, and coefficient of partial determination, aka partial R^2 by Zhang (2016) for generalized linear models (including quasi models with well defined variance functions). It also avoids overstatement of variation proportion explained by the model or a group of covariates.
This package embeds the SQLite database engine in R and
provides an interface compliant with the DBI package.
The source for the SQLite engine (version 3.8.6) is included.
Utilises The jTDS Project's JDBC 3.0 SQL Server
driver to extend the RJDBC classes and DBI methods. It defines a
SQLServerDriver, SQLServerConnection & SQLServerRsult S4 classes as
extensions of the RJDBC equivalent classes with most DBI
methods being thin extensions of the methods defined by RJDBC classes.
However, the dbConnect interface is more convenient, and the data reading
and writing capabilities found in RJDBC's fetch and dbWriteTable methods
have been refined. The package also implements a SQL backend to the dplyr
package.
Methods and tools for Singular Spectrum Analysis including decomposition, forecasting and gap-filling for univariate and multivariate time series.
An extremely simple stack data type, implemented with 'R6'
classes. The size of the stack increases as needed, and the amortized
time complexity is O(1). The stack may contain arbitrary objects.
Provides fast, persistent (side-effect-free) stack, queue and
deque (double-ended-queue) data structures. While deques include a superset
of functionality provided by queues, in these implementations queues are
more efficient in some specialized situations. See the documentation for
rstack, rdeque, and rpqueue for details.
User-facing R functions are provided to parse, compile, test,
estimate, and analyze Stan models by accessing the header-only Stan library
provided by the 'StanHeaders' package. The Stan project develops a
probabilistic programming language that implements full Bayesian statistical
inference via Markov Chain Monte Carlo, rough Bayesian inference via variational
approximation, and (optionally penalized) maximum likelihood estimation via
optimization. In all three cases, automatic differentiation is used to quickly
and accurately evaluate gradients without burdening the user with the need
to derive the partial derivatives.
Estimates pre-compiled regression models using the 'rstan' package, which provides
the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the
customary R syntax with a formula and data.frame plus some additional arguments for priors.
Access to the Digital Universe Data set API pulls data on
exoplants, stars, and galaxies.
A simple R -> Stata interface allowing the user to
execute Stata commands (both inline and from a .do file)
from R.
R interface for china national data http://data.stats.gov.cn/,
some convenient functions for accessing the national data are provided.
This package simulates random orthonormal matrices from linear and quadratic exponential family distributions on the Stiefel manifold. The most general type of distribution covered is the matrix-variate  Bingham-von Mises-Fisher distribution. Most of the simulation methods are presented in Hoff(2009) "Simulation of the Matrix Bingham-von Mises-Fisher Distribution, With Applications to Multivariate and Relational Data."
Toolbox for remote sensing image processing and analysis such as
calculating spectral indices, principal component transformation, unsupervised
and supervised classification or fractional cover analyses.
While streaming processing provides opportunities to deal with extremely large and ever growing data sets in (near) real time, the development of streaming algorithms for complex models is often cumbersome: the software packages that facilitate streaming processing in production environments do not provide statisticians with the simulation, estimation, and plotting tools they are used to. Developers of streaming algorithms would thus benefit from the flexibility of [R] to create, plot and compute data while developing streaming algorithms. Package RStorm implements a streaming architecture modeled on Storm for easy development and testing of streaming algorithms in [R]. RStorm is not intended as a production package, but rather a development tool for streaming algorithms.
R implementation of generalized survival models, where g(S(t|x))=eta(t,x) for a link function g, survival S at time t with covariates x and a linear predictor eta(t,x). The main assumption is that the time effect(s) are smooth. For fully parametric models, this re-implements Stata's 'stpm2' function, which are flexible parametric survival models developed by Royston and colleagues. We have extended the parametric models to include any smooth parametric smoothers for time. We have also extended the model to include any smooth penalized smoothers from the 'mgcv' package, using penalized likelihood. These models include left truncation, right censoring, interval censoring, gamma frailties and normal random effects.
Unified object oriented interface for multiple independent streams of random numbers from different sources.
A convenience interface for communicating with the Stripe payment processor to accept payments online. See <https://stripe.com> for more information.
Access the RStudio API (if available) and provide informative error
messages when it's not.
A collection of efficient and effective tools and
algorithms for subgroup discovery and analytics. The package
integrates an R interface to the org.vikamine.kernel library
of the VIKAMINE system (http://www.vikamine.org) implementing
subgroup discovery, pattern mining and analytics in Java.
This package provides an interface for the package of
nonlinear differential algebraic equation solvers that comprise
SUNDIALS. ODEs are expressed as R functions or as compiled
code.
Interface to three 'Sunlight' Foundation 'APIs' (http://
sunlightfoundation.com/api/) for government data, including the
Congress 'API' 'v3', the Capitol Words 'API', and the Open States
'API'. 'Sunlight' Foundation is a 'nonpartison' 'nonprofit' that collects and
provides data on government activities, and those that influence government.
Functions are provided to interact with each of the three 'APIs'.
Provides functions to estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate marker.
This package provides a range of functions for the design and
analysis of disease surveillance activities. These functions were
originally developed for animal health surveillance activities but can be
equally applied to aquatic animal, wildlife, plant and human health
surveillance activities. Utilities are included for sample size calculation
and analysis of representative surveys for disease freedom, risk-based
studies for disease freedom and for prevalence estimation.
A processing program for spatially distributed data.
It features graphing tools, query building, and polygon clipping.
A graphical user interface is provided.
Randomized singular value decomposition (rsvd) is a very fast probabilistic algorithm that can be used to compute the near optimal low-rank singular value decomposition of massive data sets with high accuracy. SVD plays a central role in data analysis and scientific computing. SVD is also widely used for computing (randomized) principal component analysis (PCA), a linear dimensionality reduction technique. Randomized PCA (rpca) uses the approximated singular value decomposition to compute the most significant principal components. This package also includes a function to compute (randomized) robust principal component analysis (RPCA). In addition several plot functions are provided.
Renders vector-based svg images into high-quality custom-size bitmap
arrays using 'librsvg2'. The resulting bitmap can be written to e.g. png, jpeg
or webp format. In addition, the package can convert images directly to various
formats such as pdf or postscript.
A graphics device for R that uses the w3.org xml standard
for Scalable Vector Graphics.
A graphics device for R that uses the w3.org xml standard
for Scalable Vector Graphics.  This version supports
tooltips with 1 to 3 lines, hyperlinks, and line styles.
An R interface to the SYMPHONY solver for mixed-integer linear programs.
Access SymPy computer algebra system from R via Jython
Provides tabular reporting functionalities to work with 'ReporteRs'
package: 'as.FlexTable' methods are available for 'ftable' and 'xtable' objects,
function 'FlexPivot' is producing a pivot table and 'freqtable' a percentage table,
a 'knitr' print method and a 'shiny' render function are provided for 'FlexTable' objects.
Contains functions for random generation of R x C and 2 x 2 x K contingency tables. In addition to the generation of contingency tables over predetermined intraclass-correlated clusters, it is possible to generate contingency tables without intraclass correlations under product multinomial, multinomial, and Poisson sampling plans. It also consists of a function for generation of random data from a given discrete probability distribution function.
Storing huge data in RData format causes problems because
of the necessity to load the whole file to the memory in order
to access and manipulate objects inside such file; rtape is a
simple solution to this problem. The package contains several
wrappers of R built-in serialize/unserialize mechanism allowing
user to quickly append objects to a tape-like file and later
iterate over them requiring only one copy of each stored object
to reside in memory a time.
Discretize AR(1) process following Tauchen (1986) <http://www.sciencedirect.com/science/article/pii/0165176586901680>. A discrete Markov chain that approximates in the sense of weak convergence a continuous-valued univariate Autoregressive process of first order is generated. It is a popular method used in economics and in finance.
Tools for analyzing sales report files of iTunes Connect.
Robust tail dependence estimation for bivariate models. This package is based on two papers by the authors:'Robust and bias-corrected estimation of the coefficient of tail dependence' and 'Robust and bias-corrected estimation of probabilities of extreme failure sets'. This work was supported by a research grant (VKR023480) from VILLUM FONDEN and an international project for scientific cooperation (PICS-6416).
Provides response time distributions (density/PDF, distribution
function/CDF, quantile function, and random generation): (a) Ratcliff diffusion
model based on C code by Andreas and Jochen Voss and (b) linear ballistic
accumulator (LBA) with different distributions underlying the drift rate.
Exploit controlled vocabularies organized on tematres servers.
A set of tools for creation, manipulation, and modeling
of tensors with arbitrary number of modes. A tensor in the context of data
analysis is a multidimensional array. rTensor does this by providing a S4
class 'Tensor' that wraps around the base 'array' class. rTensor
provides common tensor operations as methods, including matrix unfolding,
summing/averaging across modes, calculating the Frobenius norm, and taking
the inner product between two tensors. Familiar array operations are
overloaded, such as index subsetting via '[' and element-wise operations.
rTensor also implements various tensor decomposition, including CP, GLRAM,
MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements
transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some
auxiliary functions include the Khatri-Rao product, Kronecker product, and
the Hamadard product for a list of matrices.
RTextTools is a machine learning package for automatic
text classification that makes it simple for novice users to
get started with machine learning, while allowing experienced
users to easily experiment with different settings and
algorithm combinations. The package includes nine algorithms
for ensemble classification (svm, slda, boosting, bagging,
random forests, glmnet, decision trees, neural networks,
maximum entropy), comprehensive analytics, and thorough
documentation.
This package contains several functions for calculation of texture metrics for Grey Level Co-occurrence matrices
A set of R functions to output Rich Text Format (RTF) files with high resolution tables and graphics that may be edited with a standard word processor such as Microsoft Word.
Identifies and scores possible Transcription Factor
Binding Sites and allows for FDR analysis and pruning.  It supports
splitting of sequences based on size or a specified GFF, grouping
by G+C content, and specification of Markov model order.  The heavy
lifting is done in C while all results are made available via R.
A suite of custom R Markdown formats and templates for
authoring journal articles and conference submissions.
Reads and writes TIFF format images and
returns them as a pixmap object. Because the resulting object
can be very large for even modestly sized TIFF images, images
can be reduced as they are read for improved performance.  This
package is a wrapper around libtiff (www.libtiff.org), on which
it depends (i.e. the libtiff shared library must be on your
PATH for the binary to work, and tiffio.h must be on your
system to build the package from source). By using libtiff's
highlevel TIFFReadRGBAImage function, this package inherently
supports a wide range of image formats and compression schemes.
This package also provides an implementation of the Ridler
Autothresholding algorithm for easy generation of binary masks.
Interface to Congress, Campaign Finance, Article Search, and
Geographic 'APIs' from the New York Times. Documentation for New York
Times 'APIs' (http://developer.nytimes.com/docs/). This client covers
a subset of the New York Times 'APIs'.
R tools to measure and compare inequality, welfare and poverty using the EU statistics on income and living conditions surveys.
Allows normalization of very large abundance tables, from metagenomics applications or other sources, to an equal depth. Additionally diversity measures, such as richness, Shannon diversity, chao1, chao2 and others are calculated on the fly. The results may be plotted using the provided plotting functions.
STK++ (http://www.stkpp.org) is a collection of
C++ classes for statistics, clustering, linear algebra, arrays (with an
Eigen-like API), regression, dimension reduction, etc. The integration of
the library to R is using Rcpp.

The rtkore package includes the header files from the STK++ core library.
All files contain only templated classes and/or inlined functions.

STK++ is licensed under the GNU LGPL version 2 or later. rtkore
(the stkpp integration into R) is licensed under the
GNU GPL version 2 or later. See file LICENSE.note for details.
STK++ (http://www.stkpp.org) is a collection of
C++ classes for statistics, clustering, linear algebra, arrays (with an
Eigen-like API), regression, dimension reduction, etc. The integration of
the library to R is using Rcpp.

The rtkpp package includes the header files from the STK++
library (currently version 0.8.99). Thus users do not need to
install STK++ itself in order to use it.

STK++ is licensed under the GNU LGPL version 2 or later. rtkpp
(the stkpp integration into R) is licensed under the
GNU GPL version 2 or later.
Truncated Newton function minimization with bounds constraints
based on the 'Matlab'/'Octave' codes of Stephen Nash.
Aimed at seismic tomography, the package
plots tomographic images, and allows one to interact and query
three-dimensional tomographic models.
Vertical cross-sectional cuts can be extracted by mouse click.
Geographic information can be added easily.
Geostatistical interpolation of data with irregular spatial support such as runoff related data or data from administrative units.
This is a port of Jonathan Shewchuk's Triangle library to
R. From his description: "Triangle generates exact Delaunay
triangulations, constrained Delaunay triangulations, conforming
Delaunay triangulations, Voronoi diagrams, and high-quality
triangular meshes. The latter can be generated with no small or
large angles, and are thus suitable for finite element analysis."
This framework aims to provide classes and methods for manipulating and processing of raster time series data (e.g. a time series of satellite images).
An R wrapper around the fast T-distributed Stochastic
Neighbor Embedding implementation by Van der Maaten.
TSON, short for Typed JSON, is a binary-encoded serialization of
JSON like document that support JavaScript typed data (https://github.com/tercen/TSON).
Contains the program 'ttf2pt1', for use with the
'extrafont' package. This product includes software developed by the 'TTF2PT1'
Project and its contributors.
Convert text into speech (voice file in 'wav' format) with API offered by ITRI TTS (Text-To-Speech service, Industrial Technology Research Institute, Taiwan. http://tts.itri.org.tw/). One main function is given, tts_ITRI(). English and Chinese (both traditional and simplified) are supported, and user can specify the speaker accent, speed and volume. Using this package requires internet connection.
Contains functions for launching R Tutorial & Plotting Apps. The R Tutorial app
provides a set of most commonly performed data manipulation tasks in R. The
app structures the contents into different topics and provides an interactive & dynamic interface
for navigation.
The plotting app provides an automated interface for generating plots using the 'ggplot2' package.
Current version of this app supports 10 different plot types along with options to manipulate specific
aesthetics and controls related to each plot type.
The 't-walk' is a general-purpose MCMC sampler for
arbitrary continuous distributions that requires no tuning.
An implementation of calls designed to extract
and organize Twitter data via Twitter's REST and stream
APIs. Functions formulate GET and POST requests and
convert response objects to more user friendly structures,
e.g., data frames or lists. Specific consideration is
given to functions designed to return tweets, friends,
and followers.
A strong type system for R which supports
symbol declaration and assignment with type checking
and condition checking.
An R interface to the 'typeform' (https://typeform.com) application program interface.
Also provides functions for downloading your results.
R port of 'universalchardet', that is the encoding detector
library of Mozilla.
Unobserved Components Models (introduced in Harvey, A. (1989),
Forecasting, structural time series models and the Kalman filter, Cambridge
New York: Cambridge University Press) decomposes a time series into
components such as trend, seasonal, cycle, and the regression effects due
to predictor series which captures the salient features of the series to
predict its behavior.
ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting.
Contains data and visualization functions for USA unemployment
data. Data comes from the US Bureau of Labor Statistics (BLS). State data
is in ?df_state_unemployment and covers 2000-2013. County data is in
?df_county_unemployment and covers 1990-2013. Choropleth maps of the data
can be generated with ?state_unemployment_choropleth and
?county_unemployment_choropleth respectively. See the vignettes for
additional information.
R functions implementing a standard Unit Testing
framework, with additional code inspection and report
generation tools.
Automatically convert a file or package worth of 'RUnit' test
functions into 'testthat' tests.
This package contains some functions for converting R
objects to Java style variables and XML. Generated Java code is
interpretable by dynamic Java libraries such as Beanshell.
Calling R externally and handling the Java or XML output is an
other way to call R from other languages without native
interfaces. For a Java implementation of this approach visit
http://www.mhsatman.com/rcaller.php and
http://stdioe.blogspot.com/search/label/rcaller
User-friendly interface utilities for MCMC models via
Just Another Gibbs Sampler (JAGS), facilitating the use of parallel
(or distributed) processors for multiple chains, automated control
of convergence and sample length diagnostics, and evaluation of the
performance of a model using drop-k validation or against simulated
data. Template model specifications can be generated using a standard
lme4-style formula interface to assist users less familiar with the
BUGS syntax.  A JAGS extension module provides additional distributions
including the Pareto family of distributions, the DuMouchel prior and
the half-Cauchy prior.
Interface to the UNU.RAN library for Universal Non-Uniform RANdom variate generators.
Thus it allows to build non-uniform random number generators from quite arbitrary
distributions. In particular, it provides an algorithm for fast numerical inversion
for distribution with given density function.
In addition, the package contains densities, distribution functions and quantiles
from a couple of distributions.
This package provides a GUI (Graphical User Interface) for
the UNU.RAN random variate generators. Thus it allows to build
non-uniform random number generators interactively for quite
arbitrary distributions. In addition, R code for the required
calls from package Runuran can be displayed and stored for
later use. Some basic analysis like goodness-of-fit tests can
be performed.
An interface to the web service methods provided by the United States Department of Agriculture (USDA). The Agricultural Research Service (ARS) provides a large set of databases. The current version of the package holds interfaces to the Systematic Mycology and Microbiology Laboratory (SMML), which consists of four databases: Fungus-Host Distributions, Specimens, Literature and the Nomenclature database. It provides functions for querying these databases. The main function is \code{associations}, which allows searching for fungus-host combinations.
Utility functions useful when programming and developing R packages.
Implements the 'RUV' (Remove Unwanted Variation) algorithms.  These algorithms attempt to adjust for systematic errors of unknown origin in high-dimensional data.  The algorithms were originally developed for use with genomic data, especially microarray data, but may be useful with other types of high-dimensional data as well.  These algorithms were proposed by Gagnon-Bartsch and Speed (2012), and by Gagnon-Bartsch, Jacob and Speed (2013).  The algorithms require the user to specify a set of negative control variables, as described in the references.  The algorithms included in this package are 'RUV-2', 'RUV-4', 'RUV-inv', and 'RUV-rinv', along with various supporting algorithms.
Contains diverse more or less complicated functions, written to simplify user's life: simplifications of existing functions, basic but not implemented tests, easy-to-use tools, bridges between functions of different packages... All functions are presented in the French book 'Aide-memoire de statistique appliquee a la biologie', written by the same author and available on CRAN.
A collection of functions for computing "r-values" from various
kinds of user input such as MCMC output or a list of effect size estimates
and associated standard errors. Given a large collection of measurement units,
the r-value, r, of a particular unit is a reported percentile that may be
interpreted as the smallest percentile at which the unit should be placed in the
top r-fraction of units.
Operations on triangular meshes based on 'VCGLIB'. This package
integrates nicely with the R-package 'rgl' to render the meshes processed by
'Rvcg'. The Visualization and Computer Graphics Library (VCG for short) is
an open source portable C++ templated library for manipulation, processing
and displaying with OpenGL of triangle and tetrahedral meshes. The library,
composed by more than 100k lines of code, is released under the GPL license,
and it is the base of most of the software tools of the Visual Computing Lab of
the Italian National Research Council Institute ISTI (http://vcg.isti.cnr.it),
like 'metro' and 'MeshLab'. The 'VCGLIB' source is pulled from trunk (svn://
svn.code.sf.net/p/vcg/code/trunk/vcglib) and patched to work with options
determined by the configure script as well as to work with the header files
included by 'RcppEigen'.
Check latest release version of R and R package (both in 'CRAN' or 'Bioconductor').
Query the main 'R' 'SVN' repository to find the
versions 'r-release' and 'r-oldrel' refer to, and also all
previous 'R' versions and their release dates.
Retrieve, map and summarize data from the 'VertNet.org' archives.
Functions allow searching by many parameters, including 'taxonomic' names,
places, and dates. In addition, there is an interface for conducting spatially
delimited searches, and another for requesting large 'datasets' via email.
Wrappers around the 'xml2' and 'httr' packages to make it easy to
download, then manipulate, HTML and XML.
The RVFam package provides functions to perform single SNP association analyses and gene-based tests for continuous, binary and survival traits against sequencing data (e.g. exome chip) using family data.
Vector Graphics devices for 'SVG', 'DrawingML' for
Microsoft Word, PowerPoint and Excel.
Test suite for non-uniform pseudo-random number generators.
To detecting rare variants for binary traits using general pedigrees, the pedigree disequilibrium tests are proposed by collapsing rare haplotypes/variants with/without weights. To run the test, MERLIN is needed in Linux for haplotyping.
Play Video Poker with R, complete with a graphical user
interface. So far, only "Jacks or Better" is implemented.
ViennaCL is a free open-source linear algebra library
for computations on many-core architectures (GPUs, MIC) and
multi-core CPUs. The library is written in C++ and supports CUDA,
OpenCL, and OpenMP (including switches at runtime).
I have placed these libraries in this package as a more efficient
distribution system for CRAN. The idea is that you can write a package
that depends on the ViennaCL library and yet you do not need to
distribute a copy of this code with your package.
Variable metric nonlinear function minimization with bounds constraints.
The 'Vowpal Wabbit' project is a fast out-of-core learning
system sponsored by Microsoft Research (having started at Yahoo! Research)
and written by John Langford along with a number of contributors. This R
package does not include the distributed computing implementation of the
cluster/ directory of the upstream sources. Use of the software as a network
service is also not directly supported as the aim is a simpler direct call
from R for validation and comparison.
This is a collection of the five region-based
rare-variant genetic association tests. The following tests are
currently implemented: ASKAT, ASKAT-Normalized, VC-C1, VC-C2 and
VC-C3.
When a gene or a genetic region is significantly associated with a disease or a trait, the rare variant selection procedure is able to distinguish causal (risk or protective) rare variants from noncausal rare variants located within the same gene or the same genetic region.
Computes estimates of the probability of related individuals sharing a rare variant.
Used to compute population controls weighted rare variants transmission distortion test
Use multiple regression methods to test rare variants
association with disease traits.
A set of R functions which provide an
environment for the Time-Frequency analysis of 1-D signals (and
especially for the wavelet and Gabor transforms of noisy
signals). It was originally written for Splus by Rene Carmona,
Bruno Torresani, and Wen L. Hwang, first at the University of
California at Irvine and then at Princeton University.  Credit
should also be given to Andrea Wang whose functions on the
dyadic wavelet transform are included. Rwave is based on the
book: "Practical Time-Frequency Analysis: Gabor and Wavelet
Transforms with an Implementation in S", by Rene Carmona, Wen
L. Hwang and Bruno Torresani, Academic Press, 1998.
This package will download model predictions from 15 different global circulation models in 20 year intervals from the world bank.  Users can also access historical data, and create maps at 2 different spatial scales.
a Bipartite graph and is constructed based on the spatial and/or non-spatial attributes of the spatial objects in the dataset. Secondly, RW techniques are utilized on the graphs to compute the outlierness for each point (the differences between spatial objects and their spatial neighbours). The top k objects with higher outlierness are recognized as outliers.
RWebLogo is a wrapper for the WebLogo python package
that allows generating of customised sequence logos. Sequence logos are
graphical representations of the sequence conservation of nucleotides (in a
strand of DNA/RNA) or amino acids (in protein sequences). Each logo
consists of stacks of symbols, one stack for each position in the sequence.
The overall height of the stack indicates the sequence conservation at that
position, while the height of symbols within the stack indicates the
relative frequency of each amino or nucleic acid at that position. In
general, a sequence logo provides a richer and more precise description of,
for example, a binding site, than would a consensus sequence.
An R interface to Weka (Version 3.9.0).
Weka is a collection of machine learning algorithms for data mining
tasks written in Java, containing tools for data pre-processing,
classification, regression, clustering, association rules, and
visualization.  Package 'RWeka' contains the interface code, the
Weka jar is in a separate package 'RWekajars'.  For more information
on Weka see <http://www.cs.waikato.ac.nz/ml/weka/>.
External jars required for package 'RWeka'.
Communications simulation package supporting forward error correction.
This package provides Wiener process distribution functions,
namely the Wiener first passage time density, CDF, quantile and random
functions.
A plug in for using WinEdt as an editor for R.
The Rwinsteps package facilitates communication between R
and the Rasch modeling software Winsteps. The package currently
includes functions for reading and writing command files,
sending them to Winsteps, reading and writing data according to
command file specifications, reading output into R, and
plotting various results.
A communications simulation package supporting common wireless modulation
formats including BPSK, QPSK, 8-PSK, 16-PSK, 16-QAM and 64-QAM. The package includes AWGN
noise generation, and raised cosine and square root raised cosine pulse shaping. It also
includes convenience functions for plotting constellation diagrams, density plots, stem
plots and eye diagrams. Together these functions enable the evaluation of bit error and
symbol error rates, evaluation of pulse shaping and inter-symbol interference and support
visualization of the respective signals and noise in a variety of formats.
Enables mapping of country level and gridded user datasets.
High resolution vector country boundaries derived from
Natural Earth data, can be plotted in rworldmap.
Provides a set of functions for performing digital signal
processing.
Implements various tests, visualizations, and metrics
for diagnosing convergence of MCMC chains in phylogenetics.  It implements
and automates many of the functions of the AWTY package in the R
environment.
Tools for getting historical weather information and forecasts from wunderground.com.  Historical weather and forecast data includes, but is not limited to, temperature, humidity, windchill, wind speed, dew point, heat index.  Additionally, the weather underground weather API also includes information on sunrise/sunset, tidal conditions, satellite/webcam imagery, weather alerts, hurricane alerts and historical record high/low temperatures.
Fits the R x C inference model described in Greiner and
Quinn (2009).  Allows incorporation of survey results.
This package allows the visualization of your favorite
XKCD comic strip directly from R. XKCD web comic content is
provided under the Creative Commons Attribution-NonCommercial
2.5 License.
Functions which allow to read many XMCDA tags and transform them into R variables which are then usable in MCDA algorithms written in R. It also allows to write certain R variables into XML files respecting the XMCDA standard.
Methods to compute chemical similarity between two or more reactions and molecules. Allows masking of chemical substructures for weighted similarity computations. Uses packages 'rCDK' and 'fingerprint' for cheminformatics functionality.
Facilities for running simulations from ordinary
differential equation (ODE) models, such as pharmacometrics and other
compartmental models.  A compilation manager translates the ODE model
into C, compiles it, and dynamically loads the object code into R for
improved computational efficiency.  An event table object facilitates
the specification of complex dosing regimens (optional) and sampling
schedules.  NB: The use of this package requires both C and
Fortran compilers, for details on their use with R please see
Section 6.3, Appendix A, and Appendix D in the "R Administration and
Installation" manual.
Identify and display TRACEs for a specified shrinkage path and determine
the extent of shrinkage most likely, under normal distribution theory, to produce an
optimal reduction in MSE Risk in estimates of regression (beta) coefficients.
An interface to the yacas computer algebra system.
'Yandex Translate' (https://translate.yandex.com/) is a statistical machine translation system.
The system translates separate words, complete texts, and webpages.
This package can be used to detect language from text and to translate it to supported target language.
For more info: https://tech.yandex.com/translate/doc/dg/concepts/About-docpage/ .
You can use this package to translate thousands of words. The Youdao translation open API is applied in this package. But, it just translates less than 1000 English words into Chinese.
Package contains some data and functions that
are used in my forthcoming "R you ready?" book.
A programmatic interface to web-services of YouTheria. YouTheria is
an online database of mammalian trait data <http://www.utheria.org/>.
This package is a port to R of the SysGran program, written in Delphi by Camargo (2006). It contains functions for the analysis of grain size samples (in logarithmic (phi) and geometric (micrometers) scale) based on various methods, like Folk & Ward (1957) and Methods of Moments (Tanner, 1995), among others; textural classifications and distribution of unconsolidated sediments are shown in histograms, bivariated plots and ternary diagrams of Shepard (1954) and Pejrup (1988). English and Portuguese languages are supported in outputs
R is very powerful but it lacks some of the functionalities found in
Stata or SPSS to manage survey data. The 'memisc' package provides these
(variable labels, value labels, definable missing values and so on), but to
efficiently work these functions need a graphical interface to allow the user
to get an overview of the data. This package provides such a graphical interface,
similar in fashion to SPSS's Variable View and data managing system. It uses the
'memisc' package as its backend. Additionally, 'Rz' has a powerful plot assistant
interface based on 'ggplot2'.
R interface to the 'Zabbix API' data <https://www.zabbix.com/documentation/3.0/manual/api/reference>. Enables easy and direct communication with 'Zabbix API' from 'R'.
Interface to the ZeroMQ lightweight messaging kernel (see <http://www.zeromq.org/> for more information).
A set of functions used in teaching STATS 201/208 Data Analysis at the University of Auckland. The functions are designed to make parts of R more accessible to a large undergraduate population who are mostly not statistics majors.
Set of tools to verify forecasts through the computation of typical prediction scores against one or more observational datasets or reanalyses (a reanalysis being a physical extrapolation of observations that relies on the equations from a model, not a pure observational dataset). Intended for seasonal to decadal climate forecasts although can be useful to verify other kinds of forecasts. The package can be helpful in climate sciences for other purposes than forecasting.
Fit a spatial instrumental-variable regression by two-stage least squares.
The main function s4vd() performs a biclustering via sparse
singular value decomposition with a nested stability selection.
The results is an biclust object and thus all methods of the
biclust package can be applied.
Perform joint segmentation on two signal dimensions derived from
total read depth (intensity) and allele specific read depth (intensity) for
whole genome sequencing (WGS), whole exome sequencing (WES) and SNP array data.
A collection of baseball analytics functions for sabermetrics
purposes. Among these functions include popular metrics such as FIP, wOBA, and
runs created and other advanced metrics.
Semiparametric empirical likelihood ratio
based test of changepoint with one-change or epidemic alternatives
with data-based model diagnostic
Functions for detecting eye fixations in raw eye-tracking
data.  The detection is done using a velocity-based algorithm for
saccade detection proposed by Ralf Engbert and Reinhold Kliegl in
2003.  The algorithm labels segments as saccades when the velocity of
the eye movement exceeds a certain threshold.  Anything between two
saccades is considered a fixation.  Thus the algorithm is not
appropriate for data containing episodes of smooth pursuit eye
movements.
Computes the Exposure-At-Default based on standardized approach
of the Basel III Regulatory framework (SA-CCR). Currently, trade types of all
the five major asset classes have been created and, given the inheritance-
based structure of the application, the addition of further trade types is
straightforward. The application automatically separates the trades on the
corresponding hedging and netting sets including the basis and volatility
transactions. All the examples appearing on the regulatory paper (including the
margined and the un-margined workflow) have been implemented.
Performs constrained optimization for expensive black-box problems.
Provides the density, distribution, quantile and generation
functions of some obscure probability distributions, including the doubly non-
central t, F, Beta, and Eta distributions; Lecoutre's lambda-prime and K-prime;
the upsilon distribution; the (weighted) sum of non-central chi-squares to a
power; the (weighted) sum of log non-central chi-squares; the product of non-
central chi-squares to powers; the product of doubly non-central F variates.
Maximum likelihood tools to fit and compare models of species
abundance distributions and of species rank-abundance distributions.
Time series models for small area estimation based on area-level models.
The SAEMIX package implements the Stochastic Approximation EM algorithm for parameter estimation in (non)linear mixed effects models. The SAEM algorithm: - computes the maximum likelihood estimator of the population parameters, without any approximation of the model (linearisation, quadrature approximation,...), using the Stochastic Approximation Expectation Maximization (SAEM) algorithm, - provides standard errors for the maximum likelihood estimator - estimates the conditional modes, the conditional means and the conditional standard deviations of the individual parameters, using the Hastings-Metropolis algorithm. Several applications of SAEM in agronomy, animal breeding and PKPD analysis have been published by members of the Monolix group (http://group.monolix.org/).
An implementation of a stacked sparse autoencoder for dimension reduction of features and pre-training of feed-forward neural networks
with the 'neuralnet' package is contained within this package. The package also includes a predict function for the stacked autoencoder object to generate the compressed
representation of new data if required. For the purposes of this package, 'stacked' is defined in line with http://ufldl.stanford.edu/wiki/index.php/Stacked_Autoencoders .
The underlying sparse autoencoder is defined in the documentation of 'autoencoder'.
Methods to fit robust alternatives to commonly used models used in
Small Area Estimation. The methods here used are based on best linear
unbiased predictions and linear mixed models. At this time available models
include area level models incorporating spatial and temporal correlation in
the random effects.
A complete set of functions to calculate several EBLUP (Empirical Best Linear Unbiased Predictor) estimators and their mean squared errors. All estimators are based on an area-level linear mixed model introduced by Rao and Yu in 1994 (see documentation). The REML method is used for fitting this model.
Tools for the simulation of data in the context of small area
estimation. Combine all steps of your simulation - from data generation
over drawing samples to model fitting - in one object. This enables easy
modification and combination of different scenarios. You can store your
results in a folder or start the simulation in parallel.
The aim of the package is to provide some basic functions
for doing statistics with one dimensional Fuzzy Data (in the
form of polygonal fuzzy numbers). In particular, the package
contains functions for the basic operations on the class of
fuzzy numbers (sum, scalar product, mean, median, Hukuhara difference)
as well as for calculating (Bertoluzza) distance,
sample variance, sample covariance, and the
Dempster-Shafer (levelwise) histogram. Moreover a function to
simulate fuzzy random variables, bootstrap tests for the
equality of means, and a function to do linear regression given
trapezoidal fuzzy data is included. Version 1.0 fixes some bugs
of previous versions.
Functions for Generalized and Safe-Bayesian Ridge and Lasso Regression models with both fixed and varying variance.
Overloads the glm function in the stats package so that
a test for the existence of the maximum likelihood estimate is included
in the fitting procedure for binary regression models.
Tools for the statistical analysis and visualization of (relative and absolute) quantitative (LFQ,TMT,HRM) Proteomics data.
Design and sensitivity analysis for computer experiments with scalar-valued output and functional input, e.g. over time or space. The aim is to explore the behavior of the sensitivity over the functional domain.
Implements an information theory approach to the analysis of line
cross data providing model averaged results of parameter estimates and
unconditional standard errors.  Also includes functions to provide a
visualization of models space, custom plots of multi-model inference results, and traditional
line cross analysis plots.
A coordinate descent algorithm for computing the solution path of the sparse and coupled sparse asymmetric least squares, including the elastic net and (adaptive) Lasso penalized SALES and COSALES regressions.
The SALTSampler package facilitates Monte Carlo Markov Chain (MCMC)
sampling of random variables on a simplex. A Self-Adjusting Logit Transform
(SALT) proposal is used so that sampling is still efficient even in difficult
cases, such as those in high dimensions or with parameters that differ by orders
of magnitude. Special care is also taken to maintain accuracy even when some
coordinates approach 0 or 1 numerically. Diagnostic and graphic functions are
included in the package, enabling easy assessment of the convergence and mixing
of the chain within the constrained space.
The package SAM targets at high dimensional predictive
modeling (regression and classification) for complex data
analysis. SAM is short for sparse additive modeling, and adopts
the computationally efficient basis spline technique. We solve
the optimization problems by various computational algorithms
including the block coordinate descent algorithm, fast
iterative soft-thresholding algorithm, and newton method. The
computation is further accelerated by warm-start and active-set
tricks.
Programs for fitting Gaussian linear mixed models (LMM).
A framework for running sets of MCMC samplers on sets of
distributions with a variety of tuning parameters, along with plotting
functions to visualize the results of those simulations.  See sc-intro.pdf
for an introduction.
Two-step estimation
and maximum likelihood estimation
of Heckman-type sample selection models:
standard sample selection models (Tobit-2)
and endogenous switching regression models (Tobit-5).
Computes sample size for Student's t-test and for the Wilcoxon-Mann-Whitney test for categorical data. The t-test function allows paired and unpaired (balanced / unbalanced) designs as well as homogeneous and heterogeneous variances. The Wilcoxon function allows for ties.
Computes the required sample size using the optimal designs with multiple constraints proposed in Mayo et al.(2010). This optimal method is designed for two-arm, randomized phase II clinical trials, and the required sample size can be optimized either using fixed or flexible randomization allocation ratios.
Computes the required sample size for estimation of totals, means
and proportions under complex sampling designs.
A set of R functions for calculating sample size
requirements using three different Bayesian criteria in the
context of designing an experiment to estimate a normal mean or
the difference between two normal means.  Functions for
calculation of required sample sizes for the Average Length
Criterion, the Average Coverage Criterion and the Worst Outcome
Criterion in the context of normal means are provided.
Functions for both the fully Bayesian and the mixed
Bayesian/likelihood approaches are provided.
A set of R functions for calculating sample size
requirements using three different Bayesian criteria in the
context of designing an experiment to estimate the difference
between two binomial proportions. Functions for calculation of
required sample sizes for the Average Length Criterion, the
Average Coverage Criterion and the Worst Outcome Criterion in
the context of binomial observations are provided. In all
cases, estimation of the difference between two binomial
proportions is considered. Functions for both the fully
Bayesian and the mixed Bayesian/likelihood approaches are
provided.
Functions for drawing and calibrating samples.
Sampling procedures from the book 'Stichproben - Methoden
und praktische Umsetzung mit R' by Goeran Kauermann and Helmut
Kuechenhoff (2010).
Functions to estimate from survey data. This package is a user-friendly wrapper of the samplingVarEst package. It considers that the user is more familiar with practical survey data rather than with research on survey sampling (variance estimation). More functionalities are on the way.
In the field of stratified sampling design, this package
offers an approach for the determination of the best
stratification of a sampling frame, the one that ensures the
minimum sample cost under the condition to satisfy precision
constraints in a multivariate and multidomain case. This
approach is based on the use of the genetic algorithm: each
solution (i.e. a particular partition in strata of the sampling
frame) is considered as an individual in a population; the
fitness of all individuals is evaluated applying the
Bethel-Chromy algorithm to calculate the sampling size
satisfying precision constraints on the target estimates.
Functions in the package allows to: (a) analyse the obtained
results of the optimisation step; (b) assign the new strata
labels to the sampling frame; (c) select a sample from the new
frame accordingly to the best allocation.
Functions for the execution of the genetic algorithm are a modified
version of the functions in the 'genalg' package.
Functions to calculate some point estimators and estimating their variance under unequal probability sampling without replacement. Single and two stage sampling designs are considered. Some approximations for the second order inclusion probabilities are also available (sample and population based). A variety of Jackknife variance estimators are implemented.
Sampling surface simulation is useful in the comparison of different areal sampling methods
in forestry, ecology and natural resources. The sampSurf package allows the simulation
of numerous sampling methods for standing trees and downed woody debris in a spatial context.
It also provides an S4 class and method structure that facilitates the addition of new sampling
methods.
Augmenting a matched data set by generating multiple stochastic, matched samples from the data using a
multi-dimensional histogram constructed from dropping the input matched data into a multi-dimensional grid built on
the full data set. The resulting stochastic, matched sets will likely provide a collectively higher coverage of the full
data set compared to the single matched set. Each stochastic match is without duplication, thus allowing downstream
validation techniques such as cross-validation to be applied to each set without concern for overfitting.
This package contains R functions to gauge the impact of unpublished studies upon the meta-analytic summary effect of a set of published studies. (Credits: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 282574.)
Data sets for the book 'Statistical Analysis of
Network Data with R'.
Model-robust standard error estimators for cross-sectional, time series, and longitudinal data.
Recent gcc and clang compiler versions provide functionality to
memory violations and other undefined behaviour; this is often referred to as
"Address Sanitizer" (or SAN) and "Undefined Behaviour Sanitizer" (UBSAN).
The Writing R Extension manual describes this in some detail in Section 4.9.

This feature has to be enabled in the corresponding binary, eg in R, which
is somewhat involved as it also required a current compiler toolchain which
is not yet widely available, or in the case of Windows, not available at all
(via the common Rtools mechanism).

As an alternative, the pre-built Docker containers available via the Docker Hub
at https://registry.hub.docker.com/u/eddelbuettel/docker-debian-r/ can be used
on Linux, and via boot2docker on Windows and OS X.

This package then provides a means of testing the compiler setup as the
known code failures provides in the sample code here should be detected
correctly, whereas a default build of R will let the package pass.

The code samples are based on the examples from the Address Sanitizer
Wiki at https://code.google.com/p/address-sanitizer/wiki/AddressSanitizer.
Sankey plots illustrate the flow of information or material.
There are several functions to implement the method for analysis in a randomized clinical trial with strata with following key features. A stratified Mann-Whitney estimator addresses the comparison between two randomized groups for a strictly ordinal response variable. The multivariate vector of such stratified Mann-Whitney estimators for multivariate response variables can be considered for one or more response variables such as in repeated measurements and these can have missing completely at random (MCAR) data. Non-parametric covariance adjustment is also considered with the minimal assumption of randomization. The p-value for hypothesis test and confidence interval are provided.
Software for the book Spectral Analysis for Physical
Applications, Donald B. Percival and Andrew T. Walden,
Cambridge University Press, 1993.
Functions for statistical analysis of point processes.
Read SAS files in the sas7bdat data format.
Using any importation code designed for SAS users to read
ASCII files into sas7bdat files, the SAScii package parses
through the INPUT block of a (.sas) syntax file to design the
parameters needed for a read.fwf function call.  This allows
the user to specify the location of the ASCII (often a .dat)
file and the location of the .sas syntax file, and then load
the data frame directly into R in just one step.
Data sets and sample lmer analyses corresponding
to the examples in Littell, Milliken, Stroup and Wolfinger
(1996), "SAS System for Mixed Models", SAS Institute.
A statistical method for significant analysis of
comparative proteomics based on LC-MS/MS Experiments
Functions for reading, listing
the contents of, and writing 'SAS' 'xport' format files.
The functions support reading and writing of either
individual data frames or sets of data frames.  Further,
a mechanism has been provided for customizing how
variables of different data types are stored.
This smorgasbord provides a variety of functions which are useful
for handling, manipulating and visualizing remote sensing data.
Bayesian inference of graphical model structures using spanning trees.
Implements Bayesian statistical methodology for the
analysis of complex computer models.
It allows for the emulation, calibration, and validation of computer models,
following methodology described in Bayarri et al 2007, Technometrics.
The purpose of this package is to be able to save and load only
the needed variables/columns of a dataframe in special binary files (tar
archives) - which seems to be a lot faster method than loading the whole
binary object (RData files) via load() function, or than loading columns
from SQLite/MySQL databases via SQL commands (see vignettes). Performance
gain on SSD drives is a lot more sensible compared to basic load()
function. The performance improvement gained by loading only the chosen
variables in binary format can be useful in some special cases (e.g. where
merging data tables is not an option and very different datasets are needed
for reporting), but be sure if using this package that you really need
this, as non-standard file formats are used!
Tests coefficients with sandwich estimator of variance and with small samples. Regression types supported are gee, linear regression, and conditional logistic regression.
Smooth Backfitting for additive models using
Nadaraya-Watson estimator
An MCMC algorithm for simultaneous feature selection and classification,
and visualization of the selected features and feature interactions.
An implementation of SBFC by Krakovna, Du and Liu (2015), <http://arxiv.org/abs/1506.02371>.
This package estimates parameters of a Gaussian copula,
treating the univariate marginal distributions as nuisance
parameters as described in Hoff(2007). It also provides a
semiparametric imputation procedure for missing multivariate
data.
sbioPN is a package suited to perform simulation of deterministic and stochastic systems of biochemical reaction
networks with spatial effects.
Models are defined using a subset of Petri Nets, in a way that is close at how chemical reactions are defined.
For deterministic solutions, sbioPN creates the associated system of differential equations "on the fly", and
solves it with a Runge Kutta Dormand Prince 45 explicit algorithm.
For stochastic solutions, sbioPN offers two variants of Gillespie algorithm, or SSA.
For hybrid deterministic/stochastic,
it employs the Haseltine and Rawlings algorithm, that partitions the system in fast and slow reactions.
sbioPN algorithms are developed in C to achieve adequate performance.
An ADMM implementation of SDP-1, a semidefinite programming relaxation of the maximum likelihood estimator for fitting a block model. SDP-1 has a tendency to produce equal-sized blocks and is ideal for producing a form of network histogram approximating a nonparametric graphon model. Alternatively, it can be used for community detection. (This is experimental code, proceed with caution.)
The package uses fitting axes-aligned rectangles to a time series in order to find structural breaks. The algorithm enclose the time series in a number of axes-aligned rectangles and tries to minimize their area and number. As these are conflicting aims, the user has to specify a parameter alpha in [0.0,1.0]. Values close to 0 result in more breakpoints, values close to 1 in fewer. The left edges of the rectangles are the breakpoints. The package supplies two  methods, computeBreakPoints(series,alpha) which returns the indices of the break points and computeRectangles(series,alpha) which returns the rectangles. The algorithm is randomised; it uses a genetic algorithm. Therefore, the break point sequence found can be different in different executions of the method on the same data, especially when used on  longer series of some thousand observations. The algorithm uses a range-tree as background data structure which makes i very fast and suited to analyse series with millions of observations. A detailed description can be found in Paul Fischer, Astrid Hilbert, Fast detection  of structural breaks, Proceedings of Compstat 2014.
An implementation of Scalable Bayesian Rule Lists Algorithm.
Tools for interacting with U.S. Geological Survey ScienceBase
<https://www.sciencebase.gov> interfaces. ScienceBase is a data cataloging and
collaborative data management platform. Functions included for querying
ScienceBase, and creating and fetching datasets.
Simple Component Analysis (SCA) often provides much more
interpretable components than Principal Components (PCA) while still
representing much of the variability in the data.
Calculates graph theoretic scagnostics. Scagnostics
describe various measures of interest for pairs of variables,
based on their appearance on a scatterplot.  They are useful
tool for discovering interesting or unusual scatterplots from a
scatterplot matrix, without having to look at every individual
plot.
Provides the Scale class and corresponding functions, in order to facilitate data input for scale construction. Reverse items and alternative orders of administration are dealt with by the program. Computes reliability statistics, confirmatory, single factor loadings. It suggests item deletions and produces basic text output in English, for incorporation in reports. Returns list objects of all relevant functions from other packages (see Depends).
Graphical scales map data to aesthetics, and provide
methods for automatically determining breaks and labels
for axes and legends.
Algorithms for fitting scaled sparse linear regression and estimating precision matrices
Routines for generalized additive modelling under shape
constraints on the component functions of the linear predictor.
Models can contain multiple shape constrained (univariate
and/or bivariate) and unconstrained terms. The routines of gam()
in package 'mgcv' are used for setting up the model matrix,
printing and plotting the results.  Penalized likelihood
maximization based on Newton-Raphson method is used to fit a
model with multiple smoothing parameter selection by GCV or
UBRE/AIC.
Import, plot, and diagnose results from statistical
catch-at-age models, used in fisheries stock assessment.
This package computes the maximum likelihood estimator of the generalised additive and index regression with shape constraints. Each additive component function is assumed to obey one of the nine possible shape restrictions: linear, increasing, decreasing, convex, convex increasing, convex decreasing, concave, concave increasing, or concave decreasing.
scaRabee is a port of the Scarabee toolkit originally
written as a Matlab-based application. It provides a framework
for simulation and optimization of pharmacokinetic-pharmacodynamic
models at the individual and population level. It is built on top of the
neldermead package, which provides the direct search algorithm proposed
by Nelder and Mead for model optimization.
Creates 'D3' 'JavaScript' scatterplots from 'R' with interactive
features : panning, zooming, tooltips, etc.
Plots a three dimensional (3D) point cloud.
This package implements statistical methods for estimating and inferring the mean of functional data. The methods are based on simultaneous confidence bands and local polynomial fitting. They feature: bandwidth selection by plug-in and cross-validation, goodness-of-fit tests for parametric models, equality tests for two-sample problems, and plotting functions.
Uses the neural gas algorithm to construct
a scenario tree for use in multi-stage stochastic programming.
The primary input is a set of initial scenarios or realizations
of a disturbance. The scenario tree nodal structure must be
predefined using a scenario tree nodal partition matrix.
SCEPtER pipeline for estimating the stellar age, mass, and radius
given observational
effective temperature, [Fe/H], and astroseismic
parameters. The results are obtained adopting a maximum likelihood
technique over a grid of pre-computed stellar models.
SCEPtER pipeline for estimating the stellar age for double-lined detached binary systems. The observational constraints adopted in the recovery are the effective temperature, the metallicity [Fe/H], the mass, and the radius of the two stars. The results are obtained adopting a maximum likelihood technique over a grid of pre-computed stellar models.
The Fisher Scoring Algorithm is extended so as to combine Partial
Least Squares regression with Generalized Linear Model estimation in the
multivariate context.
Provides schema-on-read tools including a single function call (e.g., schemaOnRead('filename')) that reads text ('TXT'), comma separated value ('CSV'), raster image ('BMP', 'PNG', 'GIF', 'TIFF', and 'JPG'), R data ('RDS'), HDF5 ('H5'), NetCDF ('CS'), spreadsheet ('XLS', 'XLSX', 'ODS', and 'DIF'), Weka Attribute-Relation File Format ('ARFF'), Epi Info ('REC'), SPSS ('SAV'), Systat ('SYS'), and Stata ('DTA') files. It also recursively reads folders (e.g., schemaOnRead('folder')), returning a nested list of the contained elements.
Provides functions to extract citation data from Google
Scholar.  Convenience functions are also provided for comparing
multiple scholars and predicting future h-index values.
This package contains functions and datasets for math
taught in school. A main focus is set to prime-calculation
Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg.
This is a shape preserving spline which is guaranteed
to be monotonic and concave or convex if the data is monotonic
and concave or convex. It does not use any optimisation and is
therefore quick and smoothly converges to a fixed point in
economic dynamics problems including value function iteration.
It also automatically gives the first two derivatives of the
spline and options for determining behaviour when evaluated
outside the interpolation domain.
This package provides detailed functionality for working with the Schwartz 1997 two-factor commodity model. Essentially, it contains pricing formulas for futures and European options and the standard d/p/q/r functions for the distribution of the state variables and futures prices. In addition, a parameter estimation procedure is contained together with many utilities as filtering and plotting functionality. This package is accompanied by futures data of ten commodities.
Functions for generating Standardized Climate Indices (SCI).
SCI is a transformation of (smoothed) climate (or environmental)
time series that  removes seasonality and forces the data to
take values of the standard normal distribution. SCI was
originally developed for precipitation. In this case it is
known as the Standardized Precipitation Index (SPI).
An R interface to the SciDB array database (http://scidb.org).
Provide functions for analyzing elections and political behavior
data, including measures of political fragmentation, seat apportionment, and
small data visualization graphs.
It involves bibliometric indicators calculation from bibliometric data.It also deals pattern analysis using the text part of bibliometric data.The bibliometric data are obtained from mainly Web of Science and Scopus.
Sparse Column-wise Inverse Operator for estimating the inverse covariance matrix.  Note that this is a preliminary version accompanying the arXiv paper (arXiv:1203.3896) in 2012.   This version contains only the minimal set of functions for estimation and cross validation.
A collection of functions that creates graphs with error
bars for data collected from one-way or higher factorial
designs.
Functions to install SciViews additions to R, and more (various) tools
Provides functions to measure growth patterns and align
sampling spots in chronologically deposited materials. The package is
intended for the fields of sclerochronology, dendrochronology and geology.
An R package for single-case meta-analysis.
Given a matrix with results of different algorithms for different
problems, the package uses statistical tests and corrections to assess the
differences between algorithms.
Provides routines for scoring behavioral questionnaires. Includes scoring procedures for the 'International Physical Activity Questionnaire (IPAQ)' <http://www.ipaq.ki.se>. Compares physical functional performance to the age- and gender-specific normal ranges.
Estimate GGUM Person Parameters Using Pre-Calibrated Item Parameters and Binary or Graded Disagree-Agree Responses
A set of tools for quickly scoring models in data science and
machine learning. This toolset is written in C++ for blazing fast performance.
This package contains the functions necessary to run the SCORER 2.0 algorithm. SCORER 2.0 can be used to differentiate between parallel dimeric and trimeric coiled-coil sequence, which are the two most more frequent coiled-coil structures observed naturally. As such, SCORER 2.0 is particularly useful for researchers looking to characterize novel coiled-coil sequences. It may also be used to assist in the structural characterization of synthetic coiled-coil sequences. Also included in this package are functions that allows the user to retrain the SCORER 2.0 algorithm using user-defined training data.
Evaluating probabilistic forecasts via proper scoring rules.  scoring implements the beta, power, and pseudospherical families of proper scoring rules, along with ordered versions of the latter two families.  Included among these families are popular rules like the Brier (quadratic) score, logarithmic score, and spherical score.  For two-alternative forecasts, also includes functionality for plotting scores that one would obtain under specific scoring rules.
Dictionary-like reference for computing scoring rules in a wide
range of situations. Covers both parametric forecast distributions (such as
mixtures of Gaussians) and distributions generated via simulation.
Division of an ANOVA experiment treatment means into
homogeneous distinct groups using the clustering method of
Scott & Knott
An enhancement of the Scott-Knott test (which cluster distributions
into statistically distinct ranks) that takes effect size into consideration.
Implements the Scout method for regression, described in "Covariance-regularized regression and classification for high-dimensional problems", by Witten and Tibshirani (2008),  Journal of the Royal Statistical Society, Series B 71(3): 615-636.
The package implements different inventory models, the
bullwhip effect and other supply chain performance variables.
Given a word will produce that word's scrabble score. Unlike many naive implementations this package takes into consideration the distribution of letter in scrabble. So a word like 'zzz' will be scored '10' rather than '30'.
Tools for Scraping Data from Web-Based Documents
Routines for a collection of screen-and-clean type
variable selection procedures, including UPS and GS.
Tools for the analysis of high-dimensional data developed/implemented
at the group "Statistical Complexity Reduction In Molecular Epidemiology" (SCRIME).
Main focus is on SNP data. But most of the functions can also be applied to other
types of categorical data.
Support for using .Rt (transcript) tests
in the tests directory of a package.  Provides more
convenience and features than the standard .R/.Rout.save
tests.  Tests can be run under R CMD check and also
interactively.  Provides source.pkg() for quickly loading
code, DLLs, and data from a package for use in an
edit/compile/test development cycle.
A coalescent simulator that allows the rapid simulation of
biological sequences under neutral models of evolution. Different to
other coalescent based simulations, it has an optional approximation
parameter that allows for high accuracy while maintaining a linear run time
cost for long sequences. It is optimized for simulating massive data sets as
produced by Next-Generation Sequencing technologies for up to several thousand
sequences.
A package for designing single-case phase, alternation and multiple-baseline experiments, as well as for conducting randomization tests on data gathered by means of such designs.
Clean biological occurrence records. Includes functionality
for cleaning based on various aspects of spatial coordinates,
unlikely values due to political 'centroids', coordinates based on
where collections of specimens are held, and more.
scrypt is an R package for working with scrypt. Scrypt is a
password-based key derivation function created by Colin Percival. The
algorithm was specifically designed to make it costly to perform
large-scale custom hardware attacks by requiring large amounts of memory.
Solves convex cone programs via operator splitting. Can solve:
linear programs (LPs), second-order cone programs (SOCPs), semidefinite programs
(SDPs), exponential cone programs (ECPs), and power cone programs (PCPs), or
problems with any combination of those cones.    SCS uses AMD (a set of routines for permuting sparse matrices prior to factorization) and LDL (a sparse LDL' factorization and solve package) from 'SuiteSparse' (<http://www.suitesparse.com>).
Code for describing and manipulating scuba diving profiles
(depth-time curves) and decompression models,
for calculating the predictions of decompression models,
for calculating maximum no-decompression time and decompression tables,
and for performing mixed gas calculations.
A package to make graphical representations of single case data and to transform graphical displays back to raw data. The package also includes tools for visually analyzing single-case data, by displaying central location, variability and trend.
Provides an efficient framework for
high-dimensional linear and diagonal discriminant analysis with
variable selection.  The classifier is trained using James-Stein-type
shrinkage estimators and predictor variables are ranked using
correlation-adjusted t-scores (CAT scores).  Variable selection error
is controlled using false non-discovery rates or higher criticism.
Functions and Datasets from Lohr, S. (1999), Sampling:
Design and Analysis, Duxbury.
Test the global null in linear models using marginal approach.
Data from statistical agencies and other institutions are mostly
confidential. This package can be used for the generation of anonymized
(micro)data, i.e. for the creation of public- and scientific-use files. In
addition, various risk estimation methods are included. Note that the package
'sdcMicroGUI' includes a graphical user interface for various methods in this
package.
A point and click graphical user interface based on top of the
'sdcMicro' package to create anonymized data set. The graphical user
interface provides full reproducibility of any result via the script menu
in the GUI.
Methods for statistical disclosure control in
tabular data such as primary and secondary cell suppression are covered in
this package.
Classes and methods to calculate and evaluate target matrices for
statistical disclosure control.
Allows for  computing (and by default plotting) different types of serial dependence diagrams.
Compares the evolution of an original network X to an augmented network Y by counting the number of Shortcuts, Detours, Dead Ends (SDDE), equal paths and disconnected nodes.
The semidiscrete decomposition (SDD) approximates a matrix
as a weighted sum of outer products formed by vectors with
entries constrained to be in the set {-1, 0, 1}.
Companion package to the book Simulation and Inference for
Stochastic Differential Equations With R Examples, ISBN
978-0-387-75838-1, Springer, NY.
Performs two tests to evaluate if the
experiments are associated and returns a list of interesting
features common to all the experiments.
Implementation of evolutionary fuzzy systems for the data mining task called
"subgroup discovery". It also provide a Shiny App
for make the analysis easier. The algorithms works with data sets provided in
KEEL, ARFF and CSV format and also with data.frame objects.
An extensible R framework for developing species distribution
models using individual and community-based approaches, generate ensembles of
models, evaluate the models, and predict species potential distributions in
space and time.
Functions provided by this pedagogic package allow to compute models with two popular machine learning approaches, BRT (Boosted Regression Trees) and MaxEnt (Maximum Entropy) applied on sets of marine biological and environmental data. They include the possibility of managing the main parameters for the construction of the models. Classic tools to evaluate model performance are provided (Area Under the Curve, omission rate and confusion matrix, map standard deviation) and are completed with tools to perform null models. The biological dataset includes original occurrences of two species of the class Echinoidea (sea urchins) present on the Kerguelen Plateau and that show contrasted ecological niches. The environmental dataset includes the corresponding statistics for 15 abiotic and biotic descriptors summarized for the Kerguelen Plateau and for different periods in a raster format. The package can be used for practicals to teach and learn the basics of species distribution modelling. Maps of potential distribution can be produced based on the example data included in the package, which brings prior observations of the influence of spatial and temporal heterogeneities on modelling performances. The user can also provide his own datasets to use the modelling functions.
This packages provides a set of tools for post processing the
outcomes of species distribution modeling exercises. It includes novel
methods for comparing models and tracking changes in distributions through
time. It further includes methods for visualizing outcomes, selecting
thresholds, calculating measures of accuracy and landscape fragmentation
statistics, etc.. This package was made possible in part by financial
support from the Australian Research Council & ARC Research Network for
Earth System Science.
A software package help user to create virtual species for species distribution modelling. It includes
several methods to help user to create virtual species distribution map.
Those maps can be used for Species Distribution Modelling (SDM) study. SDM use
environmental data for sites of occurrence of a species to predict all the sites
where the environmental conditions are suitable for the species to persist, and
may be expected to occur.
Fitting discrete Bayesian networks using soft-discretized data.  Soft-discretization is based on mixture of normal distributions.  Also implemented is a supervised Bayesian network learning employing Kullback-Leibler divergence.
Utility functions for scale-dependent and alternative hyperpriors.
The main purpose of this package is to provide saddlepoint
approximations to some measures of risk, based on the compound Poisson risk
process that is perturbed by a Brownian motion.  Various approximation
methods for the probability of ruin are also included.  Furthermore, exact
values of both the risk measures as well as the probability of ruin are
available if the individual claims follow a hypo-exponential distribution
(i. e., if it can be represented as a sum of independent exponentially
distributed random variables with different rate parameters).
Routines for drawing samples, focusing on spatially balanced algorithms. Draws Halton Lattice (HAL), Balanced Acceptance Samples (BAS), Generalized Random Tesselation Stratified (GRTS), Simple Systematic Samples (SSS) and Simple Random Samples (SRS) from point, line, and polygon resources.  Frames are 'SpatialPoints', 'SpatialLines', or 'SpatialPolygons' objects from package 'sp'.
Implements algorithms to help with scenario discovery - currently only modified version of the the Patient Rule Induction Method.
Formulates a sparse distance weighted discrimination (SDWD) for high-dimensional classification and implements a very fast algorithm for computing its solution path with the L1, the elastic-net, and the adaptive elastic-net penalties.
Calculates parameters of the seawater carbonate system and assists
the design of ocean acidification perturbation experiments.
Standard error adjusted adaptive lasso (SEA-lasso) is a version of the adaptive lasso, which incorporates OLS standard error to the L1 penalty weight. This method is intended for variable selection under linear regression settings (n > p). This new weight assignment strategy is especially useful when the collinearity of the design matrix is a concern.
Provides functionality for searching / subsetting and slicing named
objects using 'stringr/i'-style modifiers by case (in)sensitivity,
regular expressions or fixed expressions; searches uses the standard '['
operator and allows specification of default search behavior to either the
search target (named object) and/or the search pattern.
Provides an interface with the Google Search Console,
formally called Google Webmaster Tools.
This package provides an implementation of the QuadTree
data structure. It uses this to implement fast k-Nearest
Neighbor and Rectangular range lookups in 2 dimenions. The
primary target is high performance interactive graphics.
Capable of deriving seasonal statistics, such as "normals", and
analysis of seasonal data, such as departures. This package also has
graphics capabilities for representing seasonal data, including boxplots for
seasonal parameters, and bars for summed normals. There are many specific
functions related to climatology, including precipitation normals,
temperature normals, cumulative precipitation departures and precipitation
interarrivals. However, this package is designed to represent any
time-varying parameter with a discernible seasonal signal, such as found
in hydrology and ecology.
This package conducts Score Equity Assessment (SEA; Dorans, 2004) by calculating and plotting multiple SEA indices as introduced by a variety of authors and summarized by Huggins and Penfield (2012).
Routines for the seasonal analysis of health data,
including regression models, time-stratified case-crossover,
plotting functions and residual checks. Thanks to Yuming Guo
for checking the case-crossover code.
Easy-to-use interface to X-13-ARIMA-SEATS, the
seasonal adjustment software by the US Census Bureau. It offers full
access to almost all options and outputs of X-13, including X-11 and SEATS,
automatic ARIMA model search, outlier detection and support for user
defined holiday variables, such as Chinese New Year or Indian Diwali. It
also includes a Shiny-based graphical user interface. Seasonal uses the
X-13 binaries from the 'x13binary' package.
A model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables
Displays state-event charts, for graphical presentation of longitudinal data.
Density, distribution function, quantile function, random
generation and survival function for the Secant Kumaraswamy Weibull Distribution
as defined by SOUZA, L. New Trigonometric Class of Probabilistic Distributions.
219 p. Thesis (Doctorate in Biometry and Applied Statistics) - Department of
Statistics and Information, Federal Rural University of Pernambuco, Recife,
Pernambuco, 2015 (available at <http://www.openthesis.org/documents/New-trigonometric-classes-probabilistic-distributions-602633.html>) and BRITO, C. C. R. Method Distributions generator and
Probability Distributions Classes. 241 p. Thesis (Doctorate in Biometry and
Applied Statistics) - Department of Statistics and Information, Federal Rural
University of Pernambuco, Recife, Pernambuco, 2014 (available upon request).
SECP package provides functionality for estimating
parameters of site clusters on 2D & 3D square lattice with
various lattice sizes, relative fractions of accessible sites
(occupation probability), iso- & anisotropy, von Neumann &
Moore (1,d)-neighborhoods
Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.
Tools are provided for designing spatially explicit capture-recapture studies of animal populations. This is primarily a simulation manager for package 'secr'.
Tools for spatially explicit capture-recapture analysis of animal populations in linear habitats, extending package 'secr'
Provides a wrapper to access data from the SeeClickFix
web API for R. SeeClickFix is a central platform employed by many cities
that allows citizens to request their city's services. This package
creates several functions to work with all the built-in calls to the
SeeClickFix API. Allows users to download service request data from
numerous locations in easy-to-use dataframe format manipulable in
standard R functions.
Suite of functions for the simulation, visualisation and analysis of bacterial evolution within- and between-host.
Supports the text book "Data Analysis and Statistics for
Geography, Environmental Science, and Engineering"
Supports Simulation of Ecological and Environmental Models
Creates SEER (Surveillance, Epidemiology and End Results) and A-bomb data binaries
from ASCII sources and provides tools for estimating SEER second cancer risks.
Functions for analysing, manipulating, displaying, editing and synthesizing time waves (particularly sound).  This package processes time analysis (oscillograms and envelopes), spectral content, resonance quality factor, entropy, cross correlation and autocorrelation, zero-crossing, dominant frequency, analytic signal, frequency coherence, 2D and 3D spectrograms and many other analyses.
A package that provides functions for measuring spatial
segregation. The methods implemented in this package include
White's P index (1983), Morrill's D(adj) (1991), Wong's D(w)
and D(s) (1993), and Reardon and O'Sullivan's set of spatial
segregation measures (2004).
Performs correlation matrix segmentation and applies a test
procedure to detect highly correlated regions in gene expression.
Contains functions that help to determine event
boundaries in event segmentation experiments by bootstrapping a critical
segmentation magnitude under the null hypothesis that all key presses were
randomly distributed across the experiment. Segmentation magnitude is
defined as the sum of Gaussians centered at the times of the segmentation
key presses performed by the participants. Within a participant, the maximum
of the overlaid Gaussians is used to prevent an excessive influence of a
single participant on the overall outcome (e.g. if a participant is pressing
the key multiple times in succession). Further functions are included, such
as plotting the results.
Given a regression model, segmented `updates' the model by adding one or more segmented (i.e., piecewise-linear) relationships. Several variables with multiple breakpoints are allowed.
Performs a fast exact segmentation on data and allows for use of various cost functions.
A model coupling polygon and point processes for assessing
risk due to contaminant sources and their impact on exposed individuals.
An implementation of self-exciting point process model for information cascades, which occurs when many people engage in the same acts after observing the actions of others (e.g. post resharings on Facebook or Twitter). It provides functions to estimate the infectiousness of an information cascade and predict its popularity given the observed history. See http://snap.stanford.edu/seismic/ for more information and datasets.
Fast versions of seismic analysis functions that 'roll' over a
vector of values. See the RcppRoll package for alternative
versions of basic statistical functions such as rolling mean,
median, etc.
Set of functions that access information about deputies and votings
in Polish diet from webpage <http://www.sejm.gov.pl/>. The package was developed
as a result of an internship in MI2 Group - <http://mi2.mini.pw.edu.pl/>,
Faculty of Mathematics and Information Science, Warsaw University of Technology.
Sejong(http://www.sejong.or.kr/) corpus and
Hannanum(http://semanticweb.kaist.ac.kr/home/index.php/HanNanum)
dictionaries for KoNLP
This package implements a novel method for fitting a
bounded probability distribution to quantiles (for example
stated by an expert), see Bornkamp and Ickstadt (2009) for
details.  For this purpose B-splines are used, and the density
is obtained by penalized least squares based on a Brier entropy
penalty.  The package provides methods for fitting the
distribution as well as methods for evaluating the underlying
density and cdf. In addition methods for plotting the
distribution, drawing random numbers and calculating quantiles
of the obtained distribution are provided.
A collection of functions for correcting biased estimates under
selection (range restriction).
Multi-stage selection is practiced in numerous fields of life and social sciences and particularly in breeding. A special characteristic of multi-stage selection is that candidates are evaluated in successive stages with increasing intensity and effort, and only a fraction of the superior candidates is selected and promoted to the next stage. For the optimum design of such selection programs, the selection gain plays a crucial role. It can be calculated by integration of a truncated multivariate normal (MVN) distribution. While mathematical formulas for calculating the selection gain and the variance among selected candidates were developed long time ago, solutions for numerical calculation were not available. This package can also be used for optimizing multi-stage selection programs for a given total budget and different costs of evaluating the candidates in each stage.
New tools for post-selection inference, for use
with forward stepwise regression, least angle regression, the
lasso, and the many means problem. The lasso function implements  Gaussian,  logistic and Cox survival models.
Publication bias, the fact that studies identified for inclusion in a meta analysis do not represent all studies on the topic of interest, is commonly recognized as a threat to the validity of the results of a meta analysis. One way to explicitly model publication bias is via selection models or weighted probability distributions. In this package we provide implementations of several parametric and nonparametric weight functions. The novelty in Rufibach (2011) is the proposal of a non-increasing variant of the nonparametric weight function of Dear & Begg (1992). The new approach potentially offers more insight in the selection process than other methods, but is more flexible than parametric approaches. To maximize the log-likelihood function proposed by Dear & Begg (1992) under a monotonicity constraint we use a differential evolution algorithm proposed by Ardia et al (2010a, b) and implemented in Mullen et al (2009). In addition, we offer a method to compute a confidence interval for the overall effect size theta, adjusted for selection bias as well as a function that computes the simulation-based p-value to assess the null hypothesis of no selection as described in Rufibach (2011, Section 6).
Translates a CSS3 selector into an equivalent XPath
expression. This allows us to use CSS selectors when working with
the XML package as it can only evaluate XPath expressions. Also
provided are convenience functions useful for using CSS selectors on
XML nodes. This package is a port of the Python package "cssselect"
(http://packages.python.org/cssselect/).
Fit and selects point pattern models based on minimum contrast, AIC and and goodness of fit.
Detection of outliers and influential errors using a latent variable model.
Functions using Cohen's effect sizes (Cohen, Jacob. Statistical power analysis for the behavioral sciences. Academic press, 2013) are provided for reliable feature selection in biology data analysis.  In addition to Cohen's effect sizes, p-values are calculated and adjusted from quasi-Poisson GLM, negative binomial GLM and Normal distribution ANOVA.  Significant features (genes, RNAs or proteins) are selected by adjusted p-value and minimum Cohen's effect sizes, calculated to keep certain level of statistical power of biology data analysis given p-value threshold and sample size.
A probability tree allows to compute probabilities of
complex events, such as genotype probabilities in intermediate generations of inbreeding
through recurrent self-fertilization (selfing). This package implements functionality to compute
probability trees for two- and three-marker genotypes in the F2 to F7 selfing
generations. The conditional probabilities are derived automatically
and in symbolic form. The package also provides functionality to
extract and evaluate the relevant probabilities.
Performs a regularization approach to variable selection in the
model-based clustering and classification frameworks.
First, the variables are arranged in order with a lasso-like procedure.
Second, the method of Maugis, Celeux, and Martin-Magniette (2009, 2011)
is adapted to define the role of variables in the two frameworks.
Functions for fitting general linear structural
equation models (with observed and latent variables) using the RAM approach,
and for fitting structural equations in observed-variable models by two-stage least squares.
Outlier and leverage diagnostics for SEM.
Fits a multidimensional scaling (MDS) model for three-way data. It integrates concepts from structural equation models (SEM) by assuming an underlying, latent dissimilarity matrix. The methods uses an alternating estimation procedure in which the unknown symmetric dissimilarity matrix is estimated in a SEM framework while the objects are represented in a low-dimensional space. As a special case it can also handle asymmetric input dissimilarities.
This is an add-on package which provides fourteen
goodness-of-fit indexes for structural equation models using
'sem' package.
Package semiArtificial contains methods to generate and evaluate semi-artificial data sets.
Based on a given data set different methods learn data properties using machine learning algorithms and
generate new data with the same properties.
The package currently includes the following data generator:
-a RBF network based generator using rbfDDA from RSNNS package,
-a Random Forest based generator for both classification and regression problems
-a density forest based generator for unsupervised data
Data evaluation support tools include:
-single attribute based statistical evaluation: mean, median, standard deviation, skewness, kurtosis, medcouple, L/RMC, KS test, Hellinger distance
-evaluation based on clustering using Adjusted Rand Index (ARI) and FM
-evaluation based on classification performance with various learning models, eg, random forests.
Parametric and semi-parametric analyses of semi-competing risks/univariate survival data.
Provides routines to check identifiability or non-identifiability
of linear structural equation models as described in Drton, Foygel &
Sullivant (Ann. Statist., 2011) and Foygel, Draisma & Drton (Ann. Statist.,
2012). The routines are based on the graphical representation of
structural equation models by a path diagram/mixed graph.
Functions for fitting multi-state semi-Markov models to longitudinal data. A parametric maximum likelihood estimation method adapted to deal with Exponential, Weibull and Exponentiated Weibull distributions is considered. Right-censoring can be taken into account and both constant and time-varying covariates can be included using a Cox proportional model.
Functions for semiparametric regression analysis, to
complement the book: Ruppert, D., Wand, M.P. and Carroll, R.J.
(2003). Semiparametric Regression. Cambridge University Press.
Routines for fitting several classes of copula regression models, with several types of covariate effects, in the presence of associated error equations, endogeneity, non-random sample selection or partial observability.
Routine for fitting continuous or discrete response copula sample selection models with semi-parametric predictors, including linear and nonlinear effects.
Functions to compute Gaussian and p-Gaussian kernels,
include supervision in these kernels, and perform kernel PCA
projections.
Conduct tests of difference in fit for mean and covariance
structure models as in structural equation modeling (SEM)
Path diagrams and visual analysis of various SEM packages' output
Fits structural equation models using partial least
squares (PLS). The PLS approach is referred to as
'soft-modeling' technique requiring no distributional
assumptions on the observed data.
Semiparametric Estimation of Stochastic Frontier Models following a two step procedure: in the first step semiparametric or nonparametric regression techniques are used to relax parametric restrictions of the functional form representing technology and in the second step variance parameters are obtained by pseudolikelihood estimators or by method of moments.
Provides useful tools for structural equation modeling packages.
Package contains a simple SMTP client which provides a
portable solution for sending email, including attachment, from
within R.
An implementation of sensitivity analysis in phylogenetic regression models,
for both linear and logistic phylogenetic regressions. The package is an umbrella
of statistical and graphical methods that estimate and report different types of
uncertainty in PGLS models:
(i) Sampling uncertainty (sample size; influential species and clades).
(ii) Phylogenetic uncertainty.
(iii) Data uncertainty (intraspecific variation and measurement error).
A collection of functions for factor screening, global sensitivity analysis and reliability sensitivity analysis. Most of the functions have to be applied on model with scalar output, but several functions support multi-dimensional outputs.
Performs exact or approximate adaptive or nonadaptive Cochran-Mantel-Haenszel-Birch tests and sensitivity analyses for one or two 2x2xk tables in observational studies.
This package performs sensitivity analysis for case-control studies in which some cases may meet a more narrow definition of being a case compared to other cases which only meet a broad definition.  The sensitivity analyses are described in Small, Cheng, Halloran and Rosenbaum (2013, "Case Definition and Sensitivity Analysis", Journal of the American Statistical Association, 1457-1468).  The functions sens.analysis.mh and sens.analysis.aberrant.rank provide sensitivity analyses based on the Mantel-Haenszel test statistic and aberrant rank test statistic as described in Rosenbaum (1991, "Sensitivity Analysis for Matched Case Control Studies", Biometrics); see also Section 1 of Small et al.  The function adaptive.case.test provides adaptive inferences as described in Section 5 of Small et al.  The function adaptive.noether.brown provides a sensitivity analysis for a matched cohort study based on an adaptive test.  The other functions in the package are internal functions.
Sensitivity analysis in observational studies, including evidence factors and amplification, using the permutation distribution of Huber-Maritz M-statistics, including the permutational t-test.
Sensitivity analysis analysis in matched observational studies with multiple controls using weighted M-statistics to increase design sensitivity.
This package provides functions to perform principal stratification sensitivity analyses on datasets.
Functions that facilitate analysis of
Sensory as well as Consumer data within a mixed effects model
framework. The so-called mixed assessor models,
that correct for the scaling effect are implemented.
The generation of the d-tilde plots forms part of the package.
The shiny application provides GUI for the functionalities.
Contains the function CUUimpute() which performs model-based clustering and imputation simultaneously.
Provides methods for sensory discrimination methods;
duotrio, tetrad, triangle, 2-AFC, 3-AFC, A-not A, same-different,
2-AC and degree-of-difference.
This enables the calculation of d-primes, standard errors of
d-primes, sample size and power computations, and
comparisons of different d-primes. Methods for profile likelihood
confidence intervals and plotting are included.
Collection of datasets from Sen & Srivastava: "Regression
Analysis, Theory, Methods and Applications", Springer.  Sources
for individual data files are more fully documented in the
book.
Provides access and analytic functions for Sensus data.
Calculate text polarity sentiment at the sentence level
and optionally aggregate by rows or grouping variable(s).
It combines maximum likelihood estimation of the parameters
of matrix and 3rd-order tensor normal distributions with unstructured
factor variance-covariance matrices, two procedures, and unbiased
modified likelihood ratio testing of simple and double separability
for variance-covariance structures, two procedures.
Functions to generate separation plots for evaluation of
model fit.
Potential randomization schemes are prospectively evaluated when
units are assigned to treatment arms upon entry into the experiment. The schemes
are evaluated for balance on covariates and on predictability (i.e., how well
could a site worker guess the treatment of the next unit enrolled).
This is a method for DNA Copy Number Profiling using
Next-Generation Sequencing. It has new model and test
statistics based on non-homogeneous Poisson Processes with
change point models. It uses an adaptation of Circular Binary
Segmentation. Also included are methods for point-wise Bayesian
Confidence Interval and model selection method for the
change-point model. A case and a control sample reads (normal
and tumor) are required.
A modification of the preventive vaccine efficacy trial design of Gilbert, Grove et al. (2011, Statistical Communications in Infectious Diseases) is implemented, with application generally to individual-randomized clinical trials with multiple active treatment groups and a shared control group, and a study endpoint that is a time-to-event endpoint subject to right-censoring. The design accounts for the issues that the efficacy of the treatment/vaccine groups may take time to accrue while the multiple treatment administrations/vaccinations are given; there is interest in assessing the durability of treatment efficacy over time; and group sequential monitoring of each treatment group for potential harm, non-efficacy/efficacy futility, and high efficacy is warranted. The design divides the trial into two stages of time periods, where each treatment is first evaluated for efficacy in the first stage of follow-up, and, if and only if it shows significant treatment efficacy in stage one, it is evaluated for longer-term durability of efficacy in stage two. The package produces plots and tables describing operating characteristics of a specified design including an unconditional power for intention-to-treat and per-protocol/as-treated analyses; trial duration; probabilities of the different possible trial monitoring outcomes (e.g., stopping early for non-efficacy); unconditional power for comparing treatment efficacies; and distributions of numbers of endpoint events occurring after the treatments/vaccinations are given, useful as input parameters for the design of studies of the association of biomarkers with a clinical outcome (surrogate endpoint problem). The code can be used for a single active treatment versus control design and for a single-stage design.
Provides user friendly methods for the identification of sequence patterns that are statistically significantly associated with a property of the sequence. For instance, SeqFeatR allows to identify viral immune escape mutations for hosts of given HLA types. The underlying statistical method is Fisher's exact test, with appropriate corrections for multiple testing, or Bayes. Patterns may be point mutations or n-tuple of mutations. SeqFeatR offers several ways to visualize the results of the statistical analyses.
The SeqGrapheR package provide interactive GUI for visualization of DNA sequence clusters. Details and principles of usage are described in user manual and (2010 BMC Bioinformatics 11:378). For full functionality installed NCBI blast is required.
Designed for fitting hidden (latent)
Markov models and mixture hidden Markov models for social
sequence data and other categorical time series. Also some more restricted
versions of these type of models are available: Markov models, mixture
Markov models, and latent class models. The package supports models for one or
multiple subjects with one or multiple parallel sequences (channels). External
covariates can be added to explain cluster membership in mixture models. The
package provides functions for evaluating and comparing models, as well as
functions for easy plotting of multichannel sequence data and hidden Markov
models. Models are estimated using maximum likelihood via the EM algorithm and/or
direct numerical maximization with analytical gradients.
All main algorithms are written in C++ with support for parallel computation.
Exploratory data analysis and data visualization
for biological sequence (DNA and protein) data. Includes also
utilities for sequence data management under the ACNUC system.
A network module-based generalized linear model for differential expression analysis with the count-based sequence data from RNA-Seq.
Computes necessary information to meta analyze region-based
tests for rare genetic variants (e.g. SKAT, T1) in individual studies, and
performs meta analysis.
Integrate sequencing data (Variant call format, e.g. VCF or BCF) or meta-analysis results in R.
A program that computes the probability of crossing
sequential boundaries in a clinical trial. It implements the
Armitage-McPherson and Rowe Algorithm using the method
described in Schoenfeld D. (2001)" A simple Algorithm for
Designing Group Sequential Clinical Trials" Biometrics 27: pp,
972-974
User inputs a range of values r1 and r2, as well as a
number of columns v, in the function sq.pe(r1,r2,v). The
returned statement is a permutation matrix.
This package includes functions for handling DNA
sequences, especially simulated RFLP and TRFLP pattern based on
selected restriction enzyme and DNA sequences.
Sequential triangular test for the arithmetic mean in one- and two-
samples, proportions in one- and two-samples, and the Pearson's correlation
coefficient.
Provides: 1) By Giving UniProtKB, the Protein Sequence will be returned from UniProt database. 2)By Giving UniProtKB, the Nucleotide Sequence will be returned from EBI database. 3) Amino acid Composition is calculated by four different methods: a) Twenty-two independent categories are considered, with one amino acid for each category. B) Five categories (Nonpolar Aliphatic, Nonpolar Aromatic, Polar Uncharged, Polar Positively Charged, Polar Negatively Charged) are considered according to the standard chemical structures of amino acids. c) Six categories (Nonpolar Aliphatic, Nonpolar Aromatic, Polar Uncharged, Polar Positively Charged, Polar Negatively Charged, Special cases) are considered which Cysteine, Selenocysteine, Glycine and Proline are placed in Special cases group. d)Eight categories are clustered via k-means algorithm on Physicochemical index of amino acids. 4) GC Content: Percentage of nucleotide g and c in sequence. 5) Codon usage: Frequency of occurrence of synonymous codons. 6) Stacking Energy: The NN model for nucleic acids assumes that the stability of a given base pair depends on the identity and orientation of neighboring base pairs. Stacking Energy = DeltaG(total) = Sigma (n(i)*DeltaG(i)) + DeltaG(init) + DeltaG(end) + DeltaG(sym), which DeltaG for i, init and end is obtained by Unified NN free energy parameter. Symmetry of self-complementary duplexes is also included by DeltaG(sym) equals to +0.43 (kcal/mol) if the duplex is self-complementary and zero if it is non-self-complementary. 7) Complement of desired nucleotide sequence. 8) Reverse of desired nucleotide sequence. 9) Reverse-Complement of desired nucleotide sequence. 10) Protein, Gene and Organism of desired UniProt ID. 11) Converting nucleotide sequence to protein sequence. 12) Getting Localization From Gene Ontology Cellular Component inside Uniprot. 13) All related codons of desired amino acid.
Educational package used in R courses to illustrate
object-oriented programming and package
development. Using biological sequences (DNA and RNA) as
a working example.
Functions to calculate exact critical values, statistical power, expected time to				signal and required  sample sizes for  performing exact sequential  analysis. All these				calculations can be done for either Poisson or binomial data, for continuous  or group				sequential analyses, and for different types of rejection boundaries.  In case  of group				sequential  analyses, the group  sizes do not  have to be specified in advance and the				alpha spending can be arbitrarily settled.
Tools to analyze genomic sequencing data from
paired normal-tumor samples, including cellularity and ploidy estimation; mutation
and copy number (allele-specific and total copy number) detection, quantification
and visualization.
Provides functionality for the use of the internal hardware for
RS232/RS422/RS485 and any other virtual serial interfaces of the
computer.
Infrastructure for seriation with an implementation of several
seriation/sequencing techniques to reorder matrices, dissimilarity
matrices, and dendrograms. Also provides (optimally) reordered heatmaps,
color images and clustering visualizations like dissimilarity plots, and
visual assessment of cluster tendency plots (VAT and iVAT).
Translates antibody levels measured in a (cross-sectional)
population sample into an estimate of the frequency with which
seroconversions (infections) occur in the sampled population.
Start an HTTP server in R to serve static files, or dynamic
documents that can be converted to HTML files (e.g., R Markdown) under a
given directory.
Structural equation modeling is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with inter-correlated dependent and independent variables. Here we implement a simple method for spatially explicit structural equation modeling based on the analysis of variance co-variance matrices calculated across a range of lag distances. This method provides readily interpreted plots of the change in path coefficients across scale.
Utility functions for interacting with R processes from
external programs. This package includes functions to save and
restore session information (including loaded packages, and
attached data objects), as well as functions to evaluate
strings containing R commands and return the printed results or
an execution transcript.
This initiated as a package companion to the book by C. Q.
Schneider and C. Wagemann "Set-Theoretic Methods for the Social
Sciences", Cambridge University Press. It grew to include functions
for performing set-theoretic multi-method research, QCA for clustered
data, theory evaluation, and Enhanced Standard Analysis. Additionally
it includes data to replicate the examples in the book and in the online
appendix.
Tests gene expression data from a biological pathway for biologically meaningful differences in the eigenstructure between two classes.  Specifically, it tests the null hypothesis that the two classes' leading eigenvalues and sums of eigenvalues are equal.  A pathway's leading eigenvalue arguably represents the total variability due to variability in pathway activity, while the sum of all its eigenvalues represents the variability due to pathway activity and to other, unregulated causes. Implementation of the method described in Danaher (2015), "Covariance-based analyses of biological pathways".
Implements an algorithm to conduct advanced
gene set enrichment analysis on the results of genomics experiments.
SetRNG provides utilities to help set and record the setting of
the seed and the uniform and normal generators used when a random
experiment is run. The utilities can be used in other functions
that do random experiments to simplify recording and/or setting all the
necessary information for reproducibility.
See the vignette and reference manual for examples.
Data structures and basic operations for ordinary sets,
generalizations such as fuzzy sets, multisets, and
fuzzy multisets, customizable sets, and intervals.
Mutators to set attributes of variables, that work well in a pipe
(much like stats::setNames()).
Provides option settings management that goes
beyond R's default 'options' function. With this package, users can define
their own option settings manager holding option names, default values and
(if so desired) ranges or sets of allowed option values that will be
automatically checked. Settings can then be retrieved, altered and reset
to defaults with ease. For R programmers and package developers it offers
cloning and merging functionality which allows for conveniently defining
global and local options, possibly in a multilevel options hierarchy. See
the package vignette for some examples concerning functions, S4 classes,
and reference classes. There are convenience functions to reset par()
and options() to their 'factory defaults'.
Automatically sets the value of options("width") when the
terminal emulator is resized. The functions of this package only work if R
is compiled for Linux systems and it is running interactively in a terminal
emulator.
This package contains functions for calculating severity
and generating severity curves. Specifically, the simple case
of the one-parameter Normal distribution (i.e., with known
variance) is considered.
This package combines several sighting based estimators of historical extinction, allowing them to be run simultaneously or individually. Code for this package was contributed by Ben Collen, Gene Hunt and Tracy Rout. Additional code was taken from McPherson & Myers (2009).
Stochastic Frontier Analysis
introduced by Aigner, Lovell and Schmidt (1976)
and Battese and Coelli (1992, 1995).
The straightforward filtering index (SFINX) identifies true positive
protein interactions in a fast, user-friendly, and highly accurate way.
It is not only useful for the filtering of affinity purification -
mass spectrometry (AP-MS) data, but also for similar types of data
resulting from other co-complex interactomics technologies, such as TAP-MS,
Virotrap and BioID. SFINX can also be used via the website interface at
<http://sfinx.ugent.be>.
Useful utilities ['goodies'] from Seminar fuer Statistik ETH
Zurich, quite a few related to graphics; many ported from S-plus times.
This package contains a series of tools for analyzing Systems Factorial Technology data.  This includes functions for plotting and statistically testing capacity coefficient functions and survivor interaction contrast functions.
Graph based clustering summaries for spatial point patterns. Includes Connectivity function,
Cumulative connectivity function and clustering function, plus the triangle/triplet intensity function T.
A fast and flexible set of tools for large scale estimation. It
features many stochastic gradient methods, built-in models, visualization
tools, automated hyperparameter tuning, model checking, interval estimation,
and convergence diagnostics.
An Object-oriented Framework for Geostatistical Modeling in S+
containing functions for variogram estimation, variogram fitting and kriging
as well as some plot functions. Written entirely in S, therefore works only
for small data sets in acceptable computing time.
Fit a regularized generalized linear model via penalized
maximum likelihood.  The model is fit for a path of values of
the penalty parameter. Fits linear, logistic and Cox models.
RCON(V, E) models (Højsgaard, et al., 2008) are a kind of restriction of the Gaussian Graphical Models defined by a set of equality constraints on the entries of the concentration matrix. 'sglasso' package implements the structured graphical lasso (sglasso) estimator proposed in Abbruzzo et al. (2014) for the weighted l1-penalized RCON(V, E) model. Two cyclic coordinate algorithms are implemented to compute the sglasso estimator, i.e. a cyclic coordinate minimization (CCM) and a cyclic coordinate descent (CCD) algorithm.
Fast generic solver for sparse group lasso optimization problems. The loss (objective) function must be defined in a C++ module. Use of multiple processors for cross validation and subsampling is supported through OpenMP. The optimization problem is solved using a coordinate gradient descent algorithm. The algorithm is applicable to a broad class of convex loss functions.Convergence of the algorithm is established (see reference). Development version is on github.
Functions for computing power and boundaries for pre-licensure vaccine trials using the Generalized Likelihood Ratio tests proposed by Shih, Lai, Heyse and Chen
Seven different methods for multiple testing problems. The SGoF-type methods and the BH and BY false discovery rate controlling procedures.
Functions to calculate student growth percentiles and percentile growth projections/trajectories for students using large scale,
longitudinal assessment data.  Functions use quantile regression to estimate the conditional density associated
with each student's achievement history.  Percentile growth projections/trajectories are calculated using the coefficient matrices derived from
the quantile regression analyses and specify what percentile growth is required for students to reach future achievement targets.
Functions for computing sparse generalized principal components, including functions for modeling structured correlation
Data sets utilized by the SGP Package as exemplars for users to conduct their own SGP analyses.
The Sparse Group Partial Least Square package (sgPLS) provides sparse, group, and sparse group versions of partial least square regression models.
The package for Sample Generation by Replacement simulations (SGR; Lombardi & Pastore, 2014; Pastore & Lombardi, 2014). The package can be used to perform fake data analysis according to the sample generation by replacement approach. It includes functions for making simple inferences about discrete/ordinal fake data. The package allows to study the implications of fake data for empirical results.
Provides functions to implement sgRSEA (single-guide RNA Set Enrichment Analysis), which is a robust test for identification of essential genes from genetic screening data using CRISPR (clustered regularly interspaced short palindromic repeats) and Cas9 (CRISPR-associated nuclease 9) system.
Density, distribution function, quantile function and random generation for the skewed generalized t distribution. This package also provides a function that can fit data to the skewed generalized t distribution using maximum likelihood estimation.
Functions for easily manipulating colours and creating colour scales.
Functions for plotting graphical shapes
such as ellipses, circles, cylinders, arrows, ...
In a scatterplot where the response variable is Gaussian, Poisson or binomial, we consider the case in which the mean function is smooth with a change-point, which is a mode, an inflection point or a jump point. The main routine estimates the mean curve and the change-point as well using shape-restricted B-splines. An optional subroutine delivering a bootstrap confidence interval for the change-point is incorporated in the main routine.
Functions to read and write ESRI shapefiles
An evolving and growing collection of tools for the quantification, assessment, and comparison of planar shape and pattern. The current flagship functionality is in the spatial decomposition of planar shapes using 'ShrinkShape' to incrementally shrink shapes to extinction while computing area, perimeter, and number of parts at each iteration of shrinking. The spectra of results are returned in graphic and tabular formats. Additional utility tools for handling data are provided and this package will be added to as more tools are created, cleaned-up, and documented.
Studies otolith shape variation among fish populations.
Otoliths are calcified structures found in the inner ear of teleost fish and their shape has
been known to vary among several fish populations and stocks, making them very useful in taxonomy,
species identification and to study geographic variations. The package extends previously described
software used for otolith shape analysis by allowing the user to automatically extract closed
contour outlines from a large number of images, perform smoothing to eliminate pixel noise,
choose from conducting either a Fourier or wavelet transform to the outlines and visualize
the mean shape. The output of the package are independent Fourier or wavelet coefficients
which can be directly imported into a wide range of statistical packages in R. The package
might prove useful in studies of any two dimensional objects.
Routines for the statistical analysis of landmark
shapes, including Procrustes analysis, graphical displays, principal
components analysis, permutation and bootstrap tests, thin-plate
spline transformation grids and comparing covariance matrices.
Landsat satellites collect important data about global forest conditions. Documentation about Landsat's role in forest disturbance estimation is available at the site <http://landsat.gsfc.nasa.gov/?p=9513>. By constrained quadratic B-splines, this package delivers an optimal shape-restricted trajectory to a time series of Landsat imagery for the purpose of modeling annual forest disturbance dynamics to behave in an ecologically sensible manner assuming one of seven possible "shapes", namely, flat, decreasing, one-jump (decreasing, jump up, decreasing), inverted vee (increasing then decreasing), vee (decreasing then increasing), linear increasing, and double-jump (decreasing, jump up, decreasing, jump up, decreasing). The main routine selects the best shape according to the minimum Bayes information criterion (BIC) or the cone information criterion (CIC), which is defined as the log of the estimated predictive squared error. The package also provides parameters summarizing the temporal pattern including year(s) of inflection, magnitude of change, pre- and post-inflection rates of growth or recovery. In addition, it contains routines for converting a flat map of disturbance agents to time-series disturbance maps and a graphical routine displaying the fitted trajectory of Landsat imagery.
A collection of tools for analyzing significance of trading
strategies, based on the Sharpe ratio and overfit of the same.
Miscellaneous soil data management, summary, visualization, and conversion utilities to support soil survey.
Hierarchical models for the analysis of species-area
relationships (SARs) by combining several data sets and covariates;
with a global data set combining individual SAR studies;
as described in Solymos and Lele
(2012, Global Ecology and Biogeography 21, 109-120).
Provides a computational framework for Bayesian estimation of
antigen-driven selection in immunoglobulin (Ig) sequences, providing an
intuitive means of analyzing selection by quantifying the degree of
selective pressure. Also provides tools to profile mutations in Ig
sequences, build models of somatic hypermutation (SHM) in Ig sequences,
and make model-dependent distance comparisons of Ig repertoires.
Implements various methods for eliciting a probability distribution
for a single parameter from an expert or a group of experts. The expert
provides a small number of probability judgements, corresponding
to points on his or her cumulative distribution function. A range of parametric
distributions can then be fitted and displayed, with feedback provided in the
form of fitted probabilities and percentiles. A graphical interface for the roulette elicitation
method is also provided. For multiple experts, a weighted linear pool can be
calculated. Also includes functions for eliciting beliefs about population distributions.
Makes it incredibly easy to build interactive web
applications with R. Automatic "reactive" binding between inputs and
outputs and extensive pre-built widgets make it possible to build
beautiful, responsive, and powerful applications with minimal effort.
Ace editor bindings to enable a rich text editing environment
within Shiny.
Provides Bootstrap 2 web components for use with the Shiny
package. With versions of Shiny prior to 0.11, these Bootstrap 2 components
were included as part of the package. Later versions of Shiny include
Bootstrap 3, so the Bootstrap 2 components have been moved into this
package for those uses who rely on features specific to Bootstrap 2.
Adds additional Twitter Bootstrap components to Shiny.
Create dashboards with 'Shiny'. This package provides
a theme on top of 'Shiny', making it easy to create attractive dashboards.
Add functionality to create drag and drop div elements in shiny.
Provides functionality for client-side navigation of
the server side file system in shiny apps. In case the app is running
locally this gives the user direct access to the file system without the
need to "download" files to a temporary location. Both file and folder
selection as well as file saving is available.
Interactive shiny application for analysis of educational tests and their items.
Perform common JavaScript operations in Shiny applications without
having to know any JavaScript. Examples include: hiding an element, disabling
an input, resetting an input back to its original value, delaying code execution
by a few seconds, and many more useful functions.
Shiny wrappers for the RGL package. This package exposes RGL's
ability to export WebGL visualization in a shiny-friendly format.
A graphical user interface for interactive Markov chain Monte
Carlo (MCMC) diagnostics and plots and tables helpful for analyzing a
posterior sample. The interface is powered by RStudio's Shiny web
application framework and works with the output of MCMC programs written
in any programming language (and has extended functionality for Stan models
fit using the rstan and rstanarm packages).
Themes for use with Shiny. Includes several Bootstrap themes
from http://bootswatch.com/, which are packaged for use with Shiny
applications.
Provides a time input widget for Shiny. This widget allows intuitive time input in the
'[hh]:[mm]:[ss]' or '[hh]:[mm]' (24H) format by using a separate numeric input for each time
component. The interface with R uses 'DateTimeClasses' objects. See the project page for more
information and examples.
Browser notifications in 'Shiny' apps, using
'toastr': <https://github.com/CodeSeven/toastr#readme>.
Exposes bindings to jsTree -- a JavaScript library
that supports interactive trees -- to enable a rich, editable trees in
Shiny.
The SHIP-package allows the estimation of various types of
shrinkage covariance matrices. These types differ in terms of
the so-called covariance target (to be chosen by the user), the
highly structured matrix which the standard unbiased sample
covariance matrix is shrunken towards and which optionally
incorporates prior biological knowledge extracted from the
database KEGG. The shrinkage intensity is obtained via an
analytical procedure.
A statistical method designed to take advantage of population genetics and microevolutionary theory, specifically by testing the association between haplotype sharing length and trait of interest.
Block-diagonal covariance selection for high dimensional Gaussian
graphical models. The selection procedure is based on the slope heuristics.
An interface to the API of the E-commerce service Shopify
(http://docs.shopify.com/api)
Analyzes shooting data with respect to group shape,
precision, and accuracy. This includes graphical methods,
descriptive statistics, and inference tests using standard,
but also non-parametric and robust statistical methods.
Implements distributions for radial error in bivariate normal
variables. Works with files exported by OnTarget PC/TDS or
Taran, as well as with custom data files in text format.
Supports inference from range statistics like extreme spread.
Includes a set of web-based graphical user interfaces.
Making it easy to use various types of fonts ('TrueType',
'OpenType', Type 1, web fonts, etc.) in R graphs, and supporting most output
formats of R graphics including PNG, PDF and SVG. Text glyphs will be converted
into polygons or raster images, hence after the plot has been created, it no
longer relies on the font files. No external software such as Ghostscript is
needed to use this package.
Providing font files that are needed by the 'showtext' package.
Functions for converting network data from a
SpatialLinesDataFrame object to a "igraph-class" object.
The predictive value of a statistical model can often be improved
by applying shrinkage methods. This can be achieved, e.g., by regularized
regression or empirical Bayes approaches. Various types of shrinkage factors can
also be estimated after a maximum likelihood. While global shrinkage modifies
all regression coefficients by the same factor, parameterwise shrinkage factors
differ between regression coefficients. With variables which are either highly
correlated or associated with regard to contents, such as several columns of a
design matrix describing a nonlinear effect, parameterwise shrinkage factors are
not interpretable and a compromise between global and parameterwise shrinkage,
termed 'joint shrinkage', is a useful extension. A computational shortcut to
resampling-based shrinkage factor estimation based on DFBETA residuals can be
applied. Global, parameterwise and joint shrinkage for models fitted by lm(),
glm(), coxph(), or mfp() is available.
Several shrinkage estimators of the effect-size of a parameter of interest.
Provides nonparametric Steinian shrinkage estimators of the covariance matrix that are suitable in high dimensional settings, that is when the number of variables is larger than the sample size.
Implementation of the shuffle estimator, a non-parametric estimator for signal and noise variance under mild noise correlations.
This package takes data on organism isotopes and fits a
Bayesian model to their dietary habits based upon a Gaussian
likelihood with a mixture dirichlet-distributed prior on the
mean. It also includes SiBER metrics. See siardemo() for an
example. Version 4.1.2 contains bug fixes to allow more than
isotope numbers other than 2. Version 4.2 fixes a bug that
stopped siar working on 64-bit systems
Fits bi-variate ellipses to stable isotope data using Bayesian
inference with the aim being to describe and compare their isotopic
niche.
The code computes the structural intervention distance (SID) between a true directed acyclic graph (DAG) and an estimated DAG. Definition and details about the implementation can be found in J. Peters and P. Bühlmann: "Structural intervention distance (SID) for evaluating causal graphs", Neural Computation 27, pages 771-799, 2015.
This package has many purposes: first, it gives to the
community an R implementation of each known side channel attack
and countermeasures as well as data to test it, second it
allows to implement a side channel attack quickly and easily.
Provides function to apply "Subgroup Identification based on Differential Effect Search" (SIDES) method proposed by Lipkovich et al. (2011) <doi:10.1002/sim.4289>.
Evolutionary reconstruction based on substitutions and insertion-deletion (indels) analyses in a distance-based framework.
Functions for making sieve test reports. Sieve test is widely used to obtain particle-size distribution of powders or granular materials.
Print function signatures and find overly complicated code.
SigClust is a statistical method for testing the
significance of clustering results. SigClust can be applied to
assess the statistical significance of splitting a data set
into two clusters. For more than two clusters, SigClust can be
used iteratively.
Uses logistic regression to model the probability of detection as a function of covariates.
This model is then used with observational survey data to estimate population size, while
accounting for uncertain detection.  See Steinhorst and Samuel (1989).
A collection of tools for estimating the location of a transmitter signal from radio telemetry studies using the maximum likelihood estimation (MLE) approach described in Lenth (1981).
Several different sigmoid functions are implemented, including a wrapper function, SoftMax preprocessing and inverse functions.
A set of signal processing functions originally written for 'Matlab' and 'Octave'.
Includes filter generation utilities, filtering functions,
resampling routines, and visualization of filter models. It also
includes interpolation functions.
Predicts the presence of signal peptides in eukaryotic protein
using hidden semi-Markov models. The implemented algorithm can be accessed from
both the command line and GUI.
Perform sign test on one-sample data, which is one of the oldest non-parametric statistical methods. Assume that X comes from a continuous distribution with median = v ( unknown ). Test the null hypothesis H0: median of X v = mu ( mu is the location parameter and is given in the test ) v.s. the alternative hypothesis H1: v > mu ( or v < mu or v != mu ) and calculate the p-value. When the sample size is large, perform the asymptotic sign test. In both ways, calculate the R-estimate of location of X and the distribution free confidence interval for mu.
Pathway Analysis is the process of statistically linking observations on the molecular level to biological processes or pathways on the systems (organism, organ, tissue, cell) level.
Traditionally, pathway analysis methods regard pathways as collections of single genes and treat all genes in a pathway as equally informative.  This can lead to identification of spurious (misleading) pathways as statistically significant, since components are often shared amongst pathways.
SIGORA seeks to avoid this pitfall by focusing on genes or gene-pairs that are (as a combination) specific to a single pathway.  In relying on such pathway gene-pair signatures (Pathway-GPS), SIGORA inherently uses the status of other genes in the experimental context to identify the most relevant pathways.
The current version allows for pathway analysis of human and mouse data sets and contains pre-computed Pathway-GPS data for pathways in the KEGG and Reactome pathway repositories as well as mechanisms for extracting GPS for user supplied repositories.
Takes a phylogenetic tree (of class phylo) and a data frame (or matrix) of corresponding tip labels and p-values, and determines the significance of the branches (families of p-values) and plots the tree with colored branches (corresponding to families) according to their levels of significance.  Also produces a CSV file with the p-values of all of the branches as well as which tips belong to which branches.  Finally, it exports a file that can be opened in FigTree that produces a colored plot (colored branches according to their significance of corresponding groups of p-values) with p-value annotations.
This package calculates ANSI S3.5-1997 Speech Intelligibility Index
(SII), a standard method for computing the intelligibility of
speech from acoustical measurements of speech, noise, and hearing
thresholds. This package includes data frames corresponding to
Tables 1 - 4 in the ANSI standard as well as a function utilizing
these tables and user-provided hearing threshold and noise level
measurements to compute the SII score.  The methods implemented
here extend the standard computations to allow calculation of SII
when the measured frequencies do not match those required by the
standard by applying interpolation to obtain values for the
required frequencies
--
Development of this package was funded by the Center for Bioscience
Education and Technology (CBET) of the Rochester Institute of
Technology (RIT).
Besides functions for the calculation of similarity and
multiple plot similarity measures with binary data (for
instance presence/absence species data) the package contains
some simple wrapper functions for reshaping species lists into
matrices and vice versa and some other functions for further
processing of similarity data (Mantel-like permutation
procedures) as well as some other useful stuff for vegetation
analysis.
Package simboot provides estimation of simultaneous bootstrap and asymptotic confidence intervals for diversity indices, namely the Shannon and the Simpson index. Several pre--specified multiple comparison types are available to choose. Further user--defined contrast matrices are applicable. In addition, simboot estimates adjusted as well as unadjusted p--values for two of the three proposed bootstrap methods. Further simboot allows for comparing biological diversities of two or more groups while simultaneously testing a user-defined selection of Hill numbers of orders q, which are considered as appropriate and useful indices for measuring diversity.
A flexible tool for simulating complex longitudinal data using
structural equations, with emphasis on problems in causal inference.
Specify interventions and simulate from intervened data generating
distributions. Define and evaluate treatment-specific means, the average
treatment effects and coefficients from working marginal structural models.
User interface designed to facilitate the conduct of transparent and
reproducible simulation studies, and allows concise expression of complex
functional dependencies for a large number of time-varying nodes. See the
package vignette for more information, documentation and examples.
Simultaneous tests and confidence intervals are provided for one-way experimental designs with one or many normally distributed, primary response variables (endpoints). Differences (Hasler and Hothorn, 2011) or ratios (Hasler and Hothorn, 2012) of means can be considered. Various contrasts can be chosen, unbalanced sample sizes are allowed as well as heterogeneous variances (Hasler and Hothorn, 2008) or covariance matrices (Hasler, 2014).
Simulates correlated multinomial responses conditional on a marginal model specification.
Algorithms for the implementation and evaluation of Monte Carlo tests, as well as for their use in multiple testing procedures.
Provides tools to help safely and efficiently organize Monte Carlo simulations in R.
The package controls the structure and back-end of Monte Carlo simulations
by utilizing a general generate-analyse-summarise strategy. The functions provided control
common simulation issues such as re-simulating non-convergent results, support parallel
back-end and MPI distributed computations, save and restore temporary files,
aggregate results across independent nodes, and provide native support for debugging.
Provides the functions for simulation and modeling of stochastic differential equations (SDE's) the type Ito and Stratonovich. This package contains many objects, the numerical methods to find the solutions to SDE's (1, 2 and 3-dim), with a possibility for simulates a flows trajectories,with good accuracy. Many theoretical problems on the SDE's have become the object of practical research, as statistical analysis and simulation of solution of SDE's, enabled many searchers in different domains to use these equations to modeling and to analyse practical problems, in financial and actuarial modeling and other areas of application, for example modelling and simulate of dispersion in shallow water using the attractive center (Boukhetala K, 1996).  We hope that the package presented here and the updated survey on the subject might be of help for practitioners, postgraduate and PhD students, and researchers in the field who might want to implement new methods.
An object oriented framework to simulate
ecological (and other) dynamic systems. It can be used for
differential equations, individual-based (or agent-based) and other
models as well. The package helps to organize scenarios (to avoid copy
and paste) and aims to improve readability and usability of code.
Estimation of function and index vector in single index model with and without shape constraints including different smoothness conditions.
Implementation of the SIMEX-Algorithm by Cook & Stefanski
and MCSIMEX by Küchenhoff, Mwalili & Lesaffre
Implement of the Simulation-Extrapolation (SIMEX) algorithm for the accelerated failure time (AFT) with covariates subject to measurement error.
A general framework for statistical simulation.
Generate power for the Cox proportional hazards model by simulating survival events data with time dependent exposure status for subjects. A dichotomous exposure variable is considered with a single transition from unexposed to exposed status during the subject's time on study.
Functions to run and assist four
different similarity measures. The similarity
measures included are: longest common
subsequence (LCSS), Frechet distance, edit distance
and dynamic time warping (DTW). Each of these
similarity measures can be calculated from two
n-dimensional trajectories, both in matrix form.
Allows a Simile model saved as a compiled binary to be
loaded, parameterized, executed and interrogated. This version works
with Simile v5.97 on.
Livestock movements are important for the spread of many
infectious diseases between herds. The package provides an
efficient and flexible framework for stochastic disease spread
modelling that integrates within-herd disease dynamics as
continuous-time Markov chains and livestock movements between
herds as scheduled events. The core simulation solver is
implemented in C and uses 'OpenMP' (if available) to divide work
over multiple processors. The package contains template models and
can be extended with user defined models.
Provides methods for simulation and analysis of a very general fatigue
lifetime model for (metal matrix) composite materials.
A process-oriented and trajectory-based Discrete-Event Simulation
(DES) package for R. Designed to be a generic framework like SimPy or
SimJulia, it leverages the use of Rcpp to boost the performance, turning
DES in R feasible. As a noteworthy characteristic, simmer exploits the
concept of trajectory: a common path in the simulation model for entities
of the same type.
Fits a stable isotope mixing model via JAGS in R. The package allows for any number of isotopes or sources, as well as concentration dependencies.
Algorithms to create prognostic biomarkers using biological networks.
Simulation of event histories with possibly non-linear baseline hazard rate functions, non-linear (time-varying) covariate effect functions, and dependencies on the past of the history. Random generation of event histories is performed using inversion sampling on the cumulative all-cause hazard rate functions.
Implements the inference of
co-expression networks based on partial correlation
coefficients from either steady-state or time-course
transcriptomic data. Note that with both type of data this
package can deal with samples collected in different
experimental conditions and therefore not identically
distributed. In this particular case, multiple but related
networks are inferred on one simone run.
Simulate data from a Gaussian graphical model or a Gaussian Bayesian network in two conditions. Given a covariance matrix of a reference condition simulate plausible dysregulations.
Simulates and plots quantities of interest (relative
hazards, first differences, and hazard ratios) for linear coefficients,
multiplicative interactions, polynomials, penalised splines, and
non-proportional hazards, as well as stratified survival curves from Cox
Proportional Hazard models. It also simulates and plots marginal effects
for multiplicative interactions.
Simple classic graph algorithms for simple graph classes.
Graphs may possess vertex and edge attributes. 'simplegraph' has
so dependencies and it is written entirely in R, so it is easy to
install.
Trains neural networks (multilayer perceptrons with one hidden layer) for bi- or multi-class classification.
Simple result caching in R based on Henrik
Bengtsson's R.cache. The global environment is not considered when caching
results simplifying moving files between multiple instances of R. Relies on
more base functions than R.cache (e.g. cached results are saved using saveRDS()
and readRDS()).
SimpleTable provides a series of methods to conduct
Bayesian inference and sensitivity analysis for causal effects
from 2 x 2 and 2 x 2 x K tables when unmeasured confounding is
present or suspected.
Simplex density, distribution, quantile functions as well as random variable
generation of the simplex distribution are given. Regression analysis of proportional data
using various kinds of simplex models is available. In addition, GEE method can be applied
to longitudinal data to model the correlation. Residual analysis is also involved. Some
subroutines are written in C with GNU Scientific Library (GSL) so as to facilitate the
computation.
Provides methods to integrate functions over m-dimensional simplices
in n-dimensional Euclidean space.  There are exact methods for polynomials and
adaptive methods for integrating an arbitrary function.  Dirichlet probabilities
are calculated in certain cases.
Basic tools for symbolic expression simplification, e.g. simplify(x*1) => x, or simplify(sin(x)^2+cos(x)^2) => 1. Based on the "Expression v3" (Ev3) 1.0 system by Leo Liberti.
Tools and methods to simulate populations for surveys based
on auxiliary data. The tools include model-based methods, calibration and
combinatorial optimization algorithms. The package was developed with support of
the International Household Survey Network, DFID Trust Fund TF011722 and funds from the World bank.
This package detects instances of Simpson's Paradox in
datasets. It examines subpopulations in the data, either
user-defined or by means of cluster analysis, to test whether a
regression at the level of the group is in the opposite
direction at the level of subpopulations.
Calculate power for generalised linear mixed models, using
simulation. Designed to work with models fit using the 'lme4' package.
Provides a number of functions to simulate restriction enzyme digestion, library construction and fragments size selection to predict the number of loci expected from most of the Restriction site Associated DNA (RAD) and Genotyping By Sequencing (GBS) approaches. SimRAD estimates the number of loci expected from a particular genome depending on the protocol type and parameters allowing to assess feasibility, multiplexing capacity and the amount of sequencing required.
Functions for performing Bayesian `similarity regression',
specialised for modelling the association between a HPO-encoded phenotype
and binary genotype. A `no association' model is compared with one in which
the log odds of having a rare genotype is linked to the semantic similarity
between patient phenotype and a latent characteristic phenotype. The method
estimates the probability of an association together with an HPO-coded phenotype
characteristic of the disease.
Facilitates data simulation from a random regression model where the data properties can be controlled by a few input parameters. The data simulation is based on the concept of relevant latent components and relevant predictors, and was developed for the purpose of testing methods for variable selection for prediction. Included are also functions for designing computer experiments in order to investigate the effects of the data properties on the performance of the tested methods. The design is constructed using the Multi-level Binary Replacement (MBR) design approach which makes it possible to set up fractional designs for multi-factor problems with potentially many levels for each factor.
Provides functions to generate and analyze individual-based spatially-explicit
simulations of multi-state movements in heterogeneous landscapes, based on "resistance"
rasters. Although originally conceived and designed to fill the gap of softwares simulating
spatially-explicit trajectories of species constrained to linear, dendritic habitats
(e.g., river networks), the simulation algorithm is built to be highly flexible and can be
applied to any (aquatic, semi-aquatic or terrestrial) organism. Thus, the user will be able
to use the package to simulate movements either in homogeneous landscapes, heterogeneous
landscapes (e.g. semi-aquatic animal in a riverscape), or even in highly contrasted
landscapes (e.g. fish in a river network). The algorithm and its input parameters are
the same for all cases, so that results are comparable. Simulated trajectories can then
be used as null models to test e.g. for species site fidelity and other movement ecology
hypotheses, or to build predictive, mechanistic movement models, among other things. The
package should thus be relevant to explore a broad spectrum of ecological phenomena, such
as those at the interface of animal behaviour, landscape, spatial and movement ecology,
disease and invasive species spread, and population dynamics. This is the first released
experimental version; do test before using in production.
Tools for setting up ("design"), conducting, and evaluating
large-scale simulation studies with graphics and tables, including
parallel computations.
Contains two functions for simulating survival data from piecewise exponential hazards with a proportional hazards adjustment for covariates. The first function SimUNIVPiecewise simulates univariate survival data based on a piecewise exponential hazard, covariate matrix and true regression vector. The second function SimSCRPiecewise semi-competing risks data based on three piecewise exponential hazards, three true regression vectors and three matrices of patient covariates (which can be different or the same). This simulates from the Semi-Markov model of Lee et al (2015) given patient covariates, regression parameters, patient frailties and baseline hazard functions.
Provides an easy framework for Monte Carlo simulation in structural equation modeling, which can be used for various purposes, such as such as model fit evaluation, power analysis, or missing data handling and planning.
RNA sequencing analysis methods are often derived by relying on hypothetical parametric models for read counts that are not likely to be precisely satisfied in practice. Methods are often tested by analyzing data that have been simulated according to the assumed model. This testing strategy can result in an overly optimistic view of the performance of an RNA-seq analysis method. We develop a data-based simulation algorithm for RNA-seq data. The vector of read counts simulated for a given experimental unit has a joint distribution that closely matches the distribution of a source RNA-seq dataset provided by the user. Users control the proportion of genes simulated to be differentially expressed (DE) and can provide a vector of weights to control the distribution of effect sizes. The algorithm requires a matrix of RNA-seq read counts with large sample sizes in at least two treatment groups. Many datasets are available that fit this standard.
Simulates data sets in order to explore modeling techniques or
better understand data generating processes. The user specifies a set of
relationships between covariates, and generates data based on these
specifications. The final data sets can represent data from randomized
control trials, repeated measure (longitudinal) designs, and cluster
randomized trials. Missingness can be generated using various
mechanisms (MCAR, MAR, NMAR).
simSummary is a small utility package which eases the
process of summarizing simulation results. Simulations often
produce intermediate results - some focal statistics that need
to be summarized over several scenarios and many replications.
This step is in principle easy, but tedious. The package
simSummary fills this niche by providing a generic way of
summarizing the focal statistics of simulations. The useR must
provide properly structured input, holding focal statistics,
and then the summary step can be performed with one line of
code, calling the simSummary function.
The simTool package is designed for statistical simulations that
have two components. One component generates the data and the other one
analyzes the data. The main aims of the simTool package are the reduction
of the administrative source code (mainly loops and management code for the
results) and a simple applicability of the package that allows the user to
quickly learn how to work with the simTool package. Parallel computing is
also supported. Finally, convenient functions are provided to summarize the
simulation results.
This package provides simulation process of 4 selection methods in predicting potent compounds
A framework for performing simulations such as those common in
methodological statistics papers.  The design principles of this package
are described in greater depth in Bien, J. (2016) "The simulator: An Engine
to Streamline Simulations," which is available at
<http://faculty.bscb.cornell.edu/~bien/simulator.pdf>.
This package performs classical correspondence analysis (CA) and
simultaneous analysis (SA). Simultaneous analysis is a factorial
methodology developed for the joint treatment of a set of several
contingency tables. In SA tables having the same rows, are concatenated
row-wise.
In this version of the package a multiple option have been included for
the simultaneous analysis
of tables having the same columns, concatenated column-wise.
This way, a MSA allows to perform the analysis of an indicator matrix
where the rows represent individuals.
In this package, functions for computation, summaries
and graphical visualization in two dimensions are provided, including
options to display partial and supplementary points.
This package provides routines to perform SIN model selection
as described in Drton & Perlman (2004, 2008).  The selected models are
represented in the format of the 'ggm' package, which allows in
particular parameter estimation in the selected model.
The sinaplot is a data visualization chart suitable for plotting
any single variable in a multiclass dataset. It is an enhanced jitter strip
chart, where the width of the jitter is controlled by the density
distribution of the data within each class.
Density, distribution function, quantile function, random
generation and survival function for the Sine Inverse Weibull Distribution as
defined by SOUZA, L. New Trigonometric Class of Probabilistic Distributions.
219 p. Thesis (Doctorate in Biometry and Applied Statistics) - Department of
Statistics and Information, Federal Rural University of Pernambuco, Recife,
Pernambuco, 2015 (available at <http://www.openthesis.org/documents/New-trigonometric-classes-probabilistic-distributions-602633.html>) and BRITO, C. C. R. Method Distributions generator and
Probability Distributions Classes. 241 p. Thesis (Doctorate in Biometry and
Applied Statistics) - Department of Statistics and Information, Federal Rural
University of Pernambuco, Recife, Pernambuco, 2014 (available upon request).
A platform for experimenting with spatially explicit individual-based vegetation models.
Calculating daily global solar radiation at horizontal surface using several well-known models (i.e. Angstrom-Prescott, Supit-Van Kappel, Hargreaves, Bristow and Campbell, and Mahmood-Hubbard), and model calibration based on ground-truth data, and (3) model auto-calibration. The FAO Penmann-Monteith equation to calculate evapotranspiration is also included.
This package fits single-index (quadratic) response surface models.
Supplementary item response theory models to complement existing
functions in R, including multidimensional compensatory and
noncompensatory IRT models, MCMC for hierarchical IRT models and
testlet models, NOHARM, Rasch copula model, faceted and
hierarchical rater models, ordinal IRT model (ISOP),
DETECT statistic, local structural equation modeling (LSEM),
mean and covariance structure modelling for multivariate normally
distributed data.
Variable selection techniques are essential tools for model
selection and estimation in high-dimensional statistical models. Through this
publicly available package, we provide a unified environment to carry out
variable selection using iterative sure independence screening (SIS) and all
of its variants in generalized linear models and the Cox proportional hazards
model.
Implements the SISAL algorithm by Tikka and Hollmén. It is
a sequential backward selection algorithm which uses a linear
model in a cross-validation setting. Starting from the full
model, one variable at a time is removed based on the
regression coefficients. From this set of models, a
parsimonious (sparse) model is found by choosing the model with
the smallest number of variables among those models where the
validation error is smaller than a threshold. Also implements
extensions which explore larger parts of the search space
and/or use ridge regression instead of ordinary least squares.
SISUS for source partitioning using stable isotopes.
SISUS reads in a specific Excel-like workbook and performs an IsoSource-type analysis by
returning a sample of feasible solutions to p in the non-over constrained linear systems, b=Ap.
Edit \file{sisus_*_template.xls} and input data values and run parameters.
Run \code{\link{sisus.run}(filename)}. See output in current working directory.
Selects invalid instruments amongst a candidate of potentially bad instruments. The algorithm selects potentially invalid instruments and provides an estimate of the causal effect between exposure and outcome.
Functions for fitting and plotting SITAR (Super Imposition by
Translation And Rotation) growth curve models. SITAR is a shape-invariant model
with a regression B-spline mean curve and subject-specific random effects on
both the measurement and age scales.
Provided within is a high quality and fast PPRNG that is able to be used in an 'OpenMP' parallel
environment compiled under either C++98 or C++11. The objective of this package release is to consolidate
the distribution of the 'sitmo' library on CRAN by enabling others to link to the 'sitmo' header file instead
of including a copy of 'sitmo' within their individual package. Lastly, the package contains example
implementations using 'sitmo' and two accompanying vignette that provide additional information.
Format a number (or a list of numbers) to a string (or a
list of strings) with SI prefix. Use SI prefixes as constants
like (4 * milli)^2
Sensitivity indices with dependent correlated inputs, using a
method based on PLS regression.
Functions and utilities to perform
Statistical Analyses in the Six Sigma way.
Through the DMAIC cycle (Define, Measure, Analyze, Improve, Control),
you can manage several Quality Management studies:
Gage R&R, Capability Analysis, Control Charts, Loss Function Analysis,
etc. Data frames used in the books "Six Sigma with R" (Springer, 2012)
and "Quality Control with R" (Springer, 2015)
are also included in the package.
This function develops an algorithm for presenting a Bayesian hierarchical model for estimating the sizes of local and national drug injected populations in Bangladesh. The model incorporates multiple commonly used data sources including mapping data, surveys, interventions, capture-recapture data, estimates or guesstimates from organizations, and expert opinion.
Contains functions to estimate morphometric and gonadal size at sexual maturity for organisms, usually fish and invertebrates. It includes methods for classification based on relative growth (using principal components analysis, hierarchical clustering, discriminant analysis), logistic regression (Frequentist or Bayes), parameters estimation and some basic plots.
Calculates and plots the SiZer map for scatterplot data.
A SiZer map is a way of examining when the p-th derivative of a
scatterplot-smoother is significantly negative, possibly zero
or significantly positive across a range of smoothing
bandwidths.
Provides a database-independent JDBC interface.
Collection of miscellaneous utility functions (especially intended
for people coming from other statistical software packages like 'SPSS', and/
or who are new to R), supporting following common tasks: 1) Reading and writing
data between R and other statistical software packages like 'SPSS', 'SAS' or
'Stata' and working with labelled data; this includes easy ways to get and set
label attributes, to convert labelled vectors into factors (and vice versa),
or to deal with multiple declared missing values etc. 2) Data transformation
tasks like recoding, dichotomizing or grouping variables, setting and replacing
missing values. 3) Convenient functions to perform frequently used statistical
tests, or to calculate various commonly used statistical coefficients.
Collection of plotting and table output functions for data
visualization. Results of various statistical analyses (that are commonly used
in social sciences) can be visualized using this package, including simple and
cross tabulated frequencies, histograms, box plots, (generalized) linear models,
mixed effects models, PCA and correlation matrices, cluster analyses, scatter
plots, Likert scales, effects plots of regression models (including interaction
terms) and much more. This package supports labelled data.
Collection of convenient functions for common statistical computations,
which are not directly provided by R's base or stats packages.
This package aims at providing, first, shortcuts for statistical
measures, which otherwise could only be calculated with additional
effort (like standard errors or root mean squared errors). Second,
these shortcut functions are generic (if appropriate), and can be
applied not only to vectors, but also to other objects as well
(e.g., the Coefficient of Variation can be computed for vectors,
linear models, or linear mixed models; the r2()-function returns
the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects).
The focus of most functions lies on summary statistics or fit
measures for regression models, including generalized linear
models and mixed effects models. However, some of the functions
also deal with other statistical measures, like Cronbach's Alpha,
Cramer's V, Phi etc.
Functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.
Computes necessary information to meta analyze SKAT
statistics in each individual cohort, and then performs the
meta analysis.
Sparse (Multicategory) Kernel Discriminant Analysis does variable selection for nonparametric classification
Functions for the Skellam distribution, including: density
(pmf), cdf, quantiles and random variates.
Functions are provided for the density function,
distribution function, quantiles and random number generation
for the skew hyperbolic t-distribution. There are also
functions that fit the distribution to data. There are
functions for the mean, variance, skewness, kurtosis and mode
of a given distribution and to calculate moments of any order
about any centre. To assess goodness of fit, there are
functions to generate a Q-Q plot, a P-P plot and a tail plot.
Density, distribution function, quantile function and
random generation for the skewed t distribution of Fernandez
and Steel.
A generalization of the statistic used in Friedman's ANOVA method and in Durbin's rank test. This nonparametric statistical test is useful for the data obtained from block designs with missing observations occurring randomly. A resulting p-value is based on the chi-squared distribution and Monte Carlo method.
Algorithms to compute spherical k-means partitions.
Features several methods, including a genetic and a fixed-point
algorithm and an interface to the CLUTO vcluster program.
Provides an alternative to manually process hemispherical pictures. The algorithm processes each picture one by one to determine the proportion of sky pixel. The algorithm uses the Ridler and Calvard method (Ridler and Calvard 1978).
Provides directly interpretable estimated coefficients
for four models in connection with the two-group straight line
ANCOVA problem: (A) the full model, which requires the fitting of
two intercepts and two slopes; (B) a reduced model, which requires
the fitting of a single intercept and single slope; (C) a reduced
model, which requires the fitting of two separate intercepts and a
single, common slope; and (D) a reduced model, which requires the
fitting of a single, common intercept and two separate slopes.  The
summary function provides tests of fit for the (null) hypotheses of:
(1) equivalent data sets, (2) equivalent slopes, and
(3) equivalent intercepts.
'Slack' <http://slack.com/> provides a service for teams to
collaborate by sharing messages, images, links, files and more. Functions are provided
that make it possible to interact with the 'Slack' platform 'API'. When
you need to share information or data from R, rather than resort to copy/
paste in e-mails or other services like 'Skype' <http://www.skype.com/>, you
can use this package to send well-formatted output from multiple R objects and
expressions to all teammates at the same time with little effort. You can also
send images from the current graphics device, R objects, and upload files.
Data structures and algorithms for sparse arrays and matrices,
based on index arrays and simple triplet representations, respectively.
Estimates the slope and level change present in data after
removing phase A trend. Represents graphically the original and
the detrended data.
The skew logistic distribution is a quantile-defined generalisation
of the logistic distribution (van Staden and King 2015).  Provides random
numbers, quantiles, probabilities, densities and density quantiles for the distribution.
It provides Quantile-Quantile plots and method of L-Moments estimation
(including asymptotic standard errors) for the distribution.
Calculates maximum likelihood estimate, exact and asymptotic confidence intervals, and exact and asymptotic goodness of fit p-values for infectious units per million (IUPM) from serial limiting dilution assays. This package uses the likelihood equation, exact PGOF, and exact confidence intervals described in Meyers et al. (1994) <http://jcm.asm.org/content/32/3/732.full.pdf>.
Compute Time series Resistant Smooth 4253H, twice smoothing method.
Data sets from Ramsey, F.L. and Schafer, D.W. (2002), "The
Statistical Sleuth: A Course in Methods of Data Analysis (2nd
ed)", Duxbury.
Data sets from Ramsey, F.L. and Schafer, D.W. (2013), "The
Statistical Sleuth: A Course in Methods of Data Analysis (3rd
ed)", Cengage Learning.
Set of tools to find coherent patterns in microarray data
using a Bayesian sparse latent factor model (Duarte and Mayrink 2015 -
http://link.springer.com/chapter/10.1007%2F978-3-319-12454-4_15).
Considerable effort has been put into making slfm fast and memory efficient,
turning it an interesting alternative to simpler methods in terms
of execution time. It implements versions of the SLFM using both type
of mixtures: using a degenerate distribution or a very concentrated
normal distribution for the spike part of the mixture. It also implements
additional functions to help pre-process the data and fit the model
for a large number of arrays.
Generate the optimal Latin Hypercube Designs (LHDs) for computer experiments with quantitative factors and the optimal Sliced Latin Hypercube Designs (SLHDs) for computer experiments with both quantitative and qualitative factors. Details of the algorithm can be found in Ba, S., Brenneman, W. A. and Myers, W. R. (2015), "Optimal Sliced Latin Hypercube Designs," Technometrics. Important function in this package is "maximinSLHD".
Efficient procedures for Sorted L1 Penalized Estimation (SLOPE).
The sorted L1 norm is useful for statistical estimation and testing,
particularly for variable selection in the linear model.
Interface for creation of 'slp' class smoother objects for
use in Generalized Additive Models (as implemented by packages
'gam' and 'mgcv').
This is software linked to the book
'Applied Smoothing Techniques for Data Analysis -
The Kernel Approach with S-Plus Illustrations' Oxford University Press.
Implementation of the Stochastic Multi-Criteria Acceptability Analysis (SMAA) family of Multiple Criteria Decision Analysis (MCDA) methods.
This package provides a solution path for L1-penalized angle-based classification. Three loss functions are implemented in smac, including the deviance loss in logistic regression, the exponential loss in boosting, and the proximal support vector machine loss.
Provides the following approaches for multidimensional scaling (MDS) based on stress minimization by means of majorization (smacof): basic MDS on symmetric dissimilarity matrices,
MDS with external constraints on the configuration, individual difference scaling (idioscal, indscal, and friends), MDS with spherical restrictions, and unfolding. The MDS type can be ratio, interval, ordinal, and monotone splines.
Various tools and extensions like jackknife MDS, permutation tests, gravity models, inverse MDS, unidimensional scaling, classical scaling, and Procrustes.
Various statistical methods for analyzing case-control point data.
The methods available closely follow those in chapter 6 of Applied Spatial
Statistics for Public Health Data by Waller and Gotway (2004).
Inference techniques for Fay Herriot Model.
Animal movement models including moving-resting process
with embedded Brownian motion, Brownian motion with measurement error.
The package "smart" provides a general framework for
analyzing (including estimation, feature selection and
prediction) and visualize big data. It integrates several
novel, efficient and robust data analysis tools, including
Transelliptical Component Analysis (TCA), Transelliptical
Correlation Estimation (TCE) and Group Nearest Shrunken
Centroids (gnsc). We target on high dimensional data
analysis(usually d >> n), and exploit computationally
efficiently approaches. Results are organized to be visualized
properly for users.
Tools for accessing and processing datasets prepared by the Foundation SmarterPoland.pl. Among all: access to API of Google Maps, Central Statistical Office of Poland, MojePanstwo, Eurostat, WHO and other sources.
This package provides methods of fitting bivariate lines in allometry using the major axis (MA) or standardised major axis (SMA), and for making inferences about such lines. The available methods of inference include confidence intervals and one-sample tests for slope and elevation, testing for a common slope or elevation amongst several allometric lines, constructing a confidence interval for a common slope or elevation, and testing for no shift along a common axis, amongst several samples.
The main purpose of the package is to categorize a numeric variable into bins
mapped to a binary target variable for its ulterior usage in scoring modeling.
This functionality reduces dramatically the time consuming process of finding the optimal
cut points for a given numeric variable, quickly calculates the Information Value, either for
one variable at the time or all at once in one line of code; and also outputs 'SQL' codes,
tables, and plots used throughout the development stage.
The package also allows the user to understand the data via exploratory data analysis
in one step, establish customized cut points for numeric characteristics, and run the analysis
for categorical variables.
particle filtering, auxiliary particle filtering and sequential Monte Carlo algorithms
Implements multiple imputation of missing covariates by
Substantive Model Compatible Fully Conditional Specification.
This is a modification of the popular FCS/chained equations
multiple imputation approach, and allows imputation of missing
covariate values from models which are compatible with the user
specified substantive model.
This package is for optimizing non-linear complex
functions based on Monte Carlo random sampling.
A package containing functions for genome-wide association
studies.
Data Sets for Kumar and Petersen (2012).
Statistical Methods in Customer Relationship Management,
Wiley: New York.
An R-package for Estimating Semiparametric PH and AFT
Mixture Cure Models
Provides resampling functions (stratified, residual,
multinomial, systematic, and branching), measures of weight
uniformity (coefficient of variation, effective sample size,
and entropy), and a weight renormalizing function.
Contains data files to accompany Smithson & Merkle (2013), Generalized Linear Models for Categorical and Continuous Limited Dependent Variables.
This package provides similarity among documents.
Symbolic multidimensional scaling for interval-valued dissimilarities. The hypersphere model and the hyperbox model are available.
A package for fitting smoothing-splines mixed-effects models to replicated functional
data sets.
Provides statistical methods for the analysis of data areal data, with a focus on cluster detection.
R functions and data from Chapter 5 of 'Statistical
Methods for Financial Engineering', by Bruno Remillard, CRC
Press, (2013).
This package contains code and data for modelling and simulation of stochastic kinetic biochemical network models. It contains the code and data associated with the second edition of the book Stochastic Modelling for Systems Biology, published by Chapman & Hall/CRC Press, November 2011.
Smooth multivariate interpolation for gridded and scattered data
with possibly large datasets. The code for scattered data is taken from the
'SHEPPACK' Fortran package.
This package accompanies Aitkin et al, Statistical
Modelling in R, OUP, 2009. The package contains some functions
and datasets used in the text.
This tiny package contains one function smirnov() which
calculates two scaled taxonomic coefficients, Txy (coefficient
of similarity) and Txx (coefficient of originality). These two
characteristics may be used for the analysis of similarities
between any number of taxonomic groups, and also for assessing
uniqueness of giving taxon. It is possible to use smirnov()
output as a distance measure: convert it to distance by
"as.dist(1 - smirnov(x))".
A collection of functions for statistical computing and data manipulation in R.
Includes routines for data ingestion, operating on dataframes and matrices, conversion to and
from lists, converting factors, filename manipulation, programming utilities, parallelization, plotting,
statistical and mathematical operations, and time series.
Constructs a yield curve by the Smith-Wilson method from a
table of LIBOR and SWAP rates
The SML package is a collection of statistical machine learning methods.
Fit univariate right, left or interval censored regression model under the scale mixture of normal distributions
Fits flexible additive models to data on stream networks, taking account of flow-connectivity of the network.  Models are fitted using penalised least squares.
Provides generators for a high number of both single- and multi-
objective test functions which are frequently used for the benchmarking of
(numerical) optimization algorithms. Moreover, it offers a set of convenient
functions to generate, plot and work with objective functions.
A collection of methods for smoothing numerical data, commencing with a port of the Matlab gaussian window smoothing function. In addition, several functions typically used in smoothing of financial data are included.
SmoothHazard is a package for fitting illness-death (and survival)
model with possibly interval-censored data for transition toward transient
state. Left-truncated and right-censored data are also allowed.
Proportional intensities regression models allow for covariates on each of
the 3 transitions. We use either a parametric approach with Weibull
baseline intensities or a semi-parametric approach with M-splines
approximation of baseline intensities in order to obtain smooth estimates.
Estimation of parameters is conducted by likelihood maximization in the
parametric approach or penalized likelihood maximization in the
semi-parametric approach.
Provides flexible hazard ratio curves allowing non-linear
relationships between continuous predictors and survival. To
better understand the effects that each continuous covariate
has on the outcome, results are ex pressed in terms of hazard
ratio curves, taking a specific covariate value as reference.
Confidence bands for these curves are also derived.
Functions to smooth two-dimensional fields using FFT and the convolution theorem
Some M-estimators for 1-dimensional location (Bisquare, ML
for the Cauchy distribution, and the estimators from
application of the smoothing principle introduced in Hampel,
Hennig and Ronchetti (2011) to the above, the Huber
M-estimator, and the median, main function is smoothm), and
Pitman estimator.
Contains, as a main contribution, a function to fit
a regression model with possibly right, left or interval
censored observations and with the error distribution
expressed as a mixture of G-splines. Core part
of the computation is done in compiled C++ written
using the Scythe Statistical Library Version 0.3.
Given independent and identically distributed observations X(1), ..., X(n) from a Generalized Pareto distribution with shape parameter gamma in [-1,0], offers several estimates to compute estimates of gamma. The estimates are based on the principle of replacing the order statistics by quantiles of a distribution function based on a log--concave density function. This procedure is justified by the fact that the GPD density is log--concave for gamma in [-1,0].
This package contains the datasets and a few functions for
use with the practicals outlined in Appendix A of the book
Statistical Models (Davison, 2003, Cambridge University Press).
The practicals themselves can be found at
http://statwww.epfl.ch/davison/SM/
Computes the studentized midrange distribution (pdf, cdf and quantile) and generates random numbers
Produce small area population estimates by fitting census data to
survey data.
Datasets used in "Statistical Methods for the Social Sciences"
(SMSS) by Alan Agresti and Barbara Finlay.
Implements the structural model for variances in order to
detect differentially expressed genes from gene expression data
Build and manipulate probability distributions of the skew-normal
family and some related ones, notably the skew-t family, and provide related
statistical methods for data fitting and diagnostics, in the univariate and
the multivariate case.
A range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.
Functions for reading and writing Gadget N-body snapshots. The Gadget code is popular in astronomy for running N-body / hydrodynamical cosmological and merger simulations. To find out more about Gadget see the main distribution page at www.mpa-garching.mpg.de/gadget/
Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, and classification.
Implementation of robust and non-robust Standard Normal Homogeneity
Test (SNHT) for changepoint detection. This test statistic is equal sided,
as proposed in "Homogenization of Radiosonde Temperature Time Series Using
Innovation Statistics" by Haimberger, L., 2007. However, the statistic contains
an estimate of sigma^2 in the denominator instead of sigma, which seems to
be a more appropriate value (based on the paper "Homogenization of Swedish
temperature data. Part I: Homogeneity test for linear trends." by Alexandersson,
H., and A. Moberg, 1997).
Implement K-nearest neighbor classifier, weighted nearest neighbor classifier, bagged nearest neighbor classifier, optimal weighted nearest neighbor classifier and stabilized nearest neighbor classifier, and perform model selection via 5 fold cross-validation for them. This package also provides functions for computing the classification error and classification instability of a classification procedure.
Support for simple parallel computing in R.
An R interface to the C libstemmer library that implements
Porter's word stemming algorithm for collapsing words to a common
root to aid comparison of vocabulary. Currently supported languages are
Danish, Dutch, English, Finnish, French, German, Hungarian, Italian,
Norwegian, Portuguese, Romanian, Russian, Spanish, Swedish
and Turkish.
Functions for analysis of network objects, which are imported or
simulated by the package. The non-parametric methods of analysis center
around snowball and bootstrap sampling.
Usability wrapper around snow for easier development of
parallel R programs. This package offers e.g. extended error
checks, and additional functions. All functions work in
sequential mode, too, if no cluster is present or wished.
Package is also designed as connector to the cluster management
tool sfCluster, but can also used without it.
Extension of the snow package supporting fault tolerant and reproducible applications, as well as supporting easy-to-use parallel programming - only one function is needed.
contains several supplementary non-parametric statistics methods including quantile test, Cox-Stuart trend test, runs test, normal score test, kernel PDF and CDF estimation, kernel regression estimation and kernel Kolmogorov-Smirnov test.
This package carries out most common analysis when performing whole genome association studies. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Permutation test and related tests (sum statistic and truncated product) are also implemented. Max-statistic and genetic risk-allele score exact distributions are also possible to be estimated.
Implements classes and methods for large scale SNP enrichment analysis (e.g. SNPs associated with genes expression in a GWAS signal).
A set of functions to create SQL tables of gene and SNP information and compose them into a SNP Set, for example for use with the RSNPset package, or to export to a PLINK set.
This package implements asymptotic methods related to
maximally selected statistics, with applications to SNP data.
Bivariate Gaussian genotype clustering and calling for Illumina
microarrays, building on the package 'mclust'. Pronounced snip-em-clust.
Creates plots of p-values using single SNP and/or haplotype data.
Main features of the package include options to display a linkage
disequilibrium (LD) plot and the ability to plot multiple datasets
simultaneously. Plots can be created using global and/or individual
haplotype p-values along with single SNP p-values. Images are created as
either PDF/EPS files.
A modification of Breiman and Cutler's classification random forests modified for SNP (Single Nucleotide Polymorphism) data (based on randomForest v4.6-7) to prevent X-chromosome SNP variable importance bias compared to autosomal SNPs by simulating the process of X chromosome inactivation. Classification is based on a forest of trees using random subsets of SNPs and other variables as inputs.
Write snpStats objects to disk in formats suitable for reading by
snphap, phase, mach, IMPUTE, beagle, and (almost) anything else that
expects a rectangular format.
This package queries the SNPs data sets and makes plots of
genes and SNPs.  This package allows users to access these data
sets once they have been compiled into one file and indexed
with Tabix (http://samtools.sourceforge.net/tabix.shtml). There
are functions to retrieve SNPs, subset them for specific
strains, obtain only SNPs that are polymorphic for a subset of
strains, plot SNPs and look for certain allele patterns in
SNPs. We have also added functions to access indels and
structural variants.
Stochastic Newton Sampler (SNS) is a Metropolis-Hastings-based, Markov Chain Monte Carlo sampler for twice differentiable, log-concave probability density functions (PDFs) where the proposal density function is a multivariate Gaussian resulting from a second-order Taylor-series expansion of log-density around the current point. The mean of the Gaussian proposal is the full Newton-Raphson step from the current point. A Boolean flag allows for switching from SNS to Newton-Raphson optimization (by choosing the mean of proposal function as next point). This can be used during burn-in to get close to the mode of the PDF (which is unique due to concavity). For high-dimensional densities, mixing can be improved via 'state space partitioning' strategy, in which SNS is applied to disjoint subsets of state space, wrapped in a Gibbs cycle. Numerical differentiation is available when analytical expressions for gradient and Hessian are not available. Facilities for validation and numerical differentiation of log-density are provided.
Scan statistics applied in social network data can be used to test the cluster characteristics among a social network.
Contains functions to perform various models and
methods for test equating. It currently implements the traditional
mean, linear and equipercentile equating methods, as well as the
mean-mean, mean-sigma, Haebara and Stocking-Lord IRT linking methods.
It also supports newest methods such that local equating, kernel
equating (using Gaussian, logistic and uniform kernels) with presmoothing,
and IRT parameter linking methods based on asymmetric item characteristic
functions. Functions to obtain both standard error of equating (SEE)
and standard error of equating difference between two equating
functions (SEED) are also implemented for the kernel method of
equating.
Allows objects to be stored on disc and automatically
recalled into memory, as required, by delayed assignment.
Specific and class specific multiple correspondence analysis on
survey-like data. Soc.ca is optimized to the needs of the social scientist and
presents easily interpretable results in near publication ready quality.
A suite of tools for collecting and constructing networks from
social media data. Provides easy-to-use functions for collecting data across
popular platforms (Instagram, Facebook, Twitter, and YouTube) and generating
different types of networks for analysis.
Social media search and analytic tool that takes one or multiple URL(s) and returns the information about the popularity and reach of the URL(s) on social media. The function get_socialmedia() retrieves the number of shares, likes, pins, and hits on Facebook (www.facebook.com), Pinterest (www.pinterest.com), StumbleUpon (www.stumbleupon.com), LinkedIn (www.linkedin.com), and Reddit (www.reddit.com). The package also includes dedicated functions for each social network platform and a function to resolve shortened URLs.
Generates social networks using either of two
approaches: using either pairwise distances or territorial area intersections.
Provides to sociologists (and related scientists) a toolbox to facilitate the construction of social position indicators from survey data. Social position indicators refer to what is commonly known as social class and social status. There exists in the sociological literature many theoretical conceptualisation and empirical operationalization of social class and social status. This first version of the package offers tools to construct the International Socio-Economic Index of Occupational Status (ISEI) and the Oesch social class schema. It also provides tools to convert several occupational classifications (PCS82, PCS03, and ISCO08) into a common one (ISCO88) to facilitate data harmonisation work, and tools to collapse (i.e. group) modalities of social position indicators.
SOD (Self-Organising-Deltoids) provides multidimensional scaling by gradually reducing the dimensionality of an initial space and using the resulting stress in the configuration to re-arrange nodes. Stress is calculated from the errors in the inter-node distances, and the sum of the stresses at each node is combined to create N-dimensional force vectors that direct the movement of nodes as the dimensionality is iteratively reduced.
Functions, examples and other software related to the book
"Software for Data Analysis: Programming with R". See
package?SoDA for an overview.
Variable and interaction selection are essential to classification in high-dimensional setting. In this package, we provide the implementation of SODA procedure, which is a forward-backward algorithm that selects both main and interaction effects under quadratic discriminant analysis and logistic regression model.
To implement two clustering methods, ODC and SODC, for
clustering datasets using optimal scoring, can also be used as
an dimension reduction tool.
Bindings to libsodium: a modern, easy-to-use software library for
encryption, decryption, signatures, password hashing and more. Sodium uses
curve25519, a state-of-the-art Diffie-Hellman function by Daniel Bernstein,
which has become very popular after it was discovered that the NSA had
backdoored Dual EC DRBG.
Este paquete tiene la finalidad de ayudar a aprender de una forma interactiva, teniendo ejemplos y la posibilidad de resolver nuevos al mismo tiempo. Apuntes de clase interactivos.
An extension of sensitivity, specificity, positive and negative
predictive value to continuous predicted and reference memberships in
[0, 1].
It contains soft clustering algorithms, in particular approaches derived from rough set theory: Lingras & West original rough k-means, Peters' refined rough k-means, and PI rough k-means. It also contains classic k-means and a corresponding illustrative demo.
Iterative methods for matrix completion that use nuclear-norm regularization. There are two main approaches.The one approach uses iterative soft-thresholded svds to impute the missing values. The second approach uses alternating least squares. Both have an "EM" flavor, in that at each iteration the matrix is completed with the current estimate. For large matrices there is a special sparse-matrix class named "Incomplete" that efficiently handles all computations. The package includes procedures for centering and scaling rows, columns or both, and for computing low-rank SVDs on large sparse centered matrices (i.e. principal components)
Sparsity Oriented Importance Learning (SOIL) provides an objective and informative profile of variable importances for high dimensional regression and classification models.
A collection of functions for reading data from USDA-NCSS soil databases.
Basic and model-based soil physical analyses.
This package provides functions to graphically represent
soil properties. Morphological data gathered in the field
such as horizon boundaries, root abundance and dimensions,
skeletal shape, abundance and dimension as well as
meaningful soil color may be represented via the plot
function. A lattice-based plot.element function has been
designed to represent depth function of a given variable.
This package contains functions for modeling Soil Organic
Matter decomposition in terrestrial ecosystems.
Methods and classes for processing and analyzing soil and plant infrared (MIR, alpha-MIR and VISNIR) spectroscopy readings based on the Africa Soil Information Services (AfSIS) project data.
"The Soil Texture Wizard" is a set of R functions designed to produce texture triangles (also called texture plots, texture diagrams, texture ternary plots), classify and transform soil textures data. These functions virtually allows to plot any soil texture triangle (classification) into any triangle geometry (isosceles, right-angled triangles, etc.). This set of function is expected to be useful to people using soil textures data from different soil texture classification or different particle size systems. Many (> 15) texture triangles from all around the world are predefined in the package. A simple text based graphical user interface is provided: soiltexture_gui().
It is a set of R implementations of parametric formulas of soil water
retention or conductivity curve. At the moment, only Van Genuchten (for
soil water retention curve) and Mualem (for hydraulic conductivity) were
implemented. See reference
\url{http://en.wikipedia.org/wiki/Water_retention_curve}.
Calculation methods of solar radiation and performance of photovoltaic systems from daily and intradaily irradiation data sources.
SOLAR is the standard software program to perform linkage and
association mappings of the quantitative trait loci (QTLs) in pedigrees of
arbitrary size and complexity. This package allows the user to exploit the
variance component methods implemented in SOLAR. It automates such routine
operations as formatting pedigree and phenotype data. It also parses the model
output and contains summary and plotting functions for exploration of the
results. In addition, solarius enables parallel computing of the linkage and
association analyses, that makes the calculation of genome-wide scans more
efficient. See <http://solar.txbiomedgenetics.org/> for more information about
SOLAR.
Calculation of solar zenith and azimuth angles.
Predicted solid earth tide displacements in the meridional,
zonal and vertical directions. Based on "Solid" from Dennis Milbert,
modified from "dehanttideinelMJD" by V. Dehant, S. Mathews, J. Gipson,
and C. Bruyninx.
Provides a set of functions for querying and parsing
data from Solr endpoints (local and remote), including search, faceting,
highlighting, stats, and 'more like this'.
Provides a set of functions for querying and parsing data
from 'Solr' (<http://lucene.apache.org/solr>) 'endpoints' (local and
remote), including search, 'faceting', 'highlighting', 'stats', and
'more like this'. In addition, some functionality is included for
creating, deleting, and updating documents in a 'Solr' 'database'.
Self-Organizing Map (with application in gene clustering).
This package provides an R implementation of the Self-Organising Migrating Algorithm, a general-purpose, stochastic optimisation algorithm. The approach is similar to that of genetic algorithms, although it is based on the idea of a series of ``migrations'' by a fixed set of individuals, rather than the development of successive generations. It can be applied to any cost-minimisation problem with a bounded parameter space, and is robust to local minima.
The stochastic (also called on-line) version of the Self-Organising
Map (SOM) algorithm is provided. Different versions of the
algorithm are implemented, for numeric and relational data and for
contingency tables. The package also contains many plotting
features (to help the user interpret the results) and a graphical
user interface based on shiny (which is also available on-line at
http://shiny.nathalievilla.org/sombrero).
some Brownian motions simulation functions
This package collects some procedures controlling the
Generalized Familywise Error Rate.
It's a collection of functions for Multiplicity Correction and Multiple Testing.
Multivariate mixed model equation solver for multiple random effects allowing the specification of variance covariance structures. ML/REML estimates are obtained using the Average Information (AI), Expectation-Maximization (EM), Newton-Raphson (NR), or Efficient Mixed Model Association (EMMA) algorithms. Designed for genomic prediction and genome wide association studies (GWAS) to include additive, dominance and epistatic relationship structures or other covariance structures in R, but also functional as a regular mixed model program. Multivariate models (multiple responses) can be fitted currently with NR, AI and EMMA algorithms allowing multiple random effects as well.
The package provides the plot function som.plot() to
create high quality visualisations of hexagonal Kohonen maps
(self-organising maps).
Estimate the abundance of cell clones from the
distribution of lengths of DNA fragments (as created by
sonication, whence `sonicLength').  The algorithm in
"Estimating abundances of retroviral insertion sites from
DNA fragment length data" by Berry CC, Gillet NA, Melamed
A, Gormley N, Bangham CR, Bushman FD. Bioinformatics;
2012 Mar 15;28(6):755-62 is implemented.  The
experimental setting and estimation details are described
in detail there. Briefly, integration of new DNA in a
host genome (due to retroviral infection or gene therapy)
can be tracked using DNA sequencing, potentially allowing
characterization of the abundance of individual cell
clones bearing distinct integration sites. The locations
of integration sites can be determined by fragmenting the
host DNA (via sonication or fragmentase), breaking the
newly integrated DNA at a known sequence, amplifying the
fragments containing both host and integrated DNA,
sequencing those amplicons, then mapping the host
sequences to positions on the reference genome. The
relative number of fragments containing a given position
in the host genome estimates the relative abundance of
cells hosting the corresponding integration site, but
that number is not available and the count of amplicons
per fragment varies widely.  However, the expected number
of distinct fragment lengths is a function of the
abundance of cells hosting an integration site at a given
position and a certain nuisance parameter. The algorithm
implicitly estimates that function to estimate the
relative abundance.
Collection of different single objective test functions
useful for benchmarks and algorithm development.
Load Russian economic indicators from the Archive of Economic and Social Data <http://sophist.hse.ru/>.
Provides functions to non-parametrically estimate the off-pulse interval of a source
function originating from a pulsar. The technique is based on a sequential application of P-values
obtained from goodness-of-fit tests for the uniform distribution, such as the Kolmogorov-Smirnov,
Cramer-von Mises, Anderson-Darling and Rayleigh goodness-of-fit tests.
Used to construct the URLs and parameters of 'Socrata Open Data API' <https://dev.socrata.com> calls, using the API's 'SoQL' parameter format. Has method-chained and sensical syntax. Plays well with pipes.
Estimation for longitudinal data following outcome dependent sampling using the sequential offsetted regression technique.  Includes support for binary, count, and continuous data.
SortableHTMLTables writes a data frame to an HTML file
that contains a sortable table. The sorting is done using the
jQuery plugin Tablesorter. The appearance is controlled through
a CSS file and several GIF's.
sortinghat is a classification framework to streamline the
evaluation of classifiers (classification models and algorithms) and seeks
to determine the best classifiers on a variety of simulated and benchmark
data sets. Several error-rate estimators are included to evaluate the
performance of a classifier. This package is intended to complement the
well-known 'caret' package.
Algorithms for Finnish open government data.
Search contributed R packages, sort by package.
sos4R is a client for Sensor Observation Services (SOS) as
specified by the Open Geospatial Consortium (OGC).  It allows
users to retrieve metadata from SOS web services and to
interactively create requests for near real-time observation
data based on the available sensors, phenomena, observations et
cetera using thematic, temporal and spatial filtering.
Tools to download data from the Sotkanet open data portal.
Basic functions for dealing with wav files and sound samples.
Functions to calculate indices for soundscape ecology and other ecology research that uses audio recordings.
The SoundexBR package provides an algorithm for decoding names
into phonetic codes, as pronounced in Portuguese. The goal is for
homophones to be encoded to the same representation so that they can be
matched despite minor differences in spelling. The algorithm mainly encodes
consonants; a vowel will not be encoded unless it is the first letter. The
soundex code resultant consists of a four digits long string composed by
one letter followed by three numerical digits: the letter is the first
letter of the name, and the digits encode the remaining consonants.
Construct a ranking of a set of treatments/groups by
gathering together information coming from several response variables.
It can be used with both balanced and unbalanced experiments
(with almost all test statistics) as well as in presence of either
continuous covariates or a stratifying (categorical) variable.
Analogous to source(), but works when given a Gist URL or
ID.
Implements a non-parametric source attribution model
to attribute cases of disease to sources in Bayesian framework with source and
type effects. Type effects are clustered using a Dirichlet Process. Multiple
times and locations are supported.
Tools for the reading and tokenization of R code.
The 'sourcetools' package provides both an R and C++ interface
for the tokenization of R code, and helpers for interacting
with the tokenized representation of R code.
Genomic and multi-environmental soybean data. Soybean Nested Association Mapping (SoyNAM) project dataset funded by the United Soybean Board (USB), pre-formatted for general analysis and genome-wide association analysis using the NAM package.
Classes and methods for spatial
data; the classes document where the spatial location information
resides, for 2D or 3D data. Utility functions are provided, e.g. for
plotting data as maps, spatial selection, as well as methods for
retrieving coordinates, for subsetting, print, summary, etc.
Provides methods for generating, exploring and executing seamless Phase II-III designs of Lai, Lavori and Shih using generalized likelihood ratio statistics. Includes pdf and source files that describe the entire R implementation with the relevant mathematical details.
Test the results of any given investment/expense combinations for a series of sliding-window periods of the S&P500 from 1950 to the present.
Implements the Sequential Predictions Algorithm
The package implements the model-based kernel machine
method for detecting gene-centric gene-gene interactions of Li
and Cui (2012).
Miscellaneous functions for analysing species association
and niche overlap.
Partial correlation estimation with joint sparse
regression model
SPACECAP is a user-friendly software package for
estimating animal densities using closed model
capture-recapture sampling based on photographic captures using
Bayesian spatially-explicit capture-recapture models. This
approach offers advantage such as: substantially dealing with
problems posed by individual heterogeneity in capture
probabilities in conventional capture-recapture analyses. It
also offers non-asymptotic inferences which are more
appropriate for small samples of capture data typical of
photo-capture studies.
undirected graph inference with missing data
This package provides an extension of conditional
independence (CIG) and directed acyclic graph (DAG) estimation
to the case where conditional relationships are (non-linear)
additive models.
Classes and methods for spatio-temporal data, including space-time regular lattices, sparse lattices, irregular data, and trajectories; utility functions for plotting data as map sequences (lattice or animation) or multiple time series; methods for spatial and temporal selection and subsetting, as well as for spatial/temporal/spatio-temporal matching or aggregation, retrieving coordinates, print, summary, etc.
SPACoDi is primarily designed to characterise the
structure and phylogenetic diversity of communities using
abundance or presence-absence data of species among community
plots.
Provides tools to construct and exploit spatially weighted context data. Spatial weights are derived by a Kernel function from a user-defined matrix of distances between contextual units. Spatial weights can then be applied either to precise contextual measures or to aggregate estimates based on micro-level survey data, to compute spatially weighted context data. Available aggregation functions include indicators of central tendency, dispersion, or inter-group variability, and take into account survey design weights. The package further allows combining the resulting spatially weighted context data with individual-level predictor and outcome variables, for the purposes of multilevel modelling. An ad hoc stratified bootstrap resampling procedure generates robust point estimates for multilevel regression coefficients and model fit indicators, and computes confidence intervals adjusted for measurement dependency and measurement error of aggregate estimates. As an additional feature, residual and explained spatial dependency can be estimated for the tested models.
A set of RStudio addins that are designed to be used in
combination with user-defined RStudio keyboard shortcuts. These
addins either:
1) insert text at a cursor position (e.g. insert
operators %>%, <<-, %$%, etc.),
2) replace symbols in selected pieces of text (e.g., convert
backslashes to forward slashes which results in stings like
"c:\data\" converted into "c:/data/") or
3) enclose text with special symbols (e.g., converts "bold" into
"**bold**") which is convenient for editing R Markdown files.
Easily implement a variety of simulation models, with a focus on
spatially explicit agent based models. These include raster-based,
event-based, and agent-based models. The core simulation components are
built upon a discrete event simulation framework that facilitates
modularity, and easily enables the user to include additional functionality
by running user-built simulation modules. Included are numerous tools to
visualize raster and other maps. The suggested package `fastshp` can be
installed with `install.packages("fastshp", repos="http://rforge.net",
type="source")`.
Implements methods for anticipating the emergence and eradication
of infectious diseases from surveillance time series. Also provides support
for computational experiments testing the performance of such methods.
Set of functions for sparse matrix algebra.
Differences with SparseM/Matrix are:
(1) we only support (essentially) one sparse matrix format,
(2) based on transparent and simple structure(s),
(3) tailored for MCMC calculations within GMRF.
(4) S3 and S4 like-"compatible"  ...     and it is fast.
Inference in mixed models, including GLMMs with spatial correlations and models with non-Gaussian random effects (e.g., Beta Binomial, or negative-binomial mixed models). Heteroscedasticity can further be fitted by a linear model. The algorithms are currently various Laplace approximations methods for ML or REML, in particular h-likelihood and penalized-likelihood methods.
Fit the spatial panel data models: the fixed effects, random
effects and between models.
Carries out a search for an optimal partition in terms of a
regular Boolean expression
This package performs robust nonparametric tests for rare variants
association analysis using summation of partition approaches that incorporate
gene-gene and gene-environmental interactions
We provide an efficient solver for estimating semiparametric generalized linear models.
Implements the sparse clustering methods of Witten and
Tibshirani (2010): "A framework for feature selection in
clustering"; published in Journal of the American Statistical
Association 105(490): 713-726.
Decide which server to connect to,
based on previous response times, and configuration.
A sparkline is a line chart, without axes and labels.
Its goal is to show the general shape of changes over time, or
another quantity. This package is an 'R' implementation
of the original shell project: <http://zachholman.com/spark/>.
Create sparklines and graphical tables for documents and websites.
Generate syntax for use with the sparklines package for
LaTeX.
Use SPARQL to pose SELECT or UPDATE queries to an end-point.
Provides functions to estimate kernel-smoothed relative risk functions and perform subsequent inference.
Implements the sparse biclustering proposal of Tan and Witten (2014), Sparse biclustering of transposable data. Journal of Computational and Graphical Statistics  23(4):985-1008.
Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization. Designed to incorporate mixed experimental and observational data with thousands of variables with either continuous or discrete observations.
A set of tools for representing and estimating sparse Bayesian networks from continuous and discrete data.
A collection of sparse and regularized discriminant analysis
methods intended for small-sample, high-dimensional data sets. The package
features the High-Dimensional Regularized Discriminant Analysis classifier.
Multidimensional scaling provides a means of uncovering a latent structure underlying observed data, while estimating the number of latent dimensions.  This package presents a means for scaling binary and count data, for example the votes and word counts for legislators.  Future work will include an EM implementation and extend this work to ordinal and continuous data.
SparseGrid is a package to create sparse grids for numerical integration, based on code from www.sparse-grids.de
Estimates Hessian of a scalar-valued function, and returns it
in a sparse Matrix format. The sparsity pattern must be known in advance. The
algorithm is especially efficient for hierarchical models with a large number of
heterogeneous units.
Performs sparse linear discriminant analysis for gaussians and mixture of gaussians models.
Coefficient estimation and model prediction based on the LASSO sparse
learning algorithm and its improved versions such as Bolasso, bootstrap ranking
LASSO, two-stage hybrid LASSO and others. These LASSO estimation procedures are
applied in the fields of variable selection, graphical modeling and ensemble
learning. The bagging LASSO model uses a Monte Carlo cross-entropy algorithm to
determine the best base-level models and improve predictive performance.
Use RcppEigen to fit least trimmed squares
regression models with an L1 penalty in order to obtain
sparse models.
Some basic linear algebra functionality for sparse matrices is
provided:  including Cholesky decomposition and backsolving as well as
standard R subsetting and Kronecker products.
Computes multivariate normal (MVN) densities, and
samples from MVN distributions, when the covariance or
precision matrix is sparse.
Sparsenet uses the MC+ penalty of Zhang. It computes the regularization surface over both the family parameter and the tuning parameter by coordinate descent.
Sparse modeling provides a mean selecting a small number of non-zero effects from a large possible number of candidate effects.  This package includes a suite of methods for sparse modeling: estimation via EM or MCMC, approximate confidence intervals with nominal coverage, and diagnostic and summary plots.  The method can implement sparse linear regression and sparse probit regression.  Beyond regression analyses, applications include subgroup analysis, particularly for conjoint experiments, and panel data. Future versions will include extensions to  models with truncated outcomes, propensity score, and instrumental variable analysis.
Sparse-aware maximum likelihood for structural equation models in inferring gene regulatory networks
Wrapper around the 'SVDLIBC' library for (truncated) singular value decomposition of a sparse matrix.
Currently, only sparse real matrices in Matrix package format are supported.
Fast algorithm for fitting solution paths of sparse linear SVM with lasso or elastic-net regularization generate sparse solutions.
Computes sparse vector autoregressive coefficients and precision
matrices for time series chain graphical models.
A wrapper for sparse VAR/VECM time series models estimation
using penalties like ENET, SCAD and MCP.
Computer simulations are becoming a popular technique to use in attempts to further our understanding of complex systems. SPARTAN, described in our 2013 publication in PLoS Computational Biology, provides code for four techniques described in available literature which aid the analysis of simulation results, at both single and multiple timepoints in the simulation run. The first technique addresses aleatory uncertainty in the system caused through inherent stochasticity, and determines the number of replicate runs necessary to generate a representative result. The second examines how robust a simulation is to parameter perturbation, through the use of a one-at-a-time parameter analysis technique. Thirdly, a latin hypercube based sensitivity analysis technique is included which can elucidate non-linear effects between parameters and indicate implications of epistemic uncertainty with reference to the system being modelled. Finally, a further sensitivity analysis technique, the extended Fourier Amplitude Sampling Test (eFAST) has been included to partition the variance in simulation results between input parameters, to determine the parameters which have a significant effect on simulation behaviour. Version 1.3 adds support for Netlogo simulations, aiding simulation developers who use Netlogo to build their simulations perform the same analyses. We have also added user support through the group spartan-group[AT]york[DOT]ac[DOT]uk. Version 2.0 added the ability to read all simulations in from a single CSV file in addition to the prescribed folder structure in previous versions.
Fit spatial CAR count regression models using MCMC
This package provides functionality for spatio-temporal modeling of large data sets. A Gaussian process in space and time is defined through a stochastic partial differential equation (SPDE). The SPDE is solved in the spectral space, and after discretizing in time and space, a linear Gaussian state space model is obtained. When doing inference, the main computational difficulty consists in evaluating the likelihood and in sampling from the full conditional of the spectral coefficients, or equivalently, the latent space-time process. In comparison to the traditional approach of using a spatio-temporal covariance function, the spectral SPDE approach is computationally advantageous. This package aims at providing tools for two different modeling approaches. First, the SPDE based spatio-temporal model can be used as a component in a customized hierarchical Bayesian model (HBM). The functions of the package then provide parameterizations of the process part of the model as well as computationally efficient algorithms needed for doing inference with the HBM. Alternatively, the adaptive MCMC algorithm implemented in the package can be used as an algorithm for doing inference without any additional modeling. The MCMC algorithm supports data that follow a Gaussian or a censored distribution with point mass at zero. Covariates can be included in the model through a regression term.
Graphs (or networks) and graph component
calculations for spatial locations in *D.
Functions for kriging and point pattern analysis.
Functions that compute the spatial covariance matrix for the matern and power classes of spatial models, for data that arise on rectangular units.  This code can also be used for the change of support problem and for spatial data that arise on irregularly shaped regions like counties or zipcodes by laying a fine grid of rectangles and aggregating the integrals in a form of Riemann integration.
Utilities to support spatial data manipulation, query, sampling
and modelling. Functions include models for species population density, download
utilities for climate and global deforestation spatial products, spatial
smoothing, multivariate separability, point process model for creating pseudo-
absences and sub-sampling, polygon and point-distance landscape metrics,
auto-logistic model, sampling models, cluster optimization and statistical
exploratory tools.
Methods and data for cluster detection and disease mapping.
Tools for the statistical modelling of spatial extremes using max-stable processes, copula or Bayesian hierarchical models.
Filter matrices or (three dimensional) array data using different convolution kernels.
This package fits a hierarchical spatial model for the generalized extreme value distribution with the option of model averaging over the space of covariates.
Edge-corrected kernel density estimation and binary kernel
regression estimation for multivariate spatial point process
data
Network based diffusion analysis (NBDA) allows inference on
the asocial and social transmission of information.  This may involve
the social transmission of a particular behaviour such as tool use, for example.
For the NBDA, the key parameters estimated are the social effect and baseline rate
parameters.  The baseline rate parameter gives the rate at which the behaviour
is first performed (or acquired) asocially amongst the individuals in a given population.
The social effect parameter quantifies the effect of the social associations amongst
the individuals on the rate at which each individual first performs or displays
the behaviour.  Spatial NBDA involves incorporating spatial information in the analysis.
This is done by incorporating social networks derived from
spatial point patterns (of the home bases of the individuals under study).  In addition,
a spatial covariate such as vegetation cover, or slope may be included in the modelling
process.
This package contains test and estimates of location,
tests of independence, tests of sphericity and several
estimates of shape all based on spatial signs, symmetrized
signs, ranks and signed ranks.
This package provides tools to assess the association between two spatial processes.
Currently, three methodologies are implemented: An adapted t-test to perform hypothesis
testing about the independence between the processes, a suitable nonparametric correlation
coefficient, and the codispersion coefficient. SpatialPack gives methods to complement
methodologies that are available in geoR for one spatial process.
Computes spatial position models: Stewart potentials, Reilly
catchment areas, Huff catchment areas.
Bayesian Estimation of Spatial Probit and Tobit Models.
Summaries for measuring segregation/mingling in multitype spatial point patterns with graph based neighbourhood description.
Included indices: Mingling, Shannon, Simpson (also the non-spatial)
Included functionals: Mingling, Shannon, Simpson, ISAR, MCI.
Included neighbourhoods: Geometric, k-nearest neighbours, Gabriel, Delaunay.
Provides functions implementing the pairwise M-estimator for
parametric models for stable tail dependence functions described in "An
M-estimator of spatial tail dependence"
(Einmahl, J.H.J., Kiriliouk, A., Krajina, A. and Segers, J., 2014).
See http://arxiv.org/abs/1403.1975.
Spatial functions meant to enhance the core functionality of the
package "raster", including a parallel processing engine for use with
rasters.
Tools for spatial data analysis.  Emphasis on kriging.  Provides functions for prediction and simulation.  Intended to be relatively straightforward, fast, and flexible.
Spatial forecast verification arose from verifying high-resolution forecasts, where coarser-resolution models generally are favored even when a human forecaster finds the higher-resolution model to be considerably better.  Most newly proposed methods, which largely come from image analysis, computer vision, and similar, are available, with more on the way.
Utilities that estimate, predict and cross-validate the
spatio-temporal model developed for MESA Air.
Provide regularized maximum covariance analysis incorporating smoothness, sparseness and orthogonality of couple patterns by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data.
Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data.
Analysis of field trial experiments by modelling spatial trends using two-dimensional Penalised spline (P-spline) models.
Bayesian inference for parametric proportional hazards spatial
survival models; flexible spatial survival models.
Tools to convert from specific formats to more general forms of
spatial data. Using tables to store the actual entities present in spatial
data provides far greater flexibility, and the functions here deliberately
minimize the level of interpretation applied, leaving that for specific
applications. Includes round-trip for 'Spatial' classes and long-form
tables, analogous to 'ggplot2::fortify'.
Fits univariate and multivariate spatio-temporal
models with Markov chain Monte Carlo (MCMC).
Provides several Bayesian survival models for spatial/non-spatial survival data: marginal Bayesian Nonparametric models, marginal Bayesian proportional hazards models, generalized accelerated failure time frailty models, and standard semiparametric frailty models within the context of proportional hazards, proportional odds and accelerated failure time.
Evaluation of control charts by means of
the zero-state, steady-state ARL (Average Run Length) and RL quantiles.
Setting up control charts for given in-control ARL. The control charts
under consideration are one- and two-sided EWMA, CUSUM, and
Shiryaev-Roberts schemes for monitoring the mean of normally
distributed independent data. ARL calculation
of the same set of schemes under drift are added.
Other charts and parameters are in preparation.
Further SPC areas will be covered as well
(sampling plans, capability indices ...).
Calibration of thresholds of control charts such as
CUSUM charts based on past data, taking estimation error into account.
A new reduced-rank LDA method which works for high dimensional multi-class data.
Spatial coverage sampling and random sampling from compact
geographical strata created by k-means.
Provides a covariance estimator for multivariate normal
data that is sparse and positive definite.  Implements the
majorize-minimize algorithm described in Bien, J., and
Tibshirani, R. (2011), "Sparse Estimation of a Covariance
Matrix," Biometrika. 98(4). 807--820.
This package computes the sparse principal component regression. The regularization parameters are optimized by cross-validation.
The Semi Parametric Piecewise Distribution blends the Generalized Pareto Distribution for the tails with a kernel based interior.
A collection of functions to create spatial weights matrix
objects from polygon contiguities, from point patterns by distance and
tessellations, for summarizing these objects, and for permitting their
use in spatial data analysis, including regional aggregation by minimum
spanning tree; a collection of tests for spatial autocorrelation,
including global Moran's I, APLE, Geary's C, Hubert/Mantel general cross
product statistic, Empirical Bayes estimates and Assunção/Reis Index,
Getis/Ord G and multicoloured join count statistics, local Moran's I
and Getis/Ord G, saddlepoint approximations  and exact tests for global
and local Moran's I; and functions for estimating spatial simultaneous
autoregressive (SAR) lag and error models, impact measures for lag
models, weighted and unweighted SAR and CAR spatial regression models,
semi-parametric and Moran eigenvector spatial filtering, GM SAR error
models, and generalized spatial two stage least squares models.
Methods for 'dplyr' verbs for 'sp' 'Spatial' classes. The basic
verbs that modify data attributes, remove or re-arrange rows are supported
and provide complete 'Spatial' analogues of the input data. The group by
and summarize workflow returns a non-topological spatial union. There is
limited support for joins, with left and inner to copy attributes from
another table.
Functions for estimating split-duration regression models and
various associated generic function methods.
A spatio-dynamic modelling package that focuses on three
characteristic wetland plant communities in a semiarid Mediterranean
wetland in response to hydrological pressures from the catchment. The
package includes the data on watershed hydrological pressure and the
initial raster maps of plant communities but also allows for random initial
distribution of plant communities. Ongoing developments of the package
focus on offering easy to use tools for creating other spatio-dynamic
models.
Implements stochastic proximity embedding as described by
Agrafiotis et al. in PNAS, 2002, 99, pg 15869 and J. Comput. Chem., 2003,24, pg 1215
We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data. Related publication is available at http://www.biomedcentral.com/1471-2105/12/405/.
Alternative to the kernlab::specc function. Includes a spectral clustering implementation, a locally adapted kernel function akin to what is already proposed in kernlab, and an optional procedure that automatically estimates the optimal number of clusters. Several sample data sets are also included.
Utility functions for spectroscopy. 1. Functions to simulate
spectra for use in teaching or testing. 2. Functions to process files created by
'LoggerPro' and 'SpectraSuite' software.
SPECIES is an R package for estimation of species richness
or diversity.
Preparation of species occurrences and distribution data for the use in phylogenetic analyses. SpeciesgeocodeR is built for data cleaning, data exploration and data analysis and especially suited for biogeographical and ecological questions on large datasets. The package includes the easy creation of summary-tables and -graphs and geographical maps, the automatic cleaning of geographic occurrence data, the calculating of coexistence matrices and species ranges (EOO) as well as mapping diversity in geographic areas.
Mixtures using BFGS and analytical derivatives
The package helps to test the specificity of personality trait-outcome (or trait-trait) associations by comparing the observed associations to those obtained using randomly created personality scales.
Provides a set of methods for metabolomics
data analysis, including data loading in different formats,
pre-processing, metabolite identification, univariate and multivariate
data analysis, machine learning and feature selection. Case studies
can be found on the website: http://darwin.di.uminho.pt/metabolomics .
A collection of new forecast verification routines for the SPECS FP7 project. The emphasis is on comparative verification of ensemble forecasts.
Routines for creating, manipulating, and performing
Bayesian inference about Gaussian processes in
one and two dimensions using the Fourier basis approximation:
simulation and plotting of processes, calculation of
coefficient variances, calculation of process density,
coefficient proposals (for use in MCMC).  It uses R environments to
store GP objects as references/pointers.
Implements the diffusion map method of dimensionality reduction and spectral method of combining multiple diffusion maps, including creation of the spectra and visualization of maps.
Contains some implementations of Singular Spectrum Analysis (SSA) for the gapfilling and spectral decomposition of time series. It contains the code used by Buttlar et. al. (2014), Nonlinear Processes in Geophysics. In addition, the iterative SSA gapfilling method of Kondrashov and Ghil (2006) is implemented. All SSA calculations are done via the truncated and fast SSA algorithm of Korobeynikov (2010) (package 'Rssa').
Spectra visualization, organizer and data preparation
from within R or stand-alone. Binary (application) part is
installed separately by running spnInstallApp()
immediately after installing the package.
From output files obtained from the software ModestR, the relative contribution of factors to explain species distribution is depicted using several plots. A global geographic raster file for each environmental variable may be also obtained with the mean relative contribution, considering all species present in each raster cell, of the factor to explain species distribution. Finally, for each variable it is also possible to compare the frequencies of any variable obtained in the cells where the species is present with the frequencies of the same variable in the cells of the extent.
Fitting linear models and generalized linear models to large data sets by updating algorithms.
The package performs estimation and testing of the
treatment effect in a 2-group randomized clinical trial with a
quantitative, dichotomous, or right-censored time-to-event
endpoint. The method improves efficiency by leveraging baseline
predictors of the endpoint. The inverse probability weighting
technique of Robins, Rotnitzky, and Zhao (JASA, 1994) is used
to provide unbiased estimation when the endpoint is missing at
random.
A set of functions for computing potential evapotranspiration and several widely used drought indices including the Standardized Precipitation-Evapotranspiration Index (SPEI).
Provides some easy-to-use functions to interpolate species range based on species occurrences and to estimate centers of biodiversity.
This package implements spatial error estimation and
permutation-based variable importance measures for predictive
models using spatial cross-validation and spatial block
bootstrap.
A set of tools for estimation of various spatial specifications of
stochastic frontier models.
Interpreted interface between GRASS 6+ geographical
information system and R, based on starting R from within the GRASS
environment, or running free-standing R in a temporary GRASS location;
the package provides facilities for using all GRASS commands from the
R command line. This package may not be used for GRASS 7, for which
rgrass7 should be used.
A collection of statistical hypothesis tests and other
techniques for identifying certain spatial relationships/phenomena in
DNA sequences. In particular, it provides tests and graphical methods for determining
whether or not DNA sequences comply with Chargaff's second parity rule
or exhibit purine-pyrimidine parity. In addition, there are functions for
efficiently simulating discrete state space Markov chains and testing
arbitrary symbolic sequences of symbols for the presence of first-order
Markovianness.
Also, it has functions for counting words/k-mers (and cylinder patterns) in
arbitrary symbolic sequences. Functions which take a DNA sequence as input
can handle sequences stored as SeqFastadna objects from the 'seqinr' package.
Functions for computing geographically weighted
regressions are provided, based on work by Chris
Brunsdon, Martin Charlton and Stewart Fotheringham.
Various functions for creating spherical coordinate system plots via extensions to rgl.
Provides several methods to integrate functions over the unit
sphere and ball in n-dimensional Euclidean space.  Routines for converting to/from
multivariate polar/spherical coordinates are also provided.
Spherical K-function for point-pattern analysis on the sphere.
This package carries out spherical wavelet transform
developed by Li (1999) and Oh (1999), and implements wavelet
thresholding approaches proposed by Oh and Li (2004).
Generalized Method of Moment estimation of Cliff-Ord-type
spatial autoregressive models with and without heteroskedastic
innovations
The SNP Panel Identification Assay (SPIA) is a package that enables an accurate determination of cell line identity from the genotype of single nucleotide polymorphisms (SNPs). The SPIA test allows to discern when two cell lines are close enough to be called similar and when they are not. Details about the method are available at "Demichelis et al. (2008) SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines. Nucleic Acids Res., 3, 2446-2456".
A package for the analysis of species limits and DNA barcoding data
Fits and simulates data from our predator preferences model, <DOI:10.1007/s10651-016-0341-3>.
Calculate the Standardized Precipitation Index (SPI) for monitoring drought, using Artificial Intelligence techniques (SPIGA) and traditional numerical technique Maximum Likelihood (SPIML).  For more information see: http://drought.unl.edu/monitoringtools/downloadablespiprogram.aspx.
Spike and slab for prediction and variable selection in
linear regression models. Uses a generalized elastic net for
variable selection.
Bayesian variable selection, model choice, and regularized
estimation for (spatial) generalized additive mixed regression models
via stochastic search variable selection with spike-and-slab priors.
An optimal weighting strategy to compute
simulation-efficient shortest probability intervals (spins).
Implements a generative model that uses a
spike-and-slab like prior distribution obtained by multiplying a
deterministic binary vector. Such a model allows an EM algorithm,
optimizing a type-II log-likelihood.
The Splancs package was written as an enhancement to S-Plus for display and analysis of spatial point pattern data; it has been ported to R and is in "maintenance mode".
Online data collection tools like Google Forms often export
multiple-response questions with data concatenated in cells. The
concat.split (cSplit) family of functions splits such data into
separate cells. The package also includes functions to stack groups
of columns and to reshape wide data, even when the data are
"unbalanced"---something which reshape (from base R) does not handle,
and which melt and dcast from reshape2 do not easily handle.
ML and GM estimation and diagnostic testing of econometric models for spatial panel data.
This package provides functions for fitting a Sparse
Partial Least Squares Regression and Classification
Currently there are many functions in S-PLUS that are
missing in R. To facilitate the conversion of S-PLUS packages
to R packages, this package provides some missing S-PLUS
functionality in R.
A collection of classes and methods for working with
times and dates. The code was originally available in S-PLUS.
A collection of classes and methods for working with time series.
The code was originally available in S-PLUS.
Installs SPM12 to the R library directory and has associated functions for fMRI and general imaging utilities, called through MATLAB.
A set of functions is provided for 1) the stratum lengths analysis along a chosen direction, 2) fast estimation of continuous lag spatial Markov chains model parameters and probability computing (also for large data sets), 3) transition probability maps and transiograms drawing, 4) simulation methods for categorical random fields.
Implements the method of general semiparametric maximum likelihood estimation for logistic models in case-mother control-mother designs.
Facilitates the rendering of networks for which nodes have a specific position on a map (cities, participants in a political debate, etc.). Map data and network data are stored together in a single object which handles the match between network nodes and their respective position on the map. The plot method renders both the map and the network data. Several networks can be plot simultaneously. The graphic is highly customisable and the legend is automatically printed. Map data have to be supplied as 'SpatialPolygons' objects (from the 'sp' package) and network data as 'named matrix'.
A programmatic interface to many species occurrence data sources,
including 'GBIF', 'USGS's' 'BISON', 'iNaturalist', Berkeley 'Ecoinformatics'
Engine 'eBird', 'AntWeb', and 'iDigBio'. Includes functionality for
retrieving species occurrence data, and combining that data.
Utilities for use with 'spocc'. Includes functions to
clean occurrence data, find and remove duplicates, combine data,
and make maps with base 'R' plots, 'ggplot2', and various interactive
maps.
SPODT is a spatial partitioning method based on oblique decision trees, in order to classify study area into zones of different risks, determining their boundaries
R implementation of the methods described in "A rank-based
empirical likelihood approach to two-sample proportional odds
model and its goodness-of-fit" by Zhong Guan and Cheng Peng,
Journal of Nonparametric Statistics, to appear.
The aim of this package is to provide infrastructure for
sports analysis. Anyway, currently it is a selection of data
sets, functions to fetch sports data, examples, and demos --
with the ambition to develop bit by bit a set of classes to
represent general concepts of sports analysis.
The Sequential Parameter Optimization Toolbox provides a set of
tools for Parameter-tuning, based on modelling techniques, DoE and statistical
methods.
Sparse arrays interpreted as multivariate polynomials.
The Statistical Package for REliability Data Analysis (SPREDA) implements recently-developed statistical methods for the analysis of reliability data. Modern technological developments, such as sensors and smart chips, allow us to dynamically track product/system usage as well as other environmental variables, such as temperature and humidity. We refer to these variables as dynamic covariates. The package contains functions for the analysis of time-to-event data with dynamic covariates and degradation data with dynamic covariates. The package also contains functions that can be used for analyzing time-to-event data with right censoring, and with left truncation and right censoring. Financial support from NSF and DuPont are acknowledged.
The recent advancement of high-throughput technologies has led to frequent utilization of gene expression and other "omics" data for toxicological, diagnostic or prognostic studies in and clinical applications. Unlike in classical predictions where the number of samples is greater than the number of variables (n>p), the challenge faced with prediction using "omics" data is that the number of parameters greatly exceeds the number of samples (p>>n). To solve this curse of dimensionality problem, several predictive functions have been proposed for direct and probabilistic classification and survival predictions. Nevertheless, these predictive functions have been shown to perform differently across datasets. Comparing predictive functions and choosing the best is computationally intensive and leads to selection bias. Thus, the question which function should one choose for a given dataset is to be ascertained. This package implements the approach proposed by Jong et al., (2016) to address this question.
Calculate species richness functions for rarefaction and
extrapolation.
SPRINT (Simple Parallel R INTerface) is a parallel
framework for R. It provides a High Performance Computing (HPC)
harness which allows R scripts to run on HPC clusters. SPRINT
contains a library of selected R functions that have been
parallelized. Functions are named after the original R function
with the added prefix 'p', i.e. the parallel version of cor()
in SPRINT is called pcor(). Call to the parallel R functions
are included directly in standard R scripts.
SPRINT contains functions for correlation (pcor), partitioning around medoids (ppam),
apply (papply), permutation testing (pmaxT), bootstrapping (pboot), random forest (prandomForest),
rank product (pRP) and hamming distance (pstringdistmatrix).
The main function of this package builds prognostic models that consider interactions by combining available statistical components. Furthermore, it provides a function for evaluating the relevance of the selected interactions by resampling techniques.
Robust dimension reduction methods for regression and discriminant analysis are implemented that yield estimates with a partial least squares alike interpretability. Partial robust M regression (PRM) is robust to both vertical outliers and leverage points. Sparse partial robust M regression (SPRM) is a related robust method with sparse coefficient estimate, and therefore with intrinsic variable selection. For binary classification related discriminant methods are PRM-DA and SPRM-DA.
R functions to mine sparse models from data.
Perform Wald's Sequential Probability Ratio Test on variables with a Normal, Bernoulli, Exponential and Poisson distribution. Plot acceptance and continuation regions, or create your own with the help of closures.
Methods to optimize spatial sample configurations using spatial simulated annealing. Multiple
objective functions are implemented for various purposes, such as variogram estimation, spatial trend
estimation, and spatial interpolation. A general purpose spatial simulated annealing function enables the
user to define his/her own objective function.
Program uses method of polynomial of variable degrees to interpolate gridded data preserving monotonicity and/or convexity or none. Method is implemented for univariate and bivariate cases. If values of derivatives are provided, spline will fix them,if not program will estimate them numerically. Package written purely in R.
SPSL package provides functionality for labeling of
percolation clusters on 2D & 3D square lattice with various
lattice size, relative fraction of accessible sites (occupation
probability), iso- & anisotropy, von Neumann & Moore
(1,d)-neighborhood
Produces Slepian smoother basis objects for use in Generalized Additive Models, as estimated by package:mgcv.
This group of functions implements algorithms for design and
analysis of probability surveys.  The functions are tailored for Generalized
Random Tessellation Stratified survey designs.
This package collects algorithms related to Sierpinski pedal triangle (SPT).
Fits, spatially predicts, and temporally forecasts space-time data using Gaussian Process (GP): (1) spatially varying coefficient process models and (2) spatio-temporal dynamic linear models.
Implements nonparametric hypothesis tests to check isotropy and
symmetry properties for two-dimensional spatial data.
spThin is a set of functions that can be used to spatially thin
species occurrence data. The resulting thinned data can be used in ecological
modeling, such as ecological niche modeling.
Fits, spatially predicts and temporally forecasts large amounts of space-time data using  [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal big-n problems.
Implements semiparametric transformation model two-phase estimation using calibration weights.
This package provides functions and datasets from the book "Introduction to Scientific Programming and Simulation Using R".
Sparse Quadratic Discriminant Analysis (SQDA) can be performed. In SQDA, the covariance matrix are assumed to be block-diagonal.And, for each block, sparsity assumption is imposed on the covariance matrix. It is useful in high-dimensional setting.
Description: Manipulate R data frames using SQL.
sqliter helps users, mainly data munging practioneers, to organize
their sql calls in a clean structure. It simplifies the process of
extracting and transforming data into useful formats.
A rendering tool for parameterized SQL that also translates into
different SQL dialects.  These dialects include Sql Server, Oracle,
PostgreSql, Amazon RedShift, and Microsoft PDW.
This package provides utilities for working with a library of SQL
files.
Normalization based a subset of negative control probes as
described in 'Subset quantile normalization using negative
control features'. Wu Z, Aryee MJ, J Comput Biol. 2010
Oct;17(10):1385-95 [PMID 20976876].
Algorithms for accelerating the convergence of slow,
monotone sequences from smooth, contraction mapping such as the
EM algorithm. It can be used to accelerate any smooth, linearly
convergent acceleration scheme.  A tutorial style introduction
to this package is available in a vignette on the CRAN download
page or, when the package is loaded in an R session, with
vignette("SQUAREM").
Functions for color-based visualization of multivariate data, i.e. colorgrams or heatmaps.  Lower-level functions  map numeric values to colors, display a matrix as an array of colors, and draw color keys.  Higher-level plotting functions generate a bivariate histogram, a dendrogram aligned with a color-coded matrix, a triangular distance matrix, and more.
A simulation-based tool made to help researchers to become familiar with
multilevel variations, and to build up sampling designs for their study.
This tool has two main objectives: First, it provides an educational tool useful for students,
teachers and researchers who want to learn to use mixed-effects models.
Users can experience how the mixed-effects model framework can be used to understand
distinct biological phenomena by interactively exploring simulated multilevel data.
Second, it offers research opportunities to those who are already familiar with
mixed-effects models, as it enables the generation of data sets that users may download
and use for a range of simulation-based statistical analyses such as power
and sensitivity analysis of multilevel and multivariate data.
This package (sra) provides a set of tools to analyse artificial-selection response datasets. The data typically feature for several generations the average value of a trait in a population, the variance of the trait, the population size and the average value of the parents that were chosen to breed. Sra implements two families of models aiming at describing the dynamics of the genetic architecture of the trait during the selection response. The first family relies on purely descriptive (phenomenological) models, based on an autoregressive framework. The second family provides different mechanistic models, accounting e.g. for inbreeding, mutations, genetic and environmental canalization, or epistasis. The parameters underlying the dynamics of the time series are estimated by maximum likelihood. The sra package thus provides (i) a wrapper for the R functions mle() and optim() aiming at fitting in a convenient way a predetermined set of models, and (ii) some functions to plot and analyze the output of the models.
Implementation of the SRCS method for a color-based visualization of the
results of multiple pairwise tests on a large number of problem configurations, proposed in:
I.G. del Amo, D.A. Pelta. SRCS: a technique for comparing multiple algorithms under several
factors in dynamic optimization problems. In: E. Alba, A. Nakib, P. Siarry
(Eds.), Metaheuristics for Dynamic Optimization. Series: Studies in
Computational Intelligence 433, Springer, Berlin/Heidelberg, 2012.
Draws scaled rectangle diagrams to represent a 2^k contingency
table, for k<=6
This package contains a collection of functions to perform
nonparametric estimation of receiver operating characteristic
(ROC) curves for continuous data.
This package implements the SRRS method introduced in Phoa (2013) into a graphical user interface (GUI) R program.
Use piping, verbs like 'group_by' and 'summarize', and other
'dplyr' inspired syntactic style when calculating summary statistics on survey
data using functions from the 'survey' package.
Develops a framework for fisheries stock assessment simulation
testing with Stock Synthesis 3 (SS3).
Procedures for analyzing simultaneous signals, e.g., features that are simultaneously significant in two different studies. Includes methods for detecting simultaneous signals, for identifying them under false discovery rate control, and for leveraging them to improve prediction.
A set of functions to calculate sample size for two-sample difference in means tests. Does adjustments for either nonadherence or variability that comes from using data to estimate parameters.
Provides the spatial sign correlation and the two-stage spatial sign correlation as well as a one-sample test for the correlation coefficient.
ssd calculates the sample size needed to detect the differences between two sets of unordered categorical data.
Functions to visually and statistically analyze single system data.
Allows to map species richness and endemism based on stacked
species distribution models (SSDM). Individuals SDMs can be created using a
single or multiple algorithms (ensemble SDMs). For each species, an SDM can
yield a habitat suitability map, a binary map, a between-algorithm variance
map, and can assess variable importance, algorithm accuracy, and between-
algorithm correlation. Methods to stack individual SDMs include summing
individual probabilities and thresholding then summing. Thresholding can be
based on a specific evaluation metric or by drawing repeatedly from a Bernoulli
distribution. The SSDM package also provides a user-friendly interface.
Performs structured OLS (sOLS) and structured SIR (sSIR).
Spatial Stochastic Frontier Analysis (SSFA) is an original method for controlling the spatial heterogeneity in Stochastic Frontier Analysis (SFA) models, for cross-sectional data, by splitting the inefficiency term into three terms: the first one related to spatial peculiarities of the territory in which each single unit operates, the second one related to the specific production features and the third one representing the error term.
Fits complex parametric models using the method proposed by Cox and Kartsonaki (2012) without likelihoods.
This package provides utility functions for system command
execution, both locally and remotely using ssh/scp. The command
output is captured and provided to the caller. This functionality is
intended to streamline calling shell commands from R, retrieving and
using their output, while instrumenting the calls with appropriate
error handling. NOTE: this first version is limited to unix with local
and remote systems running bash as the default shell.
This package contains a set of functions that calculates
appropriate sample sizes for one-sample t-tests, two-sample t-tests,
and F-tests for microarray experiments based on desired power while
controlling for false discovery rates. For all tests, the standard
deviations (variances) among genes can be assumed fixed or random.
This is also true for effect sizes among genes in one-sample and two
sample experiments. Functions also output a chart of power versus sample
size, a table of power at different sample sizes, and a table of critical
test values at different sample sizes.
We propose a procedure for sample size calculation while
controlling false discovery rate for RNA-seq experimental design. Our
procedure depends on the Voom method proposed for RNA-seq data analysis
by Law et al. (2014) <DOI:10.1186/gb-2014-15-2-r29> and the sample size
calculation method proposed for microarray experiments by Liu and Hwang
(2007) <DOI:10.1093/bioinformatics/btl664>. We develop a set of functions
that calculates appropriate sample sizes for two-sample t-test for RNA-seq
experiments with fixed or varied set of parameters. The outputs also contain a
plot of power versus sample size, a table of power at different sample sizes,
and a table of critical test values at different sample sizes.
To install this package, please use
'source("http://bioconductor.org/biocLite.R"); biocLite("ssizeRNA")'.
Semi-supervised learning has attracted the attention of machine learning community because of its high accuracy with less annotating effort compared with supervised learning.The question that semi-supervised learning wants to address is: given a relatively small labeled dataset and a large unlabeled dataset, how to design classification algorithms learning from both ? This package is a collection of some classical semi-supervised learning algorithms in the last few decades.
Performs the EM algorithm for regression models using Skew Scale Mixtures of Normal Distributions.
Package provides a set of tools for robust estimation and inference for models with sample selectivity.
Geostatistical modeling for data on stream networks, including models based on in-stream distance.  Models are created using moving average constructions. Spatial linear models, including covariates, can be fit with ML or REML.  Mapping and other graphical functions are included.
R package for computing the spherical smoothing splines
An integrated set of tools to estimate the size of a networked population based on respondent-driven sampling data. The package is part of the "RDS Analyst" suite of packages for the analysis of respondent-driven sampling data.
Takeya Semantic Structure Analysis (TSSA) and Sakai Sequential Relation Analysis (SSRA)
for polytomous items for examining whether each pair of items has a sequential or equal
relation. Package includes functions for generating a sequential relation table and a
treegram to visualize sequential or equal relations between pairs of items.
SSRAT is a computer program for two-dimensional sociometric status
determination with rating scales. For each person assessed, SSRAT computes
probability distributions of the total scores for `sympathy' (S),
`antipathy' (A), `social preference' (P) and `social impact' (I), and
applies the criteria for sociometric status categorization.
Calculates the power and sample size based on the difference in Restricted Mean Survival Times.
Tools to import survey files
in the .sss (triple-s) format. The package provides the function
read.sss() that reads the .asc and .sss files of a
triple-s survey data file.  The package is experimental
- feedback, issues and bug reports are welcome.
Fast iterative thresholding sparse SVD, together with an initialization algorithm
Set of tools to fit a semi-parametric regression model suitable for analysis of data sets in which the response variable is continuous, strictly positive, asymmetric and possibly, censored. Under this setup, both the median and the skewness of the response variable distribution are explicitly modeled by using semi-parametric functions, whose non-parametric components may be approximated by natural cubic splines or P-splines. Supported distributions for the model error include log-normal, log-Student-t, log-power-exponential, log-hyperbolic, log-contaminated-normal, log-slash, Birnbaum-Saunders and Birnbaum-Saunders-t distributions.
Implements the "shrinkage t" statistic
introduced in Opgen-Rhein and Strimmer (2007) and a shrinkage estimate
of the "correlation-adjusted t-score" (CAT score) described in
Zuber and Strimmer (2009).  It also offers a convenient interface
to a number of other regularized t-statistics commonly
employed in high-dimensional case-control studies.
Density, Probability and Quantile functions, and random number
generation for (skew) stable distributions, using the parametrizations of
Nolan.
Estimate the four parameters of stable laws using maximum
likelihood method, generalised method of moments with
finite and continuum number of points, iterative
Koutrouvelis regression and Kogon-McCulloch method.  The
asymptotic properties of the estimators (covariance
matrix, confidence intervals) are also provided.
An exploratory and heuristic approach for specification search
in Structural Equation Modeling. The basic idea is to subsample
the original data, and for each subset we search the
optimal models. Here the criteria of an optimal model is defined
by two objectives: to fit the data well and is simple (parsimonious) model.
As these objectives are conflicting, we apply NSGA-II to optimize,
such that to get optimal models for the whole range of model complexities.
From these optimal models, we observe the model specifications (structures)
that are both stable and parsimonious, called relevant. At the end we infer
causal model from these relevant structures.
Resampling procedures to assess the stability of selected variables
with additional finite sample error control for high-dimensional variable
selection procedures such as Lasso or boosting
Stacks rectangular datasets on top of each other, possibly
performing several type coercions along the way. For large datasets,
depends on the ff package. Provides an aggressive version of
ffbase::compact for data that may appear be real-typed but is in fact
int/short/byte. For many purposes plyr::rbind.fill may be more appropriate,
but for some kinds of survey data, the rules here work better.
Consists of helper functions collected from StackOverflow.com, a
question and answer site for professional and enthusiast programmers.
Analyzing a mixture of two-stage logistic regressions with fixed candidate knots. See Bruch, E., F. Feinberg, K. Lee (in press)<DOI:10.1073/pnas.1522494113>.
Provides facilities to implement and run population models of
stage-structured species...
stam is an evolving package that target on the various
methods to conduct Spatio-Temporal Analysis and
Modelling,including Exploratory Spatio-Temporal Analysis and
Inferred Spatio-Temporal Modelling.
Allows users to calculate pairwise Nei's Genetic Distances (Nei 1972), pairwise Fixation
Indexes (Fst) (Weir & Cockerham 1984) and also Genomic Relationship matrixes following Yang et al. (2010) in mixed and single
ploidy populations. Bootstrapping across loci is implemented during Fst calculation to generate confidence intervals and p-values
around pairwise Fst values. StAMPP utilises SNP genotype data of any ploidy level (with the ability to handle missing data) and is coded to
utilise multithreading where available to allow efficient analysis of large datasets. StAMPP is able to handle genotype data from genlight objects
allowing integration with other packages such adegenet.
Please refer to LW Pembleton, NOI Cogan & JW Forster, 2013, Molecular Ecology Resources, 13(5), 946-952. doi:10.1111/1755-0998.12129 for the appropriate citation and user manual. Thank you in advance.
Provides functions for the analysis of
occupational and environmental data with non-detects. Maximum
likelihood (ML) methods for censored log-normal data and
non-parametric methods based on the product limit estimate (PLE)
for left censored data are used to calculate all of the
statistics recommended by the American Industrial Hygiene
Association (AIHA) for the complete data case. Functions for
the analysis of complete samples using exact methods are also
provided for the lognormal model. Revised from 2007-11-05
'survfit~1'.
Standardizes text according to a template; particularly
useful for country names.
The C++ header files of the Stan project are provided by this package, but it contains no R code, vignettes, or function documentation. There is a shared object containing part of the CVODES library, but it is not accessible from R. StanHeaders is only useful for developers who want to utilize the LinkingTo directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or variational methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, templated statistical and linear algebra functions that can handle the automatically differentiable scalar types (and doubles, ints, etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.
Functions to analyze neuronal spike trains from a single
neuron or from several neurons recorded simultaneously.
Produces LaTeX code, HTML/CSS code and ASCII text for well-formatted tables that hold
regression analysis results from several models side-by-side, as well as summary
statistics.
Statistical functions to identify, estimate and diagnose a Space-Time AutoRegressive Moving Average (STARMA) model.
Provides utilities to create or suppress start-up messages.
A Set of Tools for Administering SHared Repositories
Datasets for Stat2 textbook (by Cannon, et. al., published
by WH Freeman)
A set of tools inspired by 'Stata' to explore data.frames ('summarize',
'tabulate', 'xtile', 'pctile', 'binscatter', elapsed quarters/month, lead/lag).
Extract statistics from articles and recompute p values.
This package offers different possibilities to make statistical analysis for Environmental Data.
Support for reading and writing files in StatDataML---an XML-based data exchange format.
Cartogram heatmaps are an alternative to choropleth maps for USA States
and are based on work by the Washington Post graphics department in their report
on "The states most threatened by trade". "State bins" preserve as much of the
geographic placement of the states as possible but has the look and feel of a
traditional heatmap. Functions are provided that allow for use of a binned,
discrete scale, a continuous scale or manually specified colors depending on
what is needed for the underlying data.
Statistics Finland (Tilastokeskus) Open Data R Tools
Selectively acquire hourly meteorological data from stations located all over the world.
Integration of two data sources referred to the same target population which share a number of common variables (aka data fusion). Some functions can also be used to impute missing values in data sets through hot deck imputation methods. Methods to perform statistical matching when dealing  with data from complex sample surveys are available too.
Offers useful functions to perform day-to-day data manipulation
operations, data quality checks and post modelling statistical checks.
One can effortlessly change class of a number of variables to factor,
remove duplicate observations from the data, create deciles of a
variable, perform data quality checks for continuous (integer or numeric),
categorical (factor) and date variables, and compute goodness of fit
measures such as auc for statistical models. The functions are consistent
for objects of class 'data.frame' and 'data.table', which is an enhanced
'data.frame' implemented in the package 'data.table'.
Functions and datasets to support Mayer Alvo and Philip L.H. Yu (2014). "Statistical Methods for Ranking Data", Springer. In this packages, smaller ranks stand for more preferred items.
A collection of algorithms and functions to aid statistical modeling. Includes growth curve comparisons, limiting dilution analysis (aka ELDA), mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models.  Includes advanced generalized linear model functions that implement secure convergence, dispersion modeling and Tweedie power-law families.
An integrated set of tools for the representation, visualization, analysis, and simulation of network data. For an introduction, type help(package='statnet').
Non-statistical utilities used by the software developed by the Statnet Project. They may also be of use to others.
A graphical user interface for network modeling with the 'statnet'
software.
Statomica is a suite of R functions that are needed for
certain packages such as LFDR.MLE, PsiHat, HistogramLFDR, combine and LFDRenrich.
A collection of statistical tools for social network analysis, with strong emphasis on the analysis of discrete powerlaw distributions and statistical hypothesis tests.
A small collection of data on graduate statistics programs from the United States.
A set of methods to implement Generalized Method of Moments and Maximal
Likelihood methods for Random Utility Models. These methods are meant to
provide inference on rank comparison data. These methods accept full,
partial, and pairwise rankings, and provides methods to break down full or
partial rankings into their pairwise components. Please see Generalized
Method-of-Moments for Rank Aggregation from NIPS 2013 for a description of
some of our methods.
An easy to use tool provides a graphical user interface for quality control based signal correction, integration of metabolomic data from multiple batches, and the comprehensive statistic analysis for non-targeted and targeted approaches.
Provides an implementation of simultaneous tolerance bounds (STB), useful for checking whether a numeric vector fits to a hypothetical null-distribution or not.
Furthermore, there are functions for computing STB (bands, intervals) for random variates of linear mixed models fitted with package 'VCA'. All kinds of, possibly transformed
(studentized, standardized, Pearson-type transformed) random variates (residuals, random effects), can be assessed employing STB-methodology.
Estimates a covariance matrix using Stein's isotonized covariance
estimator, or a related estimator suggested by Haff.
Contains three main functions including
stddiff.numeric(), stddiff.binary() and stddiff.category().
These are used to calculate the standardized difference between two groups.
It is especially used to evaluate the balance between two groups
before and after propensity score matching.
Contains functionality for regression standardization. Two general classes of models are allowed; generalized linear models and Cox proportional hazards models.
Functions related to multivariate measures of independence and ICA:
-estimate independent components by minimizing distance covariance;
-conduct a test of mutual independence based on distance covariance;
-estimate independent components via infomax (a popular method but generally performs poorer than mdcovica, ProDenICA, and/or fastICA, but is useful for comparisons);
-order indepedent components by skewness;
-match independent components from multiple estimates;
-other functions useful in ICA.
steepness is a package that computes steepness as a
property of dominance hierarchies. Steepness is defined as the
absolute slope of the straight line fitted to the normalized
David's scores. The normalized David's scores can be obtained
on the basis of dyadic dominance indices corrected for chance
or by means of proportions of wins. Given an observed
sociomatrix, it computes hierarchy's steepness and estimates
statistical significance by means of a randomization test.
Routines for computing different types of linear estimators, based on instrumental variables (IVs), including the semi-parametric Stein-like (SPS) estimator, originally introduced by Judge and Mittelhammer (2004)  <DOI:10.1198/016214504000000430>.
A package to manage and display stellar tracks and
isochrones from Pisa low-mass database. Includes tools for
isochrones construction and tracks interpolation.
Estimation of the parameters of a spatio-temporal model
using the EM algorithm, estimation of the parameter standard
errors using a spatio-temporal parametric bootstrap, spatial
mapping.
STEPwise Community Assembly Model collection, applying ABC-SMC in order to infer different community assembly processes. Also includes several plotting functions in order to visualize found estimates.
A method to explore the treatment-covariate interactions in survival or generalized
linear model (GLM) for continuous, binomial and count data arising from two treatment
arms of a clinical trial. A permutation distribution approach to inference is implemented,
based on permuting the covariate values within each treatment group.
L2 penalized logistic regression for both continuous and
discrete predictors, with forward stagewise/forward stepwise
variable selection procedure.
Allows to fit step-functions to univariate serial data where neither the number of jumps nor their positions is known.
A stepwise approach to identifying recombination
breakpoints in a sequence alignment.
Functions for the collection of 3D points and curves using a stereo camera setup.
Functions implementing the procedure of entropy comparison between two data samples after the renormalization of respective probability distributions with the algorithm designed by Klimontovich (Zeitschrift fur Physik B Condensed Matter. 1987, Volume 66, Issue 1, pp 125-127) and extended by Anishchenko (Proc. SPIE 2098, Computer Simulation in Nonlinear Optics. 1994, pp.130-136).  The package also includes data preparation tools which can also be used separately for various applications.
A set of functions for computing the Standardized Temperature Index (STI).
Functions to build and use an interpolator ("emulator") for time series or 1D regularly spaced data in multidimensional space. The standard usage is for interpolating time-resolved computer model output between model parameter settings. It can also be used for interpolating multivariate data (e.g., oceanographic time-series data, etc.) in space.  There are functions to test the emulator using cross-validation, and to produce contour plots over 2D slices in model input parameter (or physical) space.
This package enables you to estimate a regression trunk model, which is an integration of a regression tree and a multiple regression model.
A consistently well behaved method of interpolation based
on piecewise rational functions using Stineman's algorithm
Decompose a time series into seasonal, trend, and remainder
components using an implementation of Seasonal Decomposition of Time
Series by Loess (STL) that provides several enhancements over the STL
method in the stats package.  These enhancements include handling missing
values, providing higher order (quadratic) loess smoothing with automated
parameter choices, frequency component smoothing beyond the seasonal and
trend components, and some basic plot methods for diagnostics.
The Structural Topic Model (STM) allows researchers
to estimate topic models with document-level covariates.
The package also includes tools for model selection, visualization,
and estimation of topic-covariate regressions.
This visualization allows users to interactively explore the relationships between topics and the covariates estimated from the stm package in R.
Generates an interactive visualization of topic correlations/
hierarchy in a Structural Topic Model (STM) of Roberts, Stewart, and Tingley.
The package performs a hierarchical clustering of topics which are then exported
to a JSON object and visualized using D3.
Analysis by spatio-temporal data using the decomposition in n-dimensional arrays and using median polish technique.
Implementation of the family of generalised age-period-cohort
stochastic mortality models. This family of models encompasses many models
proposed in the actuarial and demographic literature including the Lee-Carter
model and the Cairns-Blake-Dowd model. It includes functions for fitting
mortality models, analysing their goodness-of-fit and performing mortality
projections and simulations.
Plots a QQ-Norm Plot with several Gaussian simulations.
Fit a spatial-temporal occupancy models using
a probit formulation instead of a traditional logit
model.
This is an R package accompanying the paper "Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles" by Sameer S Bajikar, Christiane Fuchs, Andreas Roller, Fabian J Theis and Kevin A Janes (PNAS 2014, 111(5), E626-635). In this paper, we measure expression profiles from small heterogeneous populations of cells, where each cell is assumed to be from a mixture of lognormal distributions. We perform maximum likelihood estimation in order to infer the mixture ratio and the parameters of these lognormal distributions from the cumulated expression measurements.
Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models via Markov chain Monte Carlo (MCMC) methods.
With this package, users can obtain the real-time price and volume information of stocks in China market, as well as the information of the stock index. This package adopted the API from Sina Finance (http://finance.sina.com.cn/).
Download stock data, build single index, constant
correlation, and multigroup models, and estimate optimal stock
portfolios. Plotting functions for the portfolio possibilities
curve and portfolio cloud are included. A function to test a
portfolio on a data set is also provided.
Provides functions for analyzing historical performance of stocks or other investments. Functions are written in C++ to quickly calculate maximum draw-down, Sharpe ratio, Sterling ratio, and other commonly used metrics of stock performance.
Given a list of substance compositions, a list of
substances involved in a process, and a list of constraints in
addition to mass conservation of elementary constituents, the
package contains functions to build the substance composition
matrix, to analyze the uniqueness of process stoichiometry, and
to calculate stoichiometric coefficients if process
stoichiometry is unique.  (See Reichert, P. and Schuwirth, N.,
A generic framework for deriving process stoichiometry in
enviromental models, Environmental Modelling and Software 25,
1241-1251, 2010 for more details.)
Storm is a distributed real-time computation system. Similar to how
Hadoop provides a set of general primitives for doing batch processing, Storm
provides a set of general primitives for doing real-time computation.

Storm includes a "Multi-Language" (or "Multilang") Protocol to allow
implementation of Bolts and Spouts in languages other than Java.  This R
extension provides implementations of utility functions to allow an application
developer to focus on application-specific functionality rather than Storm/R
communications plumbing.
Creates and manages simple key-value stores.  These can
use a variety of approaches for storing the data.  This package
implements the base methods and support for file system and
in-memory stores.  A vignette shows how additional drivers can be
created, and stubs exist for supporting 'Redis' databases.
A toolkit for Reliability Availability and Maintainability (RAM) modeling of industrial process systems.
Can be utilized to select a (test data) calibrated training population in high dimensional prediction problems.
Functionality and data access tools for transport planning,
including origin-destination analysis, route allocation and modelling travel
patterns.
Utilities to estimate parameters of the models with survival functions
induced by stochastic covariates. Miscellaneous functions for data preparation
and simulation are also provided. For more information, see: (i) "Life tables
with covariates: Dynamic model for nonlinear analysis of longitudinal data"
by Akushevich, I. et al. (2005), Mathematical Population Studies 12(2), 51(80),
<DOI:10.1080/08898480590932296>; (ii) "Stochastic model for analysis of
longitudinal data on aging and mortality" by Yashin A. et al. (2007),
Mathematical Biosciences, 208(2), 538-551, <DOI:10.1016/j.mbs.2006.11.006>;
(iii) "Health decline, aging and mortality: how are they related?"
by Yashin A. et al. (2007),
Biogerontology 8(3), 291(302), <DOI:10.1007/s10522-006-9073-3>.
A package for analysing, simulating and displaying space-time point patterns
Implement transformation-based and pixel-based residual
analysis of spatial-temporal point process models.
Regression-based ranking of pathogen strains with respect to their contributions to natural epidemics, using demographic and genetic data sampled in the curse of the epidemics
Functions for the stratigraphic analysis of phylogenetic trees.
A toolkit for analyzing stratified population genetic data.
Univariate stratification of survey populations with a generalization of the
Lavallee-Hidiroglou method of stratum construction. The generalized method takes into account
a discrepancy between the stratification variable and the survey variable. The determination
of the optimal boundaries also incorporate, if desired, an anticipated non-response, a take-all
stratum for large units, a take-none stratum for small units, and a certainty stratum to ensure
that some specific units are in the sample. The well known cumulative root frequency rule of
Dalenius and Hodges and the geometric rule of Gunning and Horgan are also implemented.
Stratified covariate balancing through naturally occurring strata to adjust for confounding and interaction effects. Contains 4 primary functions which perform stratification, sensitivity analysis and return adjusted odds along with naturally occurring strata.
A collection of tools for plotting and analyzing paleontological and geological data distributed through through time in stratigraphic cores or sections. Includes some miscellaneous functions for handling other kinds of palaeontological and paleoecological data.
Provides functions to estimate a strategic selection estimator. A strategic selection estimator is an agent error model in which the two random components are not assumed to be orthogonal. In addition this package provides generic functions to print and plot objects of its class as well as the necessary functions to create tables for LaTeX. There is also a function to create dyadic data sets.
The main function is icweib, which fits a stratified Weibull proportional hazards model for left censored, right censored, interval censored, and non-censored survival data. We parameterize the Weibull regression model so that it allows a stratum-specific baseline hazard function, but where the effects of other covariates are assumed to be constant across strata.
A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893 and NIH R21HG005912.
I provide functions to calculate Gross Primary Productivity, Net Ecocsystem Production, and Ecosystem Respiration from single station diurnal Oxygen curves.
Interface for data stream clustering algorithms implemented in the MOA (Massive Online Analysis) framework.
This package provides a series of functions that allow R users
to access Twitter's filter, sample, and user streams, and to
parse the output into data frames.
Functions to assist the process of learning structural
equation modeling
Forms queries to submit to the Cleveland Federal Reserve Bank web
site's financial stress index data site.  Provides query functions for both
the composite stress index and the components data. By default the download
includes daily time series data starting September 25, 1991.  The functions
return a class of either type easing or cfsi which contain a list of items
related to the query and its graphical presentation.  The list includes the
time series data as an xts object.  The package provides four lattice time
series plots to render the time series data in a manner similar to the
bank's own presentation.
Reliability of (normal) stress-strength models and for building two-sided or one-sided confidence intervals according to different approximate procedures.
Implements an approximate string matching version of R's native
'match' function. Can calculate various string distances based on edits
(damerau-levenshtein, hamming, levenshtein, optimal sting alignment), qgrams (q-
gram, cosine, jaccard distance) or heuristic metrics (jaro, jaro-winkler). An
implementation of soundex is provided as well. Distances can be computed between
character vectors while taking proper care of encoding or between integer
vectors representing generic sequences.
A toolbox for a construction of protein-protein interaction networks through the 'STRING' application programming interface, and an inference of Gaussian networks through 'SIMoNe' and 'WGCNA' approach, from DE genes analysis results and expression data. Additional functions are provided to import automatically networks into an active 'Cytoscape' session.
Allows for fast, correct, consistent, portable,
as well as convenient character string/text processing in every locale
and any native encoding. Owing to the use of the ICU library,
the package provides R users with platform-independent functions
known to Java, Perl, Python, PHP, and Ruby programmers. Among available
features there are: pattern searching (e.g., with ICU Java-like regular
expressions or the Unicode Collation Algorithm), random string generation,
case mapping, string transliteration, concatenation,
Unicode normalization, date-time formatting and parsing, etc.
A consistent, simple and easy to use set of wrappers around the
fantastic 'stringi' package. All function and argument names (and positions)
are consistent, all functions deal with "NA"'s and zero length vectors
in the same way, and the output from one function is easy to feed into
the input of another.
For making Trellis-type conditioning plots without strip labels.
This is useful for displaying the structure of results from factorial designs
and other studies when many conditioning variables would clutter the display
with layers of redundant strip labels. Settings of the variables are encoded by
layout and spacing in the trellis array and decoded by a separate legend. The
functionality is implemented by a single S3 generic strucplot() function that
is a wrapper for the Lattice package's xyplot() function. This allows access to
all Lattice graphics capabilities in the usual way.
R Codes and Datasets for Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications, CRC Press.
Testing, monitoring and dating structural changes in (linear)
regression models. strucchange features tests/methods from
the generalized fluctuation test framework as well as from
the F test (Chow test) framework. This includes methods to
fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM,
recursive/moving estimates) and F statistics, respectively.
It is possible to monitor incoming data online using
fluctuation processes.
Finally, the breakpoints in regression models with structural
changes can be estimated together with confidence intervals.
Emphasis is always given to methods for visualizing the data.
Performs multiple testing corrections that take specific structure of hypotheses into account.
Implements a broad class of latent variable and structural equation models for general pedigree data.
An open source platform for validation and process control.
Tools to analyse data from internal validation of forensic short tandem
repeat (STR) kits are provided. The tools are developed to provide
the necessary data to conform with guidelines for internal validation
issued by the European Network of Forensic Science Institutes (ENFSI)
DNA Working Group, and the Scientific Working Group on DNA Analysis Methods
(SWGDAM). A front-end graphical user interface is provided.
More information about each function can be found in the
respective help documentation.
Fit the basic structural time series model by maximum likelihood.
This package defines an S4 class for structural time series models
and provides some basic methods to work with it.
Create stubs of functions for use while testing.
A number of functions, supplemented by GUI, to perform various analyses in the field of computational stylistics, authorship attribution, etc.
Calculate empirical subcopula and dependence measures from a given bivariate sample.
The three functions in the package compute the maximum likelihood estimates of the informants' competence scores, tests for two answer keys with known groups, and finds "best" split of the informants into sub-culture groups.
A test for the existence of a subgroup with enhanced treatment effect. And, a sample size calculation procedure for the subgroup detection test.
Produces various measures of expected treatment effect heterogeneity under an assumption of homogeneity across subgroups. Graphical presentations are created to compare these expected differences with the observed differences.
The package implements a convenient procedure for microarray study, which is to do gene selection and classification simultaneously for binary outcomes. Users needn't to tune the parameters and can fix any genes that they desire to keep in the model. The K-folds cross validation results are returned.
Complementary multivariate analysis to the Outlying Mean Index
analysis to explore niche shift of a community within an Euclidean space, with
graphical displays.
Routines for identifying metabolic subpathways mediated by microRNAs (miRNAs) through topologically locating miRNAs and genes within reconstructed Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway graphs embedded by miRNAs. (1) This package can obtain the reconstructed KEGG metabolic pathway graphs with genes and miRNAs as nodes, through converting KEGG metabolic pathways to graphs with genes as nodes and compounds as edges, and then integrating miRNA-target interactions verified by low-throughput experiments from four databases (TarBase, miRecords, mirTarBase and miR2Disease) into converted pathway graphs. (2) This package can locate metabolic subpathways mediated by miRNAs by topologically analyzing the "lenient distance" of miRNAs and genes within reconstructed KEGG metabolic pathway graphs.(3) This package can identify significantly enriched miRNA-mediated metabolic subpathways based on located subpathways by hypergenomic test. (4) This package can support six species for metabolic subpathway identification, such as caenorhabditis elegans, drosophila melanogaster, danio rerio, homo sapiens, mus musculus and rattus norvegicus, and user only need to update interested organism-specific environment variables.
Identify dysfunctional subpathways competitively regulated by lncRNAs through integrating lncRNA-mRNA expression profile and pathway topologies.
The subplex algorithm for unconstrained optimization, developed by Tom Rowan.
Estimation of copula using ranks and subsampling. The main feature of this method is that simulation studies show a low sensitivity to dimension, on realistic cases. Vignette provides some theoretical documentation.
Functions for computing test subscores using methods applicable to classical test theory (CTT) scores. This package enables two sets of subscoring methods within the framework of CTT: (1) Wainer's augmentation method, and (2) Haberman's three subscoring methods. The package also includes the function to compute Proportional Reduction of Mean Squared Errors (PRMSEs) proposed by Haberman's, which are used to examine whether test subscores are of added value.
A collection of functions which (i) assess the quality of variable subsets as surrogates for a full data set, in either an exploratory data analysis or in the context of a multivariate linear model, and (ii) search for subsets which are optimal under various criteria.
Subsemble is a general subset ensemble prediction method, which can be used for small, moderate, or large datasets. Subsemble partitions the full dataset into subsets of observations, fits a specified underlying algorithm on each subset, and uses a unique form of V-fold cross-validation to output a prediction function that combines the subset-specific fits. An oracle result provides a theoretical performance guarantee for Subsemble.
An interface to 'OpenSubspace', an open source framework for
evaluation and exploration of subspace clustering algorithms in WEKA
(see <http://dme.rwth-aachen.de/de/opensubspace> for more
information).  Also performs visualization.
An interface to 'subspaceMOA', a Framework for the Evaluation of subspace stream clustering algorithms. (see <http://dme.rwth-aachen.de/de/subspacemoa> for more information.)
subtype performs a biclustering procedure on a input
dataset and assess whether resulting clusters are promising
subtypes. Note that the R-package rsmooth should be installed
before implementing subtype. rsmooth can be downloaded from
http://www.meb.ki.se/~yudpaw.
Substitution matrices are important parameters in protein alignment algorithms. These matrices represent the likelihood that an amino acid will be substituted for another during mutation. This tool allows users to apply predefined and custom matrices and then explore the resulting alignments with interactive visualizations.  SubVis requires the availability of a web browser.
Generates, plays, and solves Sudoku puzzles.  The GUI
playSudoku() needs package "tkrplot" if you are not on Windows.
Tools for making, retrieving, displaying and solving sudoku games.
This package is an alternative to the earlier sudoku-solver package,
'sudoku'.  The present package uses a slightly different algorithm, has a
simpler coding and presents a few more sugar tools, such as plot and print
methods.  Solved sudoku games are of some interest in Experimental Design
as examples of Latin Square designs with additional balance constraints.
This is a package for the subsampling method of robust
estimation of linear regression models
Generates formatted summary tables for vectors and dataframes.
Three summarizing functions: 1) 'freq' generates frequency tables
reporting counts and proportions (including cumulative); 2) 'descr'
gives common central tendency statistics and measures of dispersion
for numerical data; 3) 'dfSummary' gives as much information
as possible about a dataframe and its components in a clear,
legible table. All three functions can either display plain text tables
in the console or write markdown, text or html files to disk. An
additional misc function, 'what.is', extends base 'is' function,
checking the object against all 'is' functions and gives a variety
of other information about the object.
Functions for drawing samples according to Sunter's
sampling design, and for computing first and second order
inclusion probabilities
Methodology for supervised grouping aka "clustering" of
potentially many predictor variables, such as genes etc.
Clusters features under the assumption that each cluster has a
random effect and there is an outcome variable that is related to the random
effects by a linear regression. In this way the cluster analysis is
``supervised'' by the outcome variable. An alternate specification is that
features in each cluster have the same compound symmetric normal distribution,
and the conditional distribution of the outcome given the features
has the same coefficient for each feature in a cluster.
Biclusters are submatrices in the data matrix which
satisfy certain conditions of homogeneity. Package contains
functions for generating robust biclusters with respect to the
initialization parameters for a given bicluster solution
contained in a bicluster set in data, the procedure is also
known as ensemble biclustering. The set of biclusters is
evaluated based on the similarity of its elements (the
overlap), and afterwards the hierarchical tree is constructed
to obtain cut-off points for the classes of robust biclusters.
The result is a number of robust (or super) biclusters with
none or low overlap.
A Comprehensive Test Suite for Markov Chain
Nonconvergence.
Efficient statistical testing and scalable visualization of intersections among multiple sets.
Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
Witten and Tibshirani (2011) Supervised multidimensional scaling for visualization, classification, and bipartite ranking. Computational Statistics and Data Analysis 55(1): 789-801.
Supervised principal components for regression and
survival analsysis. Especially useful for high-dimnesional
data, including microarray data.
Tools for analysing the aggreement of two or more rankings of the same items. Examples are importance rankings of predictor variables and risk predictions of subjects. Benchmarks for agreement are computed based on random permutation and bootstrap.
The Patient Rules Induction Method (PRIM) is typically
used for "bump hunting" data mining to identify regions with abnormally
high concentrations of data with large or small values. This package
extends this methodology so that it can be applied to binary classification
problems and used for prediction.
Ten distributions supplementing those built into R.
Inverse Gauss, Kruskal-Wallis, Kendall's Tau, Friedman's chi
squared, Spearman's rho, maximum F ratio, the Pearson product
moment correlation coefficiant, Johnson distributions, normal
scores and generalized hypergeometric distributions. In
addition two random number generators of George Marsaglia are
included.
Provides three basic functions that support an implementation of object case (Case 1) best-worst scaling: one for converting a two-level orthogonal main-effect design/balanced incomplete block design into questions; one for creating a data set suitable for analysis; and one for calculating count-based scores.
Provides seven basic functions that support an implementation of choice experiments.
Calculates likelihood based support intervals for
several common data types including binomial, Poisson, normal, lm(), and
glm(). For the binomial, Poisson, and normal data likelihood intervals are
calculated via root finding algorithm. Additional parameters allow the
user to specify whether they would like to receive a parametric bootstrap
estimate of the confidence level of said support interval. For lm() and glm(),
the function returns profile likelihoods for each coefficient in the model.
SURFACE is a data-driven phylogenetic comparative method for fitting stabilizing selection models to continuous trait data, building on the ouch package. The main functions fit a series of Hansen models using stepwise AIC, then identify cases of convergent evolution where multiple lineages have shifted to the same adaptive peak.
In a clinical trial, it frequently occurs that the most credible outcome to evaluate the effectiveness of a new therapy (the true endpoint) is difficult to measure. In such a situation, it can be an effective strategy to replace the true endpoint by a (bio)marker that is easier to measure and that allows for a prediction of the treatment effect on the true endpoint (a surrogate endpoint). The package 'Surrogate' allows for an evaluation of the appropriateness of a candidate surrogate endpoint based on the meta-analytic, information-theoretic, and causal-inference frameworks. Part of this software has been developed using funding provided from the European Union's 7-th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
suRtex was designed for easy descriptive statistic reporting of categorical survey data (e.g., Likert scales) in LaTeX. suRtex takes a matrix or data frame and produces the LaTeX code necessary for a sideways table creation. Mean, median, standard deviation, and sample size are optional.
Performs inference of several model-free group contrast measures, which include difference/ratio of cumulative incidence rates at given time points, quantiles, and restricted mean survival times (RMST). Two kinds of covariate adjustment procedures (i.e., regression and augmentation) for inference of the metrics based on RMST are also included.
This package provides a function to estimate the AUC, TPR(c),
FPR(c), PPV(c), and NPV(c) for for a specific timepoint and marker cutoff
value c using non-parametric and semi-parametric estimators. Standard errors
and confidence intervals are also computed. Either analytic or bootstrap
standard errors can be computed.
The package provides a variety of functions to estimate
time-dependent true/false positive rates and AUC curves from a
set of censored survival data.
Performs inference for C of risk prediction models with
censored survival data, using the method proposed by Uno et al.
(2011). Inference for the difference in C between two competing
prediction models is also implemented.
Estimates correlation coefficients with associated
confidence limits
for bivariate, partially censored survival times. Uses
the iterative multiple imputation approach proposed
by Schemper, Kaider, Wakounig and Heinze, Statistics
in Medicine 2013. Provides a scatterplot function to visualize the bivariate
distribution, either on the original time scale or as copula.
Relative survival, AER and SMR based on French death rates
Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Principal components, factor analysis.
Tools for using different kinds of bootstrap
for estimating sampling variation using complex survey
data.
Data obtained from surveys contains information not only about the
survey responses, but also the survey metadata, e.g. the original survey
questions and the answer options. The surveydata package makes it easy to
keep track of this metadata, and to easily extract columns with
specific questions.
Help generate slides for surveys or experiments.
The resulted slides allow the subject to respond with the use of the mouse (usual keyboard input is
replaced with clicking on a virtual keyboard on the slide). Subjects' responses are saved to the user-
specified location in the form of R-readable text file. To allow flexibility, each function in
this package generates a particular type of slides thus general R function writing skills are
required to compile these edited slides.
At present, the only functionality is the calculation of optimal one-sided winsorizing cutoffs. The main function is optimal.onesided.cutoff.bygroup. It calculates the optimal tuning parameter for one-sided winsorisation, and so calculates winsorised values for a variable of interest. See the help file for this function for more details and an example.
Tools for sample survey planning, including sample size calculation, estimation of expected precision for the estimates of totals, and calculation of optimal sample size allocation.
The Gini concentration test for survival data is a nonparametric test based on the Gini index for testing the equality of two survival distributions from the point of view of concentration. The package compares different nonparametric tests (asymptotic Gini test, permutation Gini test, log-rank test, Gray-Tsiatis test and Wilcoxon test) and computes their p-values.
Performs inference for a class of measures to compare
competing risk prediction models with censored survival data.
The class includes the integrated discrimination improvement
index (IDI) and category-less net reclassification index (NRI).
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.
Estimate the regression coefficients and the baseline hazard
of proportional hazard Cox models using maximum penalised likelihood.
A 'non-parametric' smooth estimate of the baseline hazard function
is provided.
Compute time-dependent ROC curve from censored survival
data using Kaplan-Meier (KM) or Nearest Neighbor Estimation
(NNE) method of Heagerty, Lumley & Pepe (Biometrics, Vol 56 No
2, 2000, PP 337-344)
Microarray gene expression data can be analyzed individually or jointly using merging methods or meta-analysis to predict patients' survival and risk assessment.
Three breast cancer gene expression data sets that can be used for package 'survJamda'. This package contains the gene expression and phenotype data of GSE1992, GSE3143 and GSE4335.
Kernel weighting methods for estimation of proportional hazards models with intermittently observed longitudinal covariates.
Contains the function 'ggsurvplot()' for drawing easily beautiful
and 'ready-to-publish' survival curves with the 'number at risk' table. Other
functions are also available for visual examinations of 'cox' model assumptions.
A collection of functions to help in the analysis of
right-censored survival data. These extend the methods available in
package:survival.
Presmoothed estimators of survival, density, cumulative and non-cumulative hazard functions with right-censored survival data.
Estimation of the prediction accuracy in a unified survival AUC
approach. Model selection and prediction estimation based on a survival AUC.
Stepwise model selection, based on several ranking approaches.
Estimation of survival function for recurrent event data
using Peña-Strawderman-Hollander, Whang-Chang estimators and
MLE estimation under a Gamma Frailty model.
The main function of this package allows estimation of a Weibull Regression for a right-censored endpoint, one interval-censored covariate, and an arbitrary number of non-censored covariates. Additional functions allow to switch between different parametrizations of Weibull regression used by different R functions, inference for the mean difference of two arbitrarily censored Normal samples, and estimation of canonical parameters from censored samples for several distributional assumptions.
Performs two-sample comparisons using the restricted mean survival time (RMST) as a summary measure of the survival time distribution. Three kinds of between-group contrast metrics (i.e., the difference in RMST, the ratio of RMST and the ratio of the restricted mean time lost (RMTL)) are computed. It performs an ANCOVA-type covariate adjustment as well as unadjusted analyses for those measures.
Simulation of simple and complex survival data including recurrent and multiple events and competing risks.
Conduct asymptotic and empirical power and sample size calculations for Single-Nucleotide Polymorphism (SNP) association studies with right censored time to event outcomes.
The sValues package implements the s-values proposed by Ed. Leamer.
It provides a context-minimal approach for sensitivity analysis using extreme
bounds to assess the sturdiness of regression coefficients.
Accurate identification of genes that are truly differentially expressed over two sample varieties, after adjusting for hidden subject-specific effects of residual heterogeneity.
2d and 3d space-varying coefficient models are fitted to
regular grid data using either a full B-spline tensor product
approach or a sequential approximation. The latter one is
computationally more efficient. Resolution increment is
enabled.
R bindings to SVD and eigensolvers (PROPACK, nuTRLan).
Rapidly construct dialog boxes for your GUI, including an automatic
function assistant
Reimplementation of the svDialogs dialog boxes in Tcl/Tk
Visualize singular value decompositions (SVD), principal component analysis (PCA), factor analysis (FA) and related methods.
Some visualization tools based on Singular Value Decomposition
A graphics device for R that produces 'Scalable Vector Graphics'.
'svglite' is a fork of the older 'RSvgDevice' package.
This 'htmlwidget' provides pan and zoom interactivity to R
graphics, including 'base', 'lattice', and 'ggplot2'. The interactivity is
provided through the 'svg-pan-zoom.js' library. Various options to the widget
can tailor the pan and zoom experience to nearly any user desire.
Creates 3D animated, interactive visualizations in Scalable Vector Graphics (SVG) format that can be viewed in a web browser.
Implements a simple HTTP server allowing to connect GUI clients to R
Function for the GUI API to interact with external IDE/code editors
Functions to manage the GUI client, like Komodo with the
SciViews-K extension
Solve large-scale regularised linear/kernel classification by using ADMM and IADMM algorithms. This package provides linear L2-regularised primal classification (both ADMM and IADMM are available), kernel L2-regularised dual classification (IADMM) as well as L1-regularised primal classification (both ADMM and IADMM are available).
Supporting functions for the GUI API (various utility functions)
Implements the SVM-Maj algorithm to train data with
Support Vector Machine, this algorithm uses two efficient
updates, one for linear kernel and one for the nonlinear
kernel.
Causal effect estimation in observational data often requires identifying a set of untreated observations that are comparable to some treated group of interest.  This package provides a suite of functions for identifying such a set of observations and for implementing standard and new diagnostics tools.  The primary function, svmmatch(), uses support vector machines to identify a region of common support between treatment and control groups.  A sensitivity analysis, balance checking, and assessment of the region of overlap between treated and control groups is included.  The Bayesian implementation allows for recovery of uncertainty estimates for the treatment effect and all other parameters.
Computes the entire regularization path for the two-class
svm classifier with essentially the same cost as a single SVM
fit.
Various tools for semantic vector spaces, such as
correspondence analysis (simple, multiple and discriminant), latent
semantic analysis, probabilistic latent semantic analysis, non-negative
matrix factorization, latent class analysis and EM clustering. Furthermore,
there are specialized distance measures, plotting functions and some helper
functions.
Implements a simple socket server allowing to connect GUI clients to R
Supporting functions for the GUI API (Sweave functions)
Set of tools aimed at wrapping some of the functionalities
of the packages tools, utils and codetools into a nicer format so
that an IDE can use them
A complete unit test system and functions to implement its GUI part
High level management of widgets, windows and other graphical resources.
Builds, evaluates and validates a nomogram with survey data and right-censored outcomes.
This package deals with data which stem from survey designs including plausible values. This package has been created to handle data from Large Scale Assessments like PISA, PIAAC etc. which use  complex survey designs to draw the sample and plausible values to report person related estimates. Various functions/statistics (mean, quantile, GLM etc.) are provided to handle this kind of data.
The package contains functions to connect the structure of
the data with the information on the samples. Three types of
associations are covered: 1. linear model of principal
components. 2. hierarchical clustering analysis. 3.
distribution of features-sample annotation associations.
Additionally, the inter-relation between sample annotations can
be analyzed. Simple methods are provided for the correction of
batch effects and removal of principal components.
Three ensemble learning algorithms based on support vector machines.
They all train support vector machines on subset of data and combine the result.
The Soil and Water Assessment Tool is a river basin or
watershed scale model developed by Dr. Jeff Arnold for the
USDA-ARS.
Provides utilities for defining R / Rd as "language" for TeX-package "listings"
and for including R / Rd source file (snippets) copied from R-forge in its most
recent version (or another URL) thereby avoiding inconsistencies between vignette
and documented source code.
Structural handling of identity numbers used in the Swedish
administration such as personal identity numbers ('personnummer') and
organizational identity numbers ('organisationsnummer').
Collection of conversion, analytical, geodesic, mapping, and
plotting functions. Used to support packages and code written by
researchers at the Southwest Fisheries Science Center of the National
Oceanic and Atmospheric Administration.
Use the R console as an interactive learning
environment. Users receive immediate feedback as they are guided through
self-paced lessons in data science and R programming.
A set of tools for writing and sharing interactive courses
to be used with swirl.
Ozone, NOx (= Sum of Nitrogenmonoxide and
Nitrogendioxide), Nitrogenmonoxide, ambient temperature, dew
point, wind speed and wind direction at 3 sites around lake of
Lucerne in Central Switzerland in 30 min time resolution for
year 2004.
Functions for estimating the parameters from the latent
state process and the functions corresponding to the J states as
proposed by De Souza and Heckman (2013).
Provides an abstraction for managing, installing,
and switching between sets of installed R packages. This allows users to
maintain multiple package libraries simultaneously, e.g. to maintain
strict, package-version-specific reproducibility of many analyses, or
work within a development/production release paradigm. Introduces a
generalized package installation process which supports multiple repository
and non-repository sources and tracks package provenance.
Provides a simple plugin to the switchr
framework which allows users to publish manifests of packages - or of specific versions thereof - as  single-file GitHub repositories (Gists). These manifest files can then be used as remote seeds (see switchr documentation) when creating new package libraries.
Tools for retrieving, organizing, and analyzing environmental
data from the System Wide Monitoring Program of the National Estuarine
Research Reserve System.  These tools address common challenges
associated with continuous time series data for environmental decision
making.
This Systems Biology Library for R implements algorithms for constraint based analyses of metabolic networks (e.g. flux-balance analysis (FBA), minimization of metabolic adjustment (MOMA), regulatory on/off minimization (ROOM), robustness analysis and flux variability analysis). Most of the current LP/MILP solvers are supported via additional packages.
An implementation of a cost constrained flux balance analysis technique (i.e. MetabOlic Modeling with ENzyme kineTics (MOMENT)).
MOMENT uses enzyme kinetic data and enzyme molecular weights to constrain flux balance analysis(FBA) and it is described in
Adadi, R., Volkmer, B., Milo, R., Heinemann, M., & Shlomi, T. (2012). Prediction of Microbial Growth Rate versus Biomass
Yield by a Metabolic Network with Kinetic Parameters, 8(7). doi:10.1371/journal.pcbi.1002575.
This package also implements an improvement of MOMENT that considers multi-functional enzymes.
FBA is a mathematical technique to find fluxes in metabolic models at steady state.
It is described in Orth, J.D., Thiele, I. and Palsson, B.O.  What is flux balance analysis? Nat. Biotech. 28, 245-248(2010).
Implement cycle-Free flux balance analysis, flux variability, and Random Sampling of solution space. Flux balance analysis is a technique to find fluxes in metabolic models at steady state. It is described in Orth, J.D., Thiele, I. and Palsson, B.O. What is flux balance analysis? Nat. Biotech. 28, 245-248 (2010).
Implements dynamic FBA technique proposed by Varma et al 1994.
Three different approaches to use gene expression data (or protein measurements) for improving FBA predictions.
'SBML' (Systems Biology Markup Language) integration in 'sybil'. Many constraint based metabolic models are published in 'SBML' format ('*.xml'). Herewith is the ability to read and check 'SBML' files in 'sybil' provided.
Symbolic data analysis methods: importing/ exporting data from ASSO XML Files, distance calculation for symbolic data (Ichino-Yaguchi, de Carvalho measure), zoom star plot, 3d interval plot, multidimensional scaling for symbolic interval data, dynamic clustering based on distance matrix, HINoV method for symbolic data, Ichino's feature selection method, principal component analysis for symbolic interval data, decision trees for symbolic data based on optimal split with bagging, boosting and random forest approach (+visualization), kernel discriminant analysis for symbolic data, Kohonen's self-organizing maps for symbolic, replication and profiling, artificial symbolic data generation.
Package that implements various symbol plots (bars,
profiles, stars, Chernoff faces, color icons, stick figures).
Symbolic central and non-central moments of the multivariate normal distribution. Computes a standard representation, LateX code, and values at specified mean and covariance matrices.
A collection of functions required for genomic prediction which were developed within the Synbreed project for synergistic plant and animal breeding (www.synbreed.tum.de). This covers data processing, data visualization, and analysis. All functions are embedded within the framework of a single, unified data object. The implementation is flexible with respect to a wide range of data formats in plant and animal breeding. This research was funded by the German Federal Ministry of Education and Research (BMBF) within the AgroClustEr Synbreed - Synergistic plant and animal breeding (FKZ 0315528A).
Data sets for the 'synbreed' package with three data sets from cattle, maize and mice to illustrate the functions in the 'synbreed' R package. All data sets are stored in the gpData format introduced in the 'synbreed'
package. This research was funded by the German Federal Ministry of Education and Research (BMBF) within the AgroClustEr Synbreed - Synergistic plant and animal breeding (FKZ 0315528A).
Methods for computing spatial, temporal, and spatiotemporal
statistics including: empirical univariate, bivariate and multivariate
variograms; fitting variogram models; phase locking and synchrony analysis;
generating autocorrelated and cross-correlated matrices.
This package carries out synchrosqueezed wavelet transform. The package is a translation of MATLAB Synchrosqueezing Toolbox, version 1.1 originally developed by Eugene Brevdo (2012). The C code for curve_ext was authored by Jianfeng Lu, and translated to Fortran by Dongik Jang. Synchrosqueezing is based on the papers: [1] Daubechies, I., Lu, J. and Wu, H. T. (2011) Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool. Applied and Computational Harmonic Analysis, 30. 243-261. [2] Thakur, G., Brevdo, E., Fukar, N. S. and Wu, H-T. (2013) The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications. Signal Processing, 93, 1079-1094.
The function 'syncSubsample' subsamples temporal data of different entities so that the result only contains synchronal events. The function 'mci' calculates the Movement Coordination Index (MCI, see reference on help page for function 'mci') of a data set created with the function 'syncSubsample'.
Analysis of metacommunities based on functional traits and phylogeny of the community components. The functions that are offered here implement for the R environment methods that have been available in the SYNCSA application written in C++ (by Valerio Pillar, available at http://ecoqua.ecologia.ufrgs.br/ecoqua/SYNCSA.html).
This package provides programmatic access to
The Synergizer service for translating between sets of
biological identifiers.
Efficient implementations for all the popular synergy scoring models for drug combinations, including HSA, Loewe, Bliss and ZIP and visualization of the synergy scores as either a two-dimensional or a three-dimensional interaction surface over the dose matrix.
Infers sympatry matrices from distributional data and analyzes them in order to identify groups of species cohesively connected.
Framework to perform synthetic likelihood inference
for models where the likelihood function is unavailable or
intractable.
It implements various estimators of mutual information, such as
the maximum likelihood and the Millow-Madow estimator, various Bayesian
estimators, the shrinkage estimator, and the Chao-Shen estimator. It also
offers wrappers to the kNN and kernel density estimators. Furthermore, it
provides various index of performance evaluation such as precision, recall,
FPR, F-Score, ROC-PR Curves and so on. Lastly, it provides a brand new way
of generating synthetic RNA-Seq Network with known dependence structure.
Implements the synthetic control group method for comparative case studies as described in Abadie and Gardeazabal (2003) and Abadie, Diamond, and Hainmueller (2010, 2011, 2014). The synthetic control method allows for effect estimation in settings where a single unit (a state, country, firm, etc.) is exposed to an event or intervention. It provides a data-driven procedure to construct synthetic control units based on a weighted combination of comparison units that approximates the characteristics of the unit that is exposed to the intervention. A combination of comparison units often provides a better comparison for the unit exposed to the intervention than any comparison unit alone.
Firstly provides a wrapper to library(acs) to access
numerous American Community Survey (ACS) base tables which may be of interest
to many researchers. Secondly, it builds synthetic micro-datasets of ACS data
at any specified geographic level with 10 default individual attributes. Thirdly,
the package provides functionality for users to add additional ACS & non-ACS  data attributes to micro-datasets based on macro population characteristics. And
finally, the package also conducts spatial microsimulation modeling (SMSM)
via simulated annealing.  SMSM is conducted in parallel by default.
A tool for producing synthetic versions of microdata containing confidential information so that they are safe to be released to users for exploratory analysis. The key objective of generating synthetic data is to replace sensitive original values with synthetic ones causing minimal distortion of the statistical information contained in the data set. Variables, which can be categorical or continuous, are synthesised one-by-one using sequential modelling. Replacements are generated by drawing from conditional distributions fitted to the original data using parametric or classification and regression trees models. Data are synthesised via the function syn() which can be largely automated, if default settings are used, or with methods defined by the user. Optional parameters can be used to influence the disclosure risk and the analytical quality of the synthesised data.
Using FreeType to load system fonts
and Google Fonts (https://www.google.com/fonts) into R.
It is supposed to support other packages such as 'R2SWF'
and 'showtext'.
Fitting simultaneous
systems of linear and nonlinear equations using Ordinary Least
Squares (OLS), Weighted Least Squares (WLS), Seemingly Unrelated
Regressions (SUR), Two-Stage Least Squares (2SLS), Weighted
Two-Stage Least Squares (W2SLS), and Three-Stage Least Squares (3SLS).
A toolbox for systemic risk based on liabilities matrices. Contains
a Gibbs sampler for liabilities matrices where only row and column sums of the
liabilities matrix as well as some other fixed entries are observed. Includes models
for power law distribution on the degree distribution.
Extracts sentiment and sentiment-derived plot arcs
from text using three sentiment dictionaries conveniently
packaged for consumption by R users.  Implemented dictionaries include
"syuzhet" (default) developed in the Nebraska Literary Lab
"afinn" developed by Finn {\AA}rup Nielsen, "bing" developed by Minqing Hu
and Bing Liu, and "nrc" developed by Mohammad, Saif M. and Turney, Peter D.
Applicable references are available in README.md and in the documentation
for the "get_sentiment" function.  The package also provides a hack for
implementing Stanford's coreNLP sentiment parser. The package provides
several methods for plot arc normalization.
Contains functions for generating tables for statistical reports written in Microsoft Word or LaTeX. There are functions for I-by-J frequency tables, comparison of means or medians across levels of a categorical variable, and summarizing fitted generalized linear models, generalized estimating equations, and Cox proportional hazards regression. Functions are available to handle data simple random samples or survey data. The package is intended to make it easier for researchers to translate results from statistical analyses in R to their reports or manuscripts.
Sometimes you need to split your data and work on the two chunks independently before bringing them back together. 'Taber' allows you to do that with its two functions.
Some functions are included in this package for writing tables in Excel format suitable for distribution.
Table 1 is the classical way to describe the patients in a
clinical study. The amount of splits in the data in such a table is
limited. Table1Heatmap draws a heatmap of all crosstables that can be
generated with the data. Users can choose between showing the actual
crosstables or direction of effect of associations, and highlight
associations by number of patients or p-values.
A collection of time-saving wrappers for producing and exporting
summary tables commonly used in scientific articles, to .xls/.xlsx multi-tab spreadsheets, while controlling spreadsheet layout. Powered by 'XLConnect'/'rJava' utilities.
A tool to easily create and style HTML tables, which are compatible with shiny.
Provides a user friendly interface to generation of booktab style
tables using xtable.
Creates "Table 1", i.e., description of baseline patient
characteristics, which is essential in every medical research.
Supports both continuous and categorical variables, as well as
p-values and standardized mean differences. Weighted data are
supported via the survey package. See github for a screencast.
tableone was inspired by descriptive statistics functions in
Deducer , a Java-based GUI package by Ian Fellows. This package
does not require GUI or Java, and intended for command-line users.
Computes and displays complex tables of summary statistics.
TableToLongForm automatically converts hierarchical Tables intended for a human reader into a simple LongForm Dataframe that is machine readable.
A tableplot is a visualisation of a (large)
dataset with a dozen of variables, both numeric and
categorical. Each column represents a variable and each
row bin is an aggregate of a certain number of records.
Numeric variables are visualized as bar charts, and
categorical variables as stacked bar charts. Missing
values are taken into account. Also supports large ffdf
datasets from the ff package.
A tableplot is a visualisation of a (large)
dataset with a dozen of variables, both numeric and
categorical. This package contains an interactive version of
tableplot working in your browser.
R based tabu search algorithm for binary configurations
Contains functions for the easy display of statistical tests as well as
some convenience functions for recoding or data cleanup. It is meant to ease existing workflows
with packages like 'sjPlot', 'dplyr', and 'ggplot2'. The primary components are the functions
prefixed with 'tadaa_', which are built to work in an interactive environment, but also print
tidy markdown tables powered by 'pixiedust' for the creation of 'RMarkdown' reports.
Provides functions implementing minimal distance estimation methods for parametric tail dependence models.
Set of tools to estimate the probability in the upper tail of the aggregate loss distribution using different methods: Panjer recursion, Monte Carlo simulations, Markov bound, Cantelli bound, Moment bound, and Chernoff bound.
Includes marginal maximum likelihood estimation of uni- and
multidimensional item response models (Rasch, 2PL, 3PL,
Generalized Partial Credit, Multi Facets,
Nominal Item Response, Structured Latent Class Analysis,
Mixture Distribution IRT Models, Located Latent Class Models)
and joint maximum likelihood estimation for models
from the Rasch family.
Latent regression models and plausible value imputation are
also supported.
Density, distribution function, quantile function, random
generation and survival function for the Tangent Burr Type XII Distribution as
defined by SOUZA, L. New Trigonometric Class of Probabilistic Distributions.
219 p. Thesis (Doctorate in Biometry and Applied Statistics) - Department of
Statistics and Information, Federal Rural University of Pernambuco, Recife,
Pernambuco, 2015 (available at <http://www.openthesis.org/documents/New-trigonometric-classes-probabilistic-distributions-602633.html>) and BRITO, C. C. R. Method Distributions generator and
Probability Distributions Classes. 241 p. Thesis (Doctorate in Biometry and
Applied Statistics) - Department of Statistics
University of Pernambuco, Recife, Pernambuco, 2014 (available upon request).
A two-stage regression method that can be used when various input data types are correlated, for example gene expression and methylation in drug response prediction. In the first stage it uses the upstream features (such as methylation) to predict the response variable (such as drug response), and in the second stage it uses the downstream features (such as gene expression) to predict the residuals of the first stage. In our manuscript (Aben et al., 2016, in press), we show that using TANDEM prevents the model from being dominated by gene expression and that the features selected by TANDEM are more interpretable.
Functions for performing analysis of variance on time
course microarray data
Implementation of functions for fitting taper curves (a semiparametric linear mixed effects taper model) to diameter measurements along stems. Further functions are provided to estimate the uncertainty around the predicted curves, to calculate timber volume (also by sections) and marginal (e.g., upper) diameters. For cases where tree
heights are not measured, methods for estimating
additional variance in volume predictions resulting from uncertainties in
tree height models (tariffs) are provided.  The example data include the taper curve parameters for Norway spruce used in the 3rd German NFI fitted to 380 trees and a subset of section-wise diameter measurements of these trees. The functions implemented here are detailed in the following publication: Kublin, E., Breidenbach, J., Kaendler, G. (2013) A flexible stem taper and volume prediction method based on mixed-effects B-spline regression, Eur J For Res, 132:983-997.
Manager of tick-by-tick transaction data that performs 'cleaning', 'aggregation' and 'import' in an efficient and fast way. The package engine, written in C++, exploits the 'zlib' and 'gzstream' libraries to handle gzipped data without need to uncompress them. 'Cleaning' and 'aggregation' are performed according to Brownlees and Gallo (2006). Currently, TAQMNGR processes raw data from WRDS (Wharton Research Data Service).
Implement the Tariff algorithm for coding cause-of-death from verbal autopsies. The Tariff method was originally proposed in James et al (2011) <DOI:10.1186/1478-7954-9-31> and later refined as Tariff 2.0 in Serina, et al. (2015) <DOI:10.1186/s12916-015-0527-9>. Note that this package was not developed by authors affiliated with the Institute for Health Metrics and Evaluation and thus unintentional discrepancies may exist between the this implementation and the implementation available from IHME.
A collection of various utility and convenience functions.
Evaluates traveltimes and ray paths using predefined Earth
(or other planet) models.  Includes phase plotting routines.
The IASP91 and AK135 Earth models are included, and most
important arrival phases can be evaluated.
Computes the t* statistic corresponding to the tau* population
coefficient introduced by Bergsma and Dassios (2014) <DOI:10.3150/13-BEJ514>
and does so in O(n^2*log(n)) time following the algorithm of Weihs,
Drton, and Leung (2016) <DOI:10.1007/s00180-015-0639-x>. Also allows for
independence testing using the asymptotic distribution of t* as described by
Nandy, Weihs, and Drton (2016) <http://arxiv.org/abs/1602.04387>.
Portfolio optimization typically requires an estimate of a covariance matrix of asset returns. There are many approaches for constructing such a covariance matrix, some using the sample covariance matrix as a starting point. This package provides implementations for two such methods: random matrix theory and shrinkage estimation. Each method attempts to clean or remove noise related to the sampling process from the sample covariance matrix.
Base library of types for tawny and related packages
Interacts with a suite of web 'APIs' for taxonomic tasks,
such as verifying species names, and getting taxonomic 'hierarchies'.
Automated standardization of taxonomic names and removal of orthographic errors in plant species names using 'The Plant List' website (www.theplantlist.org).
Solves Teitz and Bart's p-median problem - given a set of
points attempts to find subset of size p such that summed distances of any
point in the set to the nearest point in p is minimised.  Although
generally effective, this algorithm does not guarantee that a globally
optimal subset is found.
This package provides functions to assist researchers
working in the field of tuberculosis diagnostics.  Functions
for the interpretation of two popular interferon-gamma release
assays are provided, and additional functionality is planned.
Our method introduces mathematically well-defined measures for tightness of branches in a hierarchical tree. Statistical significance of the findings is determined, for all branches of the tree, by performing permutation tests, optionally with generalized Pareto p-value estimation.
Functions to perform the reliability/survival
analysis using a parametric Transform-both-sides (TBS) model.
Automatically downloads and processes TCGA genomics and clinical data into a format convenient for statistical analyses in the R environment.
The Cancer Genome Atlas (TCGA) is a program aimed at improving our understanding of Cancer Biology. Several TCGA Datasets are available online. 'TCGAretriever' helps accessing and downloading TCGA data hosted on 'cBioPortal' via its Web Interface (see <http://www.cbioportal.org/web_api.jsp> for more information). Features of 'TCGAretriever' include: 1) it is very simple to use (get all the TCGA data you need with a few lines of code); 2) performance (smooth and reliable data download via 'httr'); 3) it is tailored for downloading large volumes of data.
Implementation of TcGSA, a method for analyzing longitudinal
gene-expression data at the gene set level.
Gene set analysis of longitudinal RNA-seq data with variance component
score test accounting for data heteroscedasticity through precision weights.
A series of additional Tcl commands and Tk widgets with style
and various functions (under Windows: DDE exchange, access to the
registry and icon manipulation) to supplement the tcltk package
A set of tools for processing and modeling high-throughput and
high-content chemical screening data. The package was developed for the
the chemical screening data generated by the US EPA ToxCast program, but
can be used for diverse chemical screening efforts.
Platform for the advanced analysis of T cell receptor and
Immunoglobulin repertoires data and visualisation of the analysis results.
Tools for the statistical analysis of persistent homology and for density clustering. For that, this package provides an R interface for the efficient algorithms of the C++ libraries GUDHI, Dionysus, and PHAT.
Topological Data Analysis using Mapper (discrete Morse theory).
Generate a 1-dimensional simplicial complex from a filter
function defined on the data:  1. Define a filter function (lens) on the
data.  2. Perform clustering within within each level set and generate
one node (vertex) for each cluster.  3. For each pair of clusters in
adjacent level sets with a nonempty intersection, generate one edge
between vertices.  The function mapper1D uses a filter function with
codomain R, while the the function mapper2D uses a filter function with
codomain R^2.
A boosted Tweedie compound Poisson model using the gradient boosting. It is capable of fitting a flexible nonlinear Tweedie compound Poisson model (or a gamma model) and capturing interactions among predictors.
The Time-Delay Correlation algorithm (TDCor) reconstructs the topology of a gene regulatory network (GRN) from time-series transcriptomic data.  The algorithm is described in details in Lavenus et al., Plant Cell, 2015.  It was initially developed to infer the topology of the GRN controlling lateral root formation in Arabidopsis thaliana.  The time-series transcriptomic dataset which was used in this study is included in the package to illustrate how to use it.
Deconvolution of instrument responses from seismic traces and seismogram lists from RSEIS.  Includes pre-calculated instrument responses for several common instruments.
Tuned Data Mining in R (TDMR) performs a complete tuning of a data
mining task.
Implementation of target diagrams using 'lattice' and 'ggplot2' graphics. Target diagrams provide a graphical overview of the respective contributions of the unbiased RMSE and MBE to the total RMSE (Jolliff, J. et al., 2009. "Summary Diagrams for Coupled Hydrodynamic-Ecosystem Model Skill Assessment." Journal of Marine Systems 76: 64–82.)
Compute time-dependent ROC curve from censored survival data using
nonparametric weight adjustments.
Transmission/disequilibrium tests for extended marker haplotypes
Demonstration functions that can be used in a classroom to demonstrate statistical concepts, or on your own to better understand the concepts or the programming.
Allows the user to draw probabilistic samples and make inferences from a finite population based on several sampling designs.
Can fit neural networks with up to two hidden layer and two different error functions. Also able to handle a weight decay. But just able to compute one output neuron and very slow.
TED performs Turbulence time series Event Detection and classification.
For fitting multiple linear regressions, the ordinary least squares approach is sensitive to outliers and/or violations of model assumptions. The trimmed elemental estimators are more robust to such situations. This package contains functions for computing the trimmed elemental estimates, as well as for creating the bias-corrected and accelerated bootstrap confidence intervals based on elemental regressions.
Fits mixtures of multivariate t-distributions (with eigen-decomposed covariance structure) via the expectation conditional-maximization algorithm under a clustering or classification paradigm.
R wrapper around the Telegram Bot API (http://core.telegram.org/bots/api) to access Telegram's messaging facilities with ease (e.g. you send messages, images, files from R to your smartphone).
Using The Free Evocation of Words Technique method with some functions, this package will make a
social representation and other analysis. The Free Evocation of Words Technique consists of collecting a number of words evoked by a subject facing exposure to an inducer term. The purpose of this technique is to understand the relationships created between words evoked by the individual and the inducer term. This technique is included in the theory of social representations, therefore, on the information transmitted by an individual, seeks to create a profile that define a social group.
This is the data companion package to the package tempcycles.
This package includes the metadata, linear, and cycling parameters from
"Recent geographic convergence in diurnal and annual temperature cycling
flattens global thermal profiles", Wang & Dillon, Nature Climate Change,
4, 988-992 (2014). doi:10.1038/nclimate2378.
Temporal disaggregation methods are used to disaggregate and
interpolate a low frequency time series to a higher frequency series, where
either the sum, the average, the first or the last value of the resulting
high frequency series is consistent with the low frequency series. Temporal
disaggregation can be performed with or without one or more high frequency
indicator series. Contains the methods of Chow-Lin, Santos-Silva-Cardoso,
Fernandez, Litterman, Denton and Denton-Cholette.
Analysis and visualization of data from temporal sensory methods, including for temporal check-all-that-apply (TCATA) and temporal dominance of sensations (TDS).
The tensor product of two arrays is notionally an outer
product of the arrays collapsed in specific extents by summing
along the appropriate diagonals.
The package provides convenience functions for advance
linear algebra with tensors and computation with datasets of
tensors on a higher level abstraction. It includes Einstein and
Riemann summing conventions, dragging, co- and contravariate
indices, parallel computations on sequences of tensors.
Contains several utility functions for manipulating tensor-valued data (centering, multiplication from a single mode etc.) and the implementations of the following blind source separation methods for tensor-valued data: tFOBI, tJADE, tgFOBI, tgJADE and tSOBI.
A collection of functions for Kronecker structured covariance
estimation and testing under the array normal model. For estimation,
maximum likelihood and Bayesian equivariant estimation procedures are
implemented. For testing, a likelihood ratio testing procedure is
available. This package also contains additional functions for manipulating
and decomposing tensor data sets. This work was partially supported by NSF
grant DMS-1505136.
The TEQR package contains software to calculate the operating characteristics for the TEQR and the ACT designs.The TEQR (toxicity equivalence range) design is a toxicity based cumulative cohort design with added safety rules. The ACT (Activity constrained for toxicity) design  is also a cumulative cohort design with additional safety rules. The unique feature of this design is that dose is escalated based on lack of activity rather than on lack of toxicity and is de-escalated only if an unacceptable level of toxicity is experienced.
This package is for the comparison of various types of A+B
escalation rules for dose finding trials.
An integrated set of extensions to the 'ergm' package to analyze and simulate network evolution based on exponential-family random graph models (ERGM). 'tergm' is a part of the 'statnet' suite of packages for network analysis.
The package offers a wide range of functions for term
structure estimation based on static and dynamic coupon bond
and yield data sets. The implementation focuses on the cubic
splines approach of McCulloch (1971, 1975) and the Nelson and
Siegel (1987) method with extensions by Svensson (1994),
Diebold and Li (2006) and De Pooter (2007). We propose a
weighted constrained optimization procedure with analytical
gradients and a globally optimal start parameter search
algorithm. Extensive summary statistics and plots are provided
to compare the results of the different estimation methods.
Several demos are available using data from European government
bonds and yields.
A suite of functions for visualising ternary probabilistic
forecasts.
Simulation of reconstructed phylogenetic trees under tree-wide time-heterogeneous birth-death processes and estimation of diversification parameters under the same model. Speciation and extinction rates can be any function of time and mass-extinction events at specific times can be provided. Trees can be simulated either conditioned on the number of species, the time of the process, or both. Additionally, the likelihood equations are implemented for convenience and can be used for Maximum Likelihood (ML) estimation and Bayesian inference.
Functions for imputing missing item responses for dichotomous and
polytomous test and assessment data. This package enables missing imputation
methods that are suitable for test and assessment data, including: listwise (LW)
deletion, treating as incorrect (IN), person mean imputation (PM), item mean
imputation (IM), two-way imputation (TW), logistic regression imputation (LR),
and EM imputation.
tester allows you to test characteristics of common R objects.
Provides a bootstrap test which decides whether two dose response curves can be assumed as equal concerning their maximum absolute deviation. A plenty of choices for the model types are available, which can be found in the 'DoseFinding' package, which is used for the fitting of the models.
Provides two convenience functions assert() and test_pkg() to
facilitate testing R packages.
GUI for entering test items and obtaining raw
and transformed scores. The results are shown on the
console and can be saved to a tabular text file for further
statistical analysis. The user can define his own tests and
scoring procedures through a GUI.
These are weighted tests type logrank for recurrent events.
A unit testing system designed to be fun, flexible and easy to
set up.
Statistical extreme value modelling of threshold excesses,
maxima and multivariate extremes.  Univariate models for threshold
excesses and maxima are the Generalised Pareto, and Generalised
Extreme Value model respectively.  These models may be fitted by
using maximum (optionally penalised-)likelihood, or Bayesian
estimation, and both classes of models may be fitted with covariates
in any/all model parameters.  Model diagnostics support the fitting
process. Graphical output for visualising fitted models and return
level estimates is provided.  For serially dependent sequences, the
intervals declustering algorithm of Ferro and Segers is provided,
with diagnostic support to aid selection of threshold and declustering
horizon.  Multivariate modelling is performed via the conditional
approach of Heffernan and Tawn, with graphical tools for threshold
selection and to diagnose estimation convergence.
Analysis and visualization of community dynamics in microbial
ecology experiments (that use sequence count data) using the
truncated Poisson lognormal distribution.
TExPosition is an extension of ExPosition for two table analyses, specifically, discriminant analyses.
Converts coefficients, standard errors, significance stars, and goodness-of-fit statistics of statistical models into LaTeX tables or HTML tables/MS Word documents or to nicely formatted screen output for the R console for easy model comparison. A list of several models can be combined in a single table. The output is highly customizable. New model types can be easily implemented.
Very fast and memory-friendly tools for text vectorization and
state-of-the-art word embeddings (GloVe). This package provides a
source-agnostic streaming API, which allows researchers to perform analysis
of collections of documents which are much larger than available RAM. All
core functions are parallelized to benefit from multicore machines.
Multinomial [inverse] regression inference for text documents and associated attributes. Provides fast sparse multinomial logistic regression for phrase counts.  A minimalist partial least squares routine is also included.  Note that the topic modeling capability of textir is now a separate package, maptpx.
An aid for text mining in R, with a syntax that
should be familiar to experienced R users. Provides a wrapper for several
topic models that take similarly-formatted input and give similarly-formatted
output. Has additional functionality for analyzing and diagnostics for
topic models.
Statistical exploration of textual corpora using several methods
from French 'Textometrie' (new name of 'Lexicometrie') and French 'Data Analysis' schools.
It includes methods for exploring irregularity of distribution of lexicon features across
text sets or parts of texts (Specificity analysis); multi-dimensional exploration (Factorial analysis), etc.
Those methods are used in the TXM software.
Function for sparse regression on raw text, regressing a labeling
vector onto a feature space consisting of all possible phrases.
Tools for measuring similarity among documents and detecting
passages which have been reused. Implements shingled n-gram, skip n-gram,
and other tokenizers; similarity/dissimilarity functions; pairwise
comparisons; minhash and locality sensitive hashing algorithms; and a
version of the Smith-Waterman local alignment algorithm suitable for
natural language.
The TFDEA algorithm for technology forecasts when future products
will be introduced based upon their features.
It also includes DEA (Data Envelopment Analysis) functions including extensions dealing with
with infeasibility.
In addition it includes some standard technology forecasting data sets.
Statistical interpretation of forensic glass transfer
(Simulation of the probability distribution of recovered glass
fragments).
In putative Transcription Factor Binding Sites (TFBSs)
identification from sequence/alignments,
we are interested in the significance of certain match score.
TFMPvalue provides the accurate calculation of P-value with
score threshold for Position Weight Matrices,
or the score with given P-value.
This package is an interface to code originally made available by
Helene Touzet and Jean-Stephane Varre, 2007,
Algorithms Mol Biol:2, 15.
Utilities for simple manipulation and quick
plotting of time series data. These utilities use the tframe package
which provides a programming kernel for time series. Extensions to
tframe provided in tframePlus can also be used. See the Guide vignette
for examples.
A kernel of functions for programming
time series methods in a way that is relatively independently of the
representation of time. Also provides plotting, time windowing,
and some
other utility functions which are specifically intended for time series.
See the Guide distributed as a vignette, or ?tframe.Intro for more
details. (User utilities are in package tfplot.)
Extensions and additional tframe utilities.
Connects R to TrueFX(tm) for free streaming real-time and
historical tick-by-tick market data for dealable interbank
foreign exchange rates with millisecond detail.
Deconvolving thermoluminescence glow curves according to the general-order
empirical expression or the semi-analytical expression derived from the one trap-
one recombination (OTOR) model based on the Lambert's W function using a modified
Levenberg-Marquardt algorithm. It provides the possibility of setting constraints
or fixing any of parameters. It offers an interactive way to initialize parameters
by clicking with a mouse on a plot at positions where peak maxima should be located.
The optimal estimate is obtained by "trial-and-error". It also provides routines
for simulating first-order, second-order, and general-order glow peaks (curves).
Density, distribution function, quantile function and random generation for the Truncated Generalised Gamma Distribution (also in log10(x) and ln(x) space).
Use Gibbs sampler with Polya-Gamma data augmentation to fit logistic and probit regression under independent Student-t priors (including Cauchy priors and normal priors as special cases).
Bayesian nonstationary, semiparametric nonlinear regression
and design by treed Gaussian processes (GPs) with jumps to the limiting
linear model (LLM).  Special cases also implemented include Bayesian
linear models, CART, treed linear models, stationary separable and
isotropic GPs, and GP single-index models.  Provides 1-d and 2-d plotting functions
(with projection and slice capabilities) and tree drawing, designed for
visualization of tgp-class output.  Sensitivity analysis and
multi-resolution models are supported. Sequential experimental
design and adaptive sampling functions are also provided, including ALM,
ALC, and expected improvement.  The latter supports derivative-free
optimization of noisy black-box functions.
Functions to compute and plot tracheidograms
Contains data sets used in other packages Torsten Hothorn
maintains.
A collection of functions and routines for inputting thermal
image video files, plotting and converting binary raw data into estimates of
temperature.  First published 2015-03-26.  Written primarily for research purposes
in biological applications of thermal images.  v1 included the base calculations
for converting thermal image binary values to temperatures. v2 included additional
equations for providing heat transfer calculations and an import function for thermal
image files.
Temperature measurement data, equations and methods for thermocouples,
wire RTD, thermistors, IC thermometers, bimetallic strips and the ITS-90.
This package interacts directly with the Thinknum API to offer data
in a number of formats usable in R
Design and analyze three-arm non-inferiority or superiority trials
which follow a gold-standard design, i.e. trials with an experimental treatment,
an active, and a placebo control.
This package implements a thresholded version of the EEBoost
algorithm described in [Wolfson (2011, JASA)]. EEBoost is a general-purpose
method for variable selection which can be applied whenever inference would
be based on an estimating equation. The package currently implements
variable selection based on the Generalized Estimating Equations, but can
also accommodate user-provided estimating functions. Thresholded EEBoost is
a generalization which allows multiple variables to enter the model at each
boosting step.
Implements the Maximum Likelihood estimator for baseline, placebo, and treatment groups (three-group) experiments with non-compliance proposed by Gerber, Green, Kaplan, and Kern (2010).
Create interactive 3D scatter plots, network plots, and
globes using the 'three.js' visualization library ("http://threejs.org").
Component analysis for three-way data arrays by means of Candecomp/Parafac, Tucker3, Tucker2 and Tucker1 models.
A connector to the 'What3Words' (http://what3words.com/) service, which represents each 3m by 3m square on earth
with a unique trio of English-language words.
Fit a threshold regression model based on the first-hitting-time of a boundary by the sample path of a Wiener diffusion process. The threshold regression methodology is well suited to applications involving survival and time-to-event data.
Fit a threshold regression model for interval-censored data based on the first-hitting-time of a boundary by the sample path of a Wiener diffusion process. The threshold regression methodology is well suited to applications involving survival and time-to-event data.
Point and interval estimations of optimum thresholds for continuous diagnostic tests (two- and three- state settings).
Fit the Simultaneous Systems of Linear Equations using Three-stage Least Squares.
Provides a 'tbl_df' class that offers better checking and
printing capabilities than traditional data frames.
Functions to execute orders in backtesting using tick data. A testing platform was established by the four major execution functions, namely 'LimitBuy', 'LimitSell', 'MarketBuy' and 'MarketSell', which enclosed all tedious aspects (such as queueing for order executions and calculate actual executed volumes) for order execution using tick data. Such that one can focus on the logic of strategies, rather than its execution.
This package provides the timing functions 'tic' and 'toc' that
can be nested. One can record all timings while a complex script is
running, and examine the values later. It is also possible to instrument
the timing calls with custom callbacks. In addition, this package provides
class 'Stack', implemented as a vector, and class 'List', implemented as a
list, both of which support operations 'push', 'pop', 'first', 'last' and
'clear'.
Utilities to generate wiki reports in TiddlyWiki format.
Tidal analysis of evenly spaced observed time series (time step 1 to 60 min) with or
without shorter gaps.
The analysis should preferably cover an observation period of at least 19 years.
For shorter periods low frequency constituents are not taken into account, in accordance with the Rayleigh-Criterion.
The main objective of this package is to synthesize or predict a tidal time series.
Implements harmonic analysis of tidal and sea-level data.
Over 400 harmonic tidal constituents can be estimated, all with
daily nodal corrections. Time-varying mean sea-levels can also
be used.
Calculate Characteristics of Qasi-Periodic Time Series, e.g. Estuarine Water Levels.
Tide analysis and prediction of predominantly semi-diurnal tides
with two high waters and two low waters during one lunar day (~24.842 hours,
~1.035 days). The analysis should preferably cover an observation period of at
least 19 years. For shorter periods, for example, the nodal cycle can not be
taken into account, which particularly affects the height calculation. The main
objective of this package is to produce tide tables.
An easy and consistent way to turn 'JSON' into tidy data frames
that are natural to work with in 'dplyr', 'ggplot2' and other tools.
An evolution of 'reshape2'. It's designed specifically for data
tidying (not general reshaping or aggregating) and works well with
'dplyr' data pipelines.
Text mining for word processing and sentiment analysis using
'dplyr', 'ggplot2', and other tidy tools.
This package provides an easy and simple way to read, write and display bitmap images stored in the TIFF format. It can read and write both files and in-memory raw vectors.
Temporally resolved groups of typical differences (errors) between two time series are determined and visualized
Pre-process for discrete time series data set which is not continuous at the column
of 'date'. Refilling records of missing 'date' and other columns to the hollow data set so that
final data set is able to be dealt with time series analysis.
A collection of data sets and functions that are useful in the
teaching of statistics at an elementary level to students who may have
little or no previous experience with the command line.  The functions for
elementary inferential procedures follow a uniform interface for user
input.  Some of the functions are instructional applets that can only be
run on the R Studio integrated development environment with package
'manipulate' installed.  Other instructional applets are Shiny apps
that may be run locally. In teaching the package is used alongside of
package 'mosaic', 'mosaicData' and 'abd', which are therefore listed as
dependencies.
Infers the V genotype of an individual from immunoglobulin (Ig)
repertoire-sequencing (Rep-Seq) data, including detection of any novel
alleles. This information is then used to correct existing V allele calls
from among the sample sequences.
This package contains functions for tight clustering
Algorithm.
Download TIGER/Line shapefiles from the United States Census Bureau
and load into R as 'SpatialDataFrame' objects.
Provides a graphics output device for R that records plots
in a LaTeX-friendly format. The device transforms plotting
commands issued by R functions into LaTeX code blocks. When
included in a LaTeX document, these blocks are interpreted with
the help of 'TikZ'---a graphics package for TeX and friends
written by Till Tantau. Using the 'tikzDevice', the text of R
plots can contain LaTeX commands such as mathematical formula.
The device also allows arbitrary LaTeX code to be inserted into
the output stream.
Methods and classes to build HMMs
that are suitable for the analysis of ChIP-chip data. The
provided parameter estimation methods include the Baum-Welch
algorithm and Viterbi training as well as a combination of
both.
This package is intended for processing the output from
functional gene tiling DNA microarray experiments. It produces
hybridization pattern plots for each gene on the array, and
statistics for each gene including mean probe intensity, median
probe intensity, bright probe fraction, bright segment length
dependent score, bright probe mean intensity, and bright probe
median intensity. Output is generated in order of bright
segment length dependent score in both a latex/eps format and
tab-delimited text file. The package works in two modes: single
array, and comparison of two arrays. Array comparison includes
array comparison statistics: median of logarithm of one array
probe divided by its counterpart on the other array, median
absolute deviation of that value, and the binomial test to see
whether the genes are equally abundant in both arrays.
Implements an algorithm for variable selection in high-dimensional linear regression using the "tilted correlation", a new way of measuring the contribution of each variable to the response which takes into account high correlations among the variables in a data-driven way.
Cox proportional hazard and competing risk regression analyses can be performed with time-to-event data as covariates.
Environment for teaching
"Financial Engineering and Computational Finance".
Managing chronological and calendar objects.
We provide a toolbox to estimate the time delay between the brightness time series of gravitationally lensed quasar images via Bayesian and profile likelihood approaches. The model is based on a state-space representation for  irregularly observed time series data generated from a latent continuous-time Ornstein-Uhlenbeck process. Our Bayesian method adopts scientifically motivated hyper-prior distributions and a Metropolis-Hastings within Gibbs sampler, producing posterior samples of the model parameters that include the time delay. A profile likelihood of the time delay is a simple approximation to the marginal posterior distribution of the time delay. Both Bayesian and profile likelihood approaches complement each other, producing almost identical results; the Bayesian way is more principled but the profile likelihood is easier to implement.
Provides an easy-to-use wrapper to Rprof() and
summaryRprof() in the profiling of both function calls and
whole blocks of code.
An easy tool for plotting annotated timelines, grouped timelines, and exploratory graphics (boxplot/histogram/density plot/scatter plot/line plot). Filter, summarize date data by duration and convert to calendar units.
Implements the Time Machine, a simulation approach for stochastic
trees.
Methods for incorporating time into network analysis. Construction of time-ordered networks (temporal graphs). Shortest-time and shortest-path-length analyses. Resource spread calculations. Data resampling and rarefaction for null model construction. Reduction to time-aggregated networks with variable window sizes; application of common descriptive statistics to these networks. Vector clock latencies. Plotting functionalities.
Extract useful time components of a date object, such as
day of week, weekend, holiday, day of month, etc, and put it in
a data frame.  This can be used to create many predictor
variables out of a single time variable, which can then be used
in a regression or decision tree.  Also includes function
plotCalendarHeatmap which draws a calendar and overlays a
heatmap based on values.
Programs for Martinussen and Scheike (2006), `Dynamic Regression
Models for Survival Data', Springer Verlag.  Plus more recent developments.
Additive survival model, semiparametric proportional odds model, fast cumulative
residuals, excess risk models and more. Flexible competing risks regression
including GOF-tests. Two-stage frailty modelling.
PLS for the additive risk model. Lasso in the 'ahaz' package.
Estimation of time-dependent ROC curve and area under time dependent ROC curve (AUC) in the presence of censored data, with or without competing risks. Confidence intervals of AUCs and tests for comparing AUCs of two rival markers measured on the same subjects can be computed, using the iid-representation of the AUC estimator. Plot functions for time-dependent ROC curves and AUC curves are provided. Time-dependent Positive Predictive Values (PPV) and Negative Predictive Values (NPV) can also be computed.
Computes bootstrap CI for the sample ACF and periodogram
Uses a negative binomial mixed-effects (NBME) model to detect nonparallel differential expression(NPDE) genes and parallel differential expression(PDE) genes in the time course RNA-seq data.
Environment for teaching
"Financial Engineering and Computational Finance".
Managing financial time series objects.
Store and organize a large amount of low frequency time series data.
The package was designed to manage a large catalog of official statistics which are
typically published on monthly, quarterly or yearly basis. Thus timeseriesdb is
optimized to handle a large number of lower frequency time series as opposed to a
smaller amount of high frequency time series such as real time data from measuring devices.
Hence timeseriesdb provides the opportunity to store extensive multi-lingual
meta information. The package also provides a web GUI to explore the underlying
PostgreSQL database interactively.
Objects to manipulate sequential and seasonal time series. Sequential time series based on time instants and time durations are handled. Both can be regularly or unevenly spaced (overlapping durations are allowed). Only POSIX* format are used for dates and times. The following classes are provided : 'POSIXcti', 'POSIXctp', 'TimeIntervalDataFrame', 'TimeInstantDataFrame', 'SubtimeDataFrame' ; methods to switch from a class to another and to modify the time support of series (hourly time series to daily time series for instance) are also defined. Tools provided can be used for instance to handle environmental monitoring data (not always produced on a regular time base).
A interface to the TimeTree of Life Webpage (www.timetree.org). TimeTree is a public database for information on the evolutionary timescale of life. This package includes functions for searching divergence time for  taxa or all nodes of a phylogeny.
Create rich and fully interactive timeline visualizations.
Timelines can be included in Shiny apps and R markdown documents, or viewed
from the R console and RStudio Viewer. 'timevis' includes an extensive API
to manipulate a timeline after creation, and supports getting data out of
the visualization into R. Based on the 'vis.js' Timeline module and the
'htmlwidgets' R package.
Date sequence, relative date calculations, and date manipulation with business days
and holidays.  Works with Date and POSIXt classes.
Prediction and ranking of drug combinations based on their drug-target interaction profiles and single-drug sensitivities in a given cancer cell line or patient-derived sample.
A problem-solving environment (PSE) for fitting
separable nonlinear models to measurements arising in physics
and chemistry experiments; has been extensively applied to
time-resolved spectroscopy and FLIM-FRET data.
Functions for statistical analysis, prediction and control of time series.
A universal non-uniform random number generator
for quite arbitrary distributions with piecewise twice
differentiable densities.
Non-parametric resampling-based inference tests for TExPosition.
Assist performing tip-dating of phylogenetic trees with BEAST.
TIPOM is based on a methodology that was developed in the
1960s by Bernardino Bagolini. The basic idea is to use
the three simple dimensions of length, width and thickness
of each lithic artefact to classify them in discrete
groups and infer their function.
Using the idea of "tipping point" (proposed in
Gregory Campbell, Gene Pennello and Lilly Yue(2011)
<DOI:10.1080/10543406.2011.550094>) to visualize  the results
of sensitivity analysis for missing data, the package provides
a set of functions to list out all the possible combinations
of the values of missing data in two treatment arms, calculate
corresponding estimated treatment effects and p values and draw
a colored heat-map to visualize them. It could deal with randomized
experiments with a binary outcome or a continuous outcome. In addition,
the package provides a visualized method to compare various imputation
methods by adding the rectangles or convex hulls on the basic plot.
Functions and S3 classes for time indexes and time indexed
series, which are compatible with FAME frequencies.
GUI to analyze mass spectrometric data on the relative
abundance of two substances from a titration series.
Uses indicator species scores across binary partitions of
a sample set to detect congruence in taxon-specific changes of abundance
and occurrence frequency along an environmental gradient as evidence of
an ecological community threshold.  Relevant references include: Baker,
ME and RS King. 2010. A new method for detecting and interpreting
biodiversity and ecological community thresholds.  Methods in Ecology and
Evolution 1(1): 25:37. King, RS and ME Baker. 2010. Considerations for
identifying and interpreting ecological community thresholds.  Journal
of the North American Benthological Association 29(3):998-1008. Baker ME
and RS King. 2013. Of TITAN and straw men: an appeal for greater
understanding of community data. Freshwater Science 32(2):489-506.
This data set provides information on the fate of passengers on
the fatal maiden voyage of the ocean liner "Titanic", summarized according
to economic status (class), sex, age and survival. Whereas the base R
Titanic data found by calling data("Titanic") is an array resulting from
cross-tabulating 2201 observations, these data sets are the individual
non-aggregated observations and formatted in a machine learning context
with a training sample, a testing sample, and two additional data sets
that can be used for deeper machine learning analysis. These data sets
are also the data sets downloaded from the Kaggle competition and thus
lowers the barrier to entry for users new to R or machine learing.
A collection of functions to plot acid/base titration
curves (pH vs. volume of titrant), complexation titration curves
(pMetal vs. volume of EDTA), redox titration curves (potential
vs.volume of titrant), and precipitation titration curves (either
pAnalyte or pTitrant vs. volume of titrant). Options include the
titration of mixtures, the ability to overlay two or more
titration curves, and the ability to show equivalence points.
Pairwise evolutionary distance estimation between protein sequences with the TKF91 and TKF92 model, which consider all the possible paths of transforming from one sequence to another.
simple mechanism for placing R graphics in a Tk widget
Contains functions for training and applying two-level random forest and hidden Markov models for human behavior classification from raw tri-axial accelerometer and/or GPS data. Includes functions for training a two-level model, applying the model to data, and computing performance.
A series of function to make thermoluminescence dating using the MAAD or the SAR protocol.
This package completes the R package "Luminescence."
TLE implements a general framework for robust fitting of
finite mixture models. Parameter estimation is performed using
the EM algorithm.
Computation of effects under linear, logistic and Poisson regression models with transformed variables. Logarithm and power transformations are allowed. Effects can be displayed both numerically and graphically in both the original and the transformed space of the variables.
Fit a linear mixed effects model for censored data with
Student-t or normal distributions. The errors are assumed
independent and identically distributed.
Functions for two level normal models as described in
Everson and Morris (2000). J. R. Statist. Soc. B, 62 prt 2,
pp.399--412.
A framework for text mining applications within R.
Thematic maps are geographical maps in which spatial data distributions are visualized. This package offers a flexible, layer-based, and easy to use approach to create thematic maps, such as choropleths and bubble maps.
With this tool, a user should be able to quickly implement complex
random effect models through simple C++ templates. The package combines
CppAD (C++ automatic differentiation), Eigen (templated matrix-vector
library) and CHOLMOD (sparse matrix routines available from R) to obtain an
efficient implementation of the applied Laplace approximation with exact
derivatives. Key features are: Automatic sparseness detection, parallelism
through BLAS and parallel user templates.
Provides an R-interface to the TMDb API (see TMDb API on <http://docs.themoviedb.apiary.io/#>). The Movie Database (TMDb) is a popular user editable database for movies and TV shows (see <https://www.themoviedb.org>).
Random number generation of truncated multivariate Gaussian distributions using Hamiltonian Monte Carlo. The truncation is defined using linear and/or quadratic polynomials.
Miscellaneous data and utility functions
for manipulating data and your R environment.
tmle implements targeted maximum likelihood estimation, first described in van der Laan and Rubin, 2006 (Targeted Maximum Likelihood Learning, The International Journal of biostatistics, 2(1), 2006.  This version adds the tmleMSM function to the package, for estimating the parameters of a marginal structural model (MSM) for a binary point treatment effect.  The tmle function calculates the adjusted marginal difference in mean outcome associated with a binary point treatment, for continuous or binary outcomes.  Relative risk and odds ratio estimates are also reported for binary outcomes. Missingness in the outcome is allowed, but not in treatment assignment or baseline covariate values. Effect estimation stratified by a binary mediating variable is also available. The population mean is calculated when there is missingness, and no variation in the treatment assignment.  An ID argument can be used to identify repeated measures. Default settings call SuperLearner to estimate the Q and g portions of the likelihood, unless values or a user-supplied regression function are passed in as arguments.
Estimation of average causal effects for single time point
interventions in network-dependent data (e.g., in the presence of spillover
and/or interference). Supports arbitrary interventions (static or
stochastic). Implemented estimation algorithms are the targeted maximum
likelihood estimation (TMLE), the inverse-probability-of-treatment (IPTW)
estimator and the parametric G-computation formula estimator. Asymptotically
correct influence-curve-based confidence intervals are constructed for the
TMLE and IPTW. The data are assumed to consist of rows of unit-specific
observations, each row i represented by variables (F.i,W.i,A.i,Y.i), where
F.i is a vector of friend IDs of unit i (i's network), W.i is a vector of
i's baseline covariates, A.i is i's exposure (can be binary, categorical or
continuous) and Y.i is i's binary outcome. Exposure A.i depends on
(multivariate) user-specified baseline summary measure(s) sW.i, where sW.i
is any function of i's baseline covariates W.i and the baseline covariates
of i's friends in F.i. Outcome Y.i depends on sW.i and (multivariate)
user-specified summary measure(s) sA.i, where sA.i is any function of i's
baseline covariates and exposure (W.i,A.i) and the baseline covariates and
exposures of i's friends. The summary measures are defined with functions
def.sW and def.sA. See ?'tmlenet-package' for a general overview.
Targeted minimum loss estimation (TMLE) of a non-parametric variable importance measure of a continuous exposure 'X' on an outcome 'Y', taking baseline covariates 'W' into account.
Methods and feature set definitions for feature or gene set
enrichment analysis in transcriptional and metabolic profiling data.
Package includes tests for enrichment based on ranked lists of features,
functions for visualisation and multivariate functional analysis.
This package provides a tm Source to create corpora from
a corpus prepared in the format used by the Alceste application (i.e.
a single text file with inline meta-data). It is able to import both
text contents and meta-data (starred) variables.
A plug-in for the text mining framework tm to support text mining
in a distributed way. The package provides a convenient interface for
handling distributed corpus objects based on distributed list objects.
Provides a 'tm' Source to create corpora from
articles exported from the 'Europresse' content provider as
HTML files. It is able to read both text content and meta-data
information (including source, date, title, author and pages).
This package provides a tm Source to create corpora from
articles exported from the Dow Jones Factiva content provider as
XML or HTML files. It is able to read both text content and meta-data
information (including source, date, title, author, subject,
geographical coverage, company, industry, and various
provider-specific fields).
Provides a 'tm' Source to create corpora from
articles exported from the 'LexisNexis' content provider as
HTML files. It is able to read both text content and meta-data
information (including source, date, title, author and pages).
Note that the file format is highly unstable: there is no warranty
that this package will work for your corpus, and you may have
to adjust the code to adapt it to your particular format.
A plug-in for the tm text mining framework providing mail handling
functionality.
Facilitate text retrieval from feed
formats like XML (RSS, ATOM) and JSON. Also direct retrieval from
HTML is supported. As most (news) feeds only incorporate small
fractions of the original text tm.plugin.webmining even retrieves
and extracts the text of the original text source.
Trauma Mortality prediction for ICD-9, ICD-10, and AIS lexicons in
long or wide format based on Dr. Alan Cook's tmpm mortality model.
Importance sampling from the truncated multivariate normal using the GHK (Geweke-Hajivassiliou-Keane) simulator.
Unlike Gibbs sampling which can get stuck in one truncation sub-region depending on initial values, this package allows
truncation based on disjoint regions that are created by truncation of absolute values. The GHK algorithm uses simple Cholesky
transformation followed by recursive simulation of univariate truncated normals hence there are also no convergence issues.
Importance sample is returned along with sampling weights, based on which, one can calculate integrals over truncated regions
for multivariate normals.
Random number generation for the truncated multivariate normal and Student t distribution.
Computes probabilities, quantiles and densities,
including one-dimensional and bivariate marginal densities. Computes first and second moments (i.e. mean and covariance matrix) for the double-truncated multinormal case.
Temporal and cross-sectional network autocorrelation models (TNAM).
R package for analyzing weighted, two-mode, and longitudinal networks.
A consistent set of tools to perform in-database analytics
on Teradata Aster Big Data Discovery Platform. toaster (a.k.a 'to Aster')
embraces simple 2-step approach: compute in Aster - visualize and analyze
in R. Its `compute` functions use combination of parallel SQL, SQL-MR and
SQL-GR executing in Aster database - highly scalable parallel
and distributed analytical platform. Then `create` functions visualize
results with boxplots, scatterplots, histograms, heatmaps, word clouds,
maps, networks, or slope graphs. Advanced options such as faceting, coloring,
labeling, and others are supported with most visualizations.
Construction of the Total Operating Characteristic (TOC) Curve and the Receiver (aka Relative) Operating Characteristic (ROC) Curve for spatial and non-spatial data. The TOC method is a modification of the ROC method which measures the ability of an index variable to diagnose either presence or absence of a characteristic. The diagnosis depends on whether the value of an index variable is above a threshold. Each threshold generates a two-by-two contingency table, which contains four entries: hits (H), misses (M), false alarms (FA), and correct rejections (CR). While ROC shows for each threshold only two ratios, H/(H + M) and FA/(FA + CR), TOC reveals the size of every entry in the contingency table for each threshold (Pontius Jr., R.G., Si, K. 2014. The total operating characteristic to measure diagnostic ability for multiple thresholds. Int. J. Geogr. Inf. Sci. 28 (3), 570-583).
Convert natural language text into tokens. The tokenizers have a
consistent interface and are compatible with Unicode, thanks to being built
on the 'stringi' package. Includes tokenizers for shingled n-grams, skip
n-grams, words, word stems, sentences, paragraphs, characters, lines, and
regular expressions.
Imports the fundamental definitions and utilities of the Time Oriented Language (TOL), focused on time series analysis and stochastic processes, and provides the basis for the integration of TOL in R. See <https://www.tol-project.org> for more information about the TOL project.
Statistical tolerance limits provide the limits between which we can expect to find a specified proportion of a sampled population with a given level of confidence.  This package provides functions for estimating tolerance limits for various distributions.  Plotting is also available for tolerance limits of continuous random variables.
Function for converting cardinal to ordinal numbers by adding a language specific ordinal indicator (http://en.wikipedia.org/wiki/Ordinal_indicator) to the number.
Provides an interface to the C code for Latent Dirichlet
Allocation (LDA) models and Correlated Topics Models
(CTM) by David M. Blei and co-authors and the C++ code
for fitting LDA models using Gibbs sampling by Xuan-Hieu
Phan and co-authors.
For multiple ranked input lists (full or partial) representing the same set of N objects, the package TopKLists offers (1) statistical inference on the lengths of informative top-k lists, (2) stochastic aggregation of full or partial lists, and (3) graphical tools for the statistical exploration of input lists, and for the visualization of aggregation results.
Set of hydrological functions including an R
implementation of the hydrological model TOPMODEL, which is
based on the 1995 FORTRAN version by Keith Beven. From version
0.7.0, the package is put into maintenance mode. New functions
for hydrological analysis are now developed as part of the
RHydro package. RHydro can be found on R-forge and is built on
a set of dedicated S4 classes.
Using Gaussian graphical models we propose a novel approach to
perform pathway analysis using gene expression. Given the
structure of a graph (a pathway) we introduce two statistical
tests to compare the mean and the concentration matrices between
two groups. Specifically, these tests can be performed on the
graph and on its connected components (cliques).
Evaluation of alternatives based on multiple criteria using TOPSIS method.
Fit an Instrumental Variables Two Stage Least Squares model
Quantifies how balanced a phylogenetic tree is, using the Total Cophenetic Index
- per A. Mir, F. Rossello, L. A. Rotger (2013), A new balance index for phylogenetic trees.
Math. Biosci. 241, 125-136 <DOI:10.1016/j.mbs.2012.10.005>.
Implements geodesic interpolation and basis
generation functions that allow you to create new tour
methods from R.
The GUI allows user to control the tour by checkboxes for
the variable selection, slider for the speed, and toggle boxes
for pause.
Provides methods to use bootstrapping to quantify uncertainty
in fitting 'ToxCast' concentration response data. Data is stored in memory,
written to file, or stored in 'MySQL' or 'MongoDB' databases.
Calculates sample size and dose allocation for binary toxicity
tests, using the Fish Embryo Toxicity Test as example.
An optimal test design is obtained by running
(i) spoD (calculate the number of individuals to test under control
conditions), (ii) setD (estimate the minimal sample size per treatment
given the users precision requirements) and (iii) doseD (construct
an individual dose scheme).
This package implements the greedy approximation for tree
preserving embedding.
Estimation of transition probabilities for the illness-death model. Both the Aalen-Johansen estimator for a Markov model and a novel non-Markovian estimator (de Una-Alvarez and Meira-Machado, 2015) are included.
Estimation of transition probabilities for the
illness-death model and or the three-state progressive model.
Regression models for temporal process responses with
time-varying coefficient.
Plant ecologists often need to collect "traits" data
about plant species which are often scattered among various
databases: TR8 contains a set of tools which take care of
automatically retrieving some of those functional traits data
for plant species from publicly available databases (Biolflor,
The Ecological Flora of the British Isles, LEDA traitbase, Ellenberg
values for Italian Flora, Mycorrhizal intensity databases, Catminat, BROT,
PLANTS, Jepson Flora Project).
The TR8 name, inspired by "car plates" jokes, was chosen since
it both reminds of the main object of the package and is
extremely short to type.
Contains functions to standardize tracheid profiles
using the traditional method (Vaganov) and a new method to standardize
tracheidograms based on the relative position of tracheids within tree rings.
Automatically stores objects in files on disk
so that files are rewritten when objects are changed, and
so that objects are accessible but do not occupy memory
until they are accessed. Keeps track of times when objects
are created and modified, and caches some basic
characteristics of objects to allow for fast summaries of
objects.  Also provides a command history mechanism that
saves the last command to a history file after each
command completes.
The aim of this package is to provide infrastructure for handling running and cycling
data from GPS-enabled tracking devices. After extraction and appropriate
manipulation of the training or competition attributes, the data are placed
into session-based and unit-aware data objects of class trackeRdata (S3 class). The
information in the resulting data objects can then be visualised, summarised,
and analysed through corresponding flexible and extensible methods.
Reconstructs animal tracks from magnetometer, accelerometer, depth and optional speed data.  Designed primarily using data from Wildlife Computers Daily Diary tags deployed on northern fur seals.
Functions for working with magnetic resonance images. Analyze,
NIfTI-1, NIfTI-2 and MGH format images can be read and written; DICOM files
can only be read.
Tree Ring Analysis of Disturbance Events in R (TRADER) package provides only one way for disturbance reconstruction from tree-ring data.
An interface for creating GUIs modeled in part after the
traits UI module for python. The basic design takes advantage of
the model-view-controller design pattern. The interface makes basic
dialogs quite easy to produce.
Species trait data from many different sources, including
sequence data from 'NCBI', plant trait data from 'BETYdb', invasive species
data from the Global Invasive Species Database and 'EOL', 'Traitbank' data
from 'EOL', Coral traits data from http://coraltraits.org, 'nativity' status
('Flora Europaea' or 'ITIS'), and 'Birdlife' International.
Implements a predictive model of community assembly called 'Traitspace' (Laughlin et al. 2012, Ecology Letters). Traitspace is a hierarchical Bayesian model that translates the theory of trait-based environmental filtering into a statistical model that incorporates intraspecific trait variation to predict the relative abundances and the distributions of species.
The package includes functions to plot the predicted and the observed values. It also includes functions to compare the predicted values against the observed values using a variety of different distance measures and to implement permutation tests to test their statistical significance.
Implements the three-step procedure proposed by Leffondree et al. (2004) to identify clusters of individual longitudinal trajectories. The procedure involves (1) calculating 24 measures describing the features of the trajectories; (2) using factor analysis to select a subset of the 24 measures and (3) using cluster analysis to identify clusters of trajectories, and classify each individual trajectory in one of the clusters.
Classes and methods for trajectory data, with nested classes for individual trips, and collections for different entities. Methods include selection, generalization, aggregation, intersection, and plotting.
Toolbox for the manipulation, description and rendering of sequences, and more generally the mining of sequence data in the field of social sciences. Although the toolbox is primarily intended for analyzing state or event sequences that describe life courses such as family formation histories or professional careers, its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for converting sequences from one format to another. It offers several functions for describing and rendering sequences, for computing distances between sequences with different metrics (among which optimal matching), original dissimilarity-based analysis tools, and simple functions for extracting the most frequent subsequences and identifying the most discriminating ones among them. A user's guide can be found on the TraMineR web page.
Collection of ancillary functions and utilities to be used in conjunction with the TraMineR package for sequence data exploration. Most of the functions are in test phase, lack systematic consistency check of the arguments and are subject to changes. Once fully checked, some of the functions of this collection could be included in a next release of TraMineR.
Matching terminal restriction fragment length
polymorphism ('TRFLP') profiles between unknown samples and a
database of known samples.  TRAMPR facilitates analysis of
many unknown profiles at once, and provides tools for working
directly with electrophoresis output through to generating
summaries suitable for community analyses with R's rich set of
statistical functions.  TRAMPR also resolves the issues of
multiple 'TRFLP' profiles within a species, and shared 'TRFLP'
profiles across species.
Transcribes audio to text with the HP IDOL API. Includes functions to upload files,
retrieve transcriptions, and monitor jobs.
Estimates the transfer entropy from one time series to another, where each time series consists of continuous random variables. The transfer entropy is an extension of mutual information which takes into account the direction of information flow, under the assumption that the underlying processes can be described by a Markov model. Two estimation methods are provided. The first calculates transfer entropy as the difference of mutual information. Mutual information is estimated using the Kraskov method, which builds on a nearest-neighbor framework (see package references). The second estimation method estimate transfer entropy via the a generalized correlation sum.
Bindings for the Google Translate API v2
translateR provides easy access to the Google and Microsoft APIs. The package is easy to use with the related R package "stm" for the estimation of multilingual topic models.
Package with translated commands of SPSS. The usage is oriented
on the handling of SPSS-Syntax. Mainly the package has two purposes:
It facilitates SPSS-Users to change over to R and aids migration projects from SPSS to R.
R  version 2.1.0 and later support Korean translations of program messages.  The continuous efforts have been made by <http://developer.r-project.org/TranslationTeams.html>   The R Documentation files are licensed under the General Public License, version 2 or 3.   This means that the pilot project to translate them into Korean has permission to reproduce them and translate them.  This work is done with GNU 'gettext' utilities.  The portable object template is updated a weekly basis or whenever changes are necessary.  Comments and corrections via email to the maintainer is of course most welcome.   In order to voluntarily participate in or offer your help with this translation, please contact the maintainer.   To check the change and progress of Korean translation, please visit <http://www.openstatistics.net>.
A unified estimation procedure for the analysis of censored data using linear transformation models.
Implementation of two transportation problem algorithms.
1. North West Corner Method
2. Minimum Cost Method or Least cost method.
For more technical details about the algorithms please refer below URLs.
<http://www.universalteacherpublications.com/univ/ebooks/or/Ch5/nw.htm>.
<http://personal.maths.surrey.ac.uk/st/J.F/chapter7.pdf>.
Solve optimal transport problems in statistics. Compute Wasserstein metrics (a.k.a. Kantorovitch, Fortet--Mourier, Mallows, Earth Mover's, or minimal L_p metrics), return the corresponding transference plans, and display them graphically. Objects that can be compared include grey-scale images, point patterns, and mass vectors.
A structural transformation model for a latent, quasi-independent
truncation time as a function of the observed dependent truncation
time and the event time, and an unknown dependence parameter.
The dependence parameter is chosen to minimize the conditional
Kendall's tau. The marginal distribution for the
truncation time and the event time are completely left unspecified.
The trapezoid package provides dtrapezoid, ptrapezoid,
qtrapezoid, and rtrapezoid functions for the trapezoidal
distribution.
Transmission Ratio Distortion (TRD) is a genetic phenomenon where the two alleles from either parent are not transmitted to the offspring at the expected 1:1 ratio under Mendelian inheritance, leading to spurious signals in genetic association studies. Functions in this package are developed to account for this phenomenon using loglinear model and Transmission Disequilibrium Test (TDT). Some population information can also be calculated.
Evaluate the performance of markers used to guide treatment selection decisions. Package includes functions to plot risk curves, evaluate marker performance, assess model calibration, and compare markers.
Utilities to investigate sensitivity to unmeasured confounding in parametric models with either binary or continuous treatment.
Interface to the API for 'TreeBASE' (http://treebase.org)
from 'R.' 'TreeBASE' is a repository of user-submitted phylogenetic
trees (of species, population, or genes) and the data used to create
them.
Bootstrapped response and correlation functions,
seasonal correlations and evaluation of reconstruction
skills for use in dendroclimatology and dendroecology.
Create a measure of inter-point dissimilarity useful
for clustering mixed data, and, optionally, perform the clustering.
The centre of mass is a crucial data for arborists in order to
consolidate a tree using steel or dynamic cables. Given field-recorded data
on branchiness of a tree, the package: (i) computes and plots the centre of
mass of the tree itself, (ii) computes branches slenderness coefficient in
order to aid the arborist identify potentially dangerous branches, and
(iii) computes the force acting on a ground plinth and its best position
relating to the tree centre of mass, should the tree need to be stabilized
by a steel cable.
Hidden Factor graph models generalise Hidden Markov Models to tree structured data. The distinctive feature of 'treeHFM' is that it learns a transition matrix for first order (sequential) and for second order (splitting) events. It can be applied to all discrete and continuous data that is structured as a binary tree. In the case of continuous observations, 'treeHFM' has Gaussian distributions as emissions.
Treelets provides a novel construction of multi-scale bases that extends
wavelets to non-smooth signals. It returns a multi-scale orthonormal
basis, where the final computed basis functions are supported
on nested clusters in a hierarchical tree.  Both the tree and
the basis, which are constructed simultaneously, reflect the
internal structure of the data.
S4 class and methods for efficient phylogenetic tree manipulation
for simulating evolution, running phylogenetic statistics and plotting.
A treemap is a space-filling visualization of hierarchical
structures. This package offers great flexibility to draw treemaps.
(i) For a given species phylogeny on present day data which is calibrated to calendar-time, a method for estimating maximum likelihood speciation and extinction processes is provided. The method allows for non-constant rates. Rates may change (1) as a function of time, i.e. rate shifts at specified times or mass extinction events (likelihood implemented as LikShifts, optimization as bd.shifts.optim and visualized as bd.shifts.plot) or (2) as a function of the number of species, i.e. density-dependence (likelihood implemented as LikDD and optimization as bd.densdep.optim) or (3) extinction rate may be a function of species age (likelihood implemented as LikAge and optimization as bd.age.optim.matlab). Note that the methods take into account the whole phylogeny, in particular it accounts for the "pull of the present" effect. (1-3) can take into account incomplete species sampling, as long as each species has the same probability of being sampled. For a given phylogeny on higher taxa (i.e. all but one species per taxa are missing), where the number of species is known within each higher taxa, speciation and extinction rates can be estimated under model (1) (implemented within LikShifts and bd.shifts.optim with groups !=0). (ii) For a given phylogeny with sequentially sampled tips, e.g. a virus phylogeny, rates can be estimated under a model where rates vary across time using bdsky.stt.optim based on likelihood LikShiftsSTT (extending LikShifts and bd.shifts.optim). Furthermore, rates may vary as a function of host types using LikTypesSTT (multitype branching process extending functions in R package diversitree). This function can furthermore calculate the likelihood under an epidemiological model where infected individuals are first exposed and then infectious.
An implementation of permutation tests in R, supporting both exact and asymptotic K sample test of data locations. The p value of exact tests is found using tree algorithms. Tree algorithms treat permutations of input data as tree nodes and perform constraint depth-first searches for permutations that fall into the critical region of a test systematically. Pruning of tree search and optimisations at C level enable exact tests for certain large data sets.
Matches phylogenetic trees and trait data, and
allows simultaneous manipulation of the tree and data using 'dplyr'.
Tools for the exploration of distributions of phylogenetic trees.
This package includes a shiny interface which can be started from R using
'treescapeServer()'.
Simulation methods for phylogenetic trees where (i) all tips are sampled at one time point or (ii) tips are sampled sequentially through time. (i) For sampling at one time point, simulations are performed under a constant rate birth-death process, conditioned on having a fixed number of final tips (sim.bd.taxa()), or a fixed age (sim.bd.age()), or a fixed age and number of tips (sim.bd.taxa.age()). When conditioning on the number of final tips, the method allows for shifts in rates and mass extinction events during the birth-death process (sim.rateshift.taxa()). The function sim.bd.age() (and sim.rateshift.taxa() without extinction) allow the speciation rate to change in a density-dependent way. The LTT plots of the simulations can be displayed using LTT.plot(), LTT.plot.gen() and LTT.average.root(). TreeSim further samples trees with n final tips from a set of trees generated by the common sampling algorithm stopping when a fixed number m>>n of tips is first reached (sim.gsa.taxa()). This latter method is appropriate for m-tip trees generated under a big class of models (details in the sim.gsa.taxa() man page). For incomplete phylogeny, the missing speciation events can be added through simulations (corsim()). (ii) sim.rateshifts.taxa() is generalized to sim.bdsky.stt() for serially sampled trees, where the trees are conditioned on either the number of sampled tips or the age. Furthermore, for a multitype-branching process with sequential sampling, trees on a fixed number of tips can be simulated using sim.bdtypes.stt.taxa(). This function further allows to simulate under epidemiological models with an exposed class. The function sim.genespeciestree() simulates coalescent gene trees within birth-death species trees, and sim.genetree() simulates coalescent gene trees.
The package is a flexible simulation tool for phylogenetic trees under a general model. It is possible to assume any probability distribution for the waiting time until speciation and extinction independently. Thus, TreeSimGM allows to simulate stochastic phylogenetic trees using any probability distribution and parameters for speciation and  extinction. The speciation modes have all binary splits and are: (i) symmetric, where for every speciation event new waiting times until speciation and extinction are drawn for both daughter lineages; and (ii) asymmetric, where a speciation event results in one species with new waiting times, and another that carries the extinction time and age of its ancestor. Those two modes were inspired by allopatric and peripatric speciation respectively.Both models (symmetric and asymmetric) were created and implemented so that different processes (distributions) for speciation and extinction could be independently and explicitly specified. It is also possible to have an implicit extinction process by setting the extinction rate to zero.
An implementation of TreeThresh, a locally adaptive version of EbayesThresh.
An extension of Trellis Display that enables creation,
organization, and interactive viewing of multi-panel displays created
against potentially very large data sets.  The dynamic viewer tiles
panels of a display across the screen in a web browser and allows the
user to interactively page through the panels and sort and filter them
based on "cognostic" metrics computed for each panel.  Panels can be
created using many of R's plotting capabilities, including base R
graphics, 'lattice', 'ggplot2', and many 'htmlwidgets'.  Conditioning is
handled through the 'datadr' package, which enables 'Trelliscope' displays
with potentially millions of panels to be created against terabytes of
data on systems like 'Hadoop'.  While designed to scale, 'Trelliscope'
displays can also be very useful for small data sets.
The analysis of environmental data often requires
the detection of trends and change-points.
This package provides the Mann-Kendall Trend Test,
seasonal Mann-Kendall Test,
correlated seasonal Mann-Kendall Test,
partial Mann-Kendall Trend test,
(Seasonal) Sen's slope, partial correlation trend test and
change-point test after Pettitt.
Estimation of causal odds ratio given trends in exposure prevalence
and outcome frequencies of stratified data.
functions and examples in Sample Size Calculation in
Clinical Research.
Provides the "r, q, p, and d" distribution functions for the triangle distribution.
Tribology test devices such as pin-on-disk, ball-on-disk machines and profilometers give important data for tribological analysis. trib is built to analyze and visualize that data into human understandable form. It has functions for finding coefficient of friction, Friction Force vs Distance graphs and calculating Wear Track Volume and Wear Track plotting.
'Radix trees', or 'tries', are key-value data structures optimised for efficient lookups, similar in purpose
to hash tables. 'triebeard' provides an implementation of 'radix trees' for use in R programming and in
developing packages with 'Rcpp'.
The package contains routines to 1) project unity-summed
triples to unit-square doubles and vice versa, 2) make a grid
of unity-summed triples paired to doubles, 3) evaluate a
function over the grid and 4) make simple plots including
ternary contour plots over a grid of values.
Propensity score matching for non-binary treatments.
Provides various commonly-used response time trimming
methods, including the recursive / moving-criterion methods reported by
Van Selst and Jolicoeur (1994). By passing trimming functions raw data files,
the package will return trimmed data ready for inferential testing.
Creates point and probability forecasts from the trees in a random forest using a trimmed opinion pool.
The package contains functions that 1) estimates
gene-environment interaction between a SNP and a continuous
non-genetic attribute by fitting a generalized additive model
to case-parent trio data, 2) produces graphical displays of
estimated interaction, 3) performs permutation test of
gene-environment interaction; 4) simulates informative
case-parent trios.
Functions for accessing and manipulating spatial data for animal
tracking, with straightforward coercion from and to other formats. Filter
for speed and create time spent maps from animal track data.
A constrained two-dimensional Delaunay triangulation package
providing both triangulation and generation of voronoi mosaics of
irregular spaced data.
Data handling and estimation functions for animal movement
estimation from archival or satellite tags. Helper functions are included
for making image summaries binned by time interval from Markov Chain Monte Carlo
simulations.
Social Relation Model (SRM) analyses for single or multiple
round-robin groups are performed. These analyses are either based on one
manifest variable, one latent construct measured by two manifest variables,
two manifest variables and their bivariate relations, or two latent
constructs each measured by two manifest variables. Within-group t-tests
for variance components and covariances are provided for single groups.
For multiple groups two types of significance tests are provided:
between-groups t-tests (as in SOREMO) and enhanced standard errors based on
Lashley and Bond (1997) <DOI:10.1037/1082-989X.2.3.278>. Handling for missing values is provided.
A new bioinformatic tool for comparing transcriptomes of two biological samples from the same or different species. The mapping is conducted based on the overlap of the associated genes of different samples. More examples and detailed explanations are available in the vignette.
Fish stock assessment methods and fisheries models based on the FAO
Manual "Introduction to tropical fish stock assessment" by P. Sparre and
S.C. Venema <http://www.fao.org/docrep/W5449E/W5449E00.htm>.  Focus is the analysis of length-frequency data and data poor fisheries.
Class definitions and constructors for pseudo-vectors containing
all permutations, combinations and subsets of objects taken from a vector.
Simplifies working with structures commonly encountered in combinatorics.
Functions and datasets for the reader of the book "The R Software: Fundamentals of Programming and Statistical Analysis".
An implementation of the TrueSkill algorithm (Herbrich,
R., Minka, T. and Grapel, T) in R; a Bayesian skill rating
system with inference by approximate message passing on a
factor graph. Used by Xbox to rank gamers and identify
appropriate matches.
http://research.microsoft.com/en-us/projects/trueskill/default.aspx
Current version allows for one player per team. Will update as
time permits.  Requires R version 3.0 as it is written with
Reference Classes.  URL:
https://github.com/bhoung/trueskill-in-r Acknowledgements to
Doug Zongker and Heungsub Lee for their python implementations
of the algorithm and for the liberal reuse of Doug's code
comments (@dougz and @sublee on github).
A collection of functions to deal with the truncated univariate and multivariate normal distributions.
A collection of functions to evalue probability density
functions, cumulative distribution functions, quantile
functions and random numbers for truncated random variables.
Functions are provided to also compute the expected value and
variance. Nadarajah and Kotz (2006) developed most of the
functions. QQ plots can be produced.  All the probability
functions in the stats, stats4 and evd packages are
automatically available for truncation..
Goodness-of-fit tests and some adjusted exploratory tools
allowing for left truncated data
r/d/p/q functions for the truncated normal distribution
Estimation of models for truncated Gaussian variables by maximum likelihood.
Semi-parametric estimation of truncated linear regression models
Does local optimization using two derivatives and trust regions.
Guaranteed to converge to local minimum of objective function.
Trust region algorithm for nonlinear optimization.  Efficient when the Hessian of the objective function is sparse (i.e., relatively few nonzero cross-partial derivatives).
Contains R functions and datasets detailed in the book
"Time Series Analysis with Applications in R (second edition)"
by Jonathan Cryer and Kung-Sik Chan
Tsallis distribution also known as the q-exponential family distribution. Provide distribution d, p, q, r functions, fitting and testing functions. Project initiated by Paul Higbie and based on Cosma Shalizi's code.
The tsbridge package contains a collection of R functions that can be used to estimate normalising constants using the bridge sampler of Meng and Wong (1996). The functions can be applied to calculate posterior model probabilities for a variety of time series Bayesian models, where parameters are estimated using BUGS, and models themselves are created using the tsbugs package.
Different estimates are provided to solve the blind source separation problem for time series with stochastic volatility.
The tsbugs package contains a collection of R functions
that can be used to create time series BUGS models of various
order. Included are function to create BUGS with non-constant
variance such stochastic volatility models and random variance
shift models.
Performs the two-sample comparisons using the following exact test procedures: the exact likelihood-ratio test (LRT) for equality of two normal populations proposed in Zhang et al. (2012); the combined test based on the LRT and Shapiro-Wilk test for normality via the Bonferroni correction technique; the newly proposed density-based empirical likelihood (DBEL) ratio test. To calculate p-values of the DBEL procedures, three procedures are used: (a) the traditional Monte Carlo (MC) method implemented in C++, (b) a new interpolation method based on regression techniques to operate with tabulated critical values of the test statistic; (c) a Bayesian type method that uses the tabulated critical values as the prior information and  MC generated DBEL-test-statistic's values as data.
This package contains a set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.
Utilities for comparing the equality of series on two databases.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
Likelihood-based methods for model fitting and assessment, prediction and intervention analysis of count time series following generalized linear models are provided. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.
Illustrates the various 'TSdbi' packages with a vignette using time series
data from several sources. The vignette also illustrates some simple time series
manipulation and plotting using packages 'tframe' and 'tfplot'.
Provides a common interface to time series databases. The
objective is to define a standard interface so users can retrieve time
series data from various sources with a simple, common, set of
commands, and so programs can be written to be portable with respect
to the data source. The SQL implementations also provide a database
table design, so users needing to set up a time series database
have a reasonably complete way to do this easily. The interface
provides for a variety of options with respect to the representation
of time series in R. The interface, and the SQL implementations, also
handle vintages of time series data (sometime called editions or
realtime data). There is also a (not yet well tested) mechanism to
handle multilingual data documentation.
Comprehensive examples of all the TS* packages is provided in the
vignette Guide.pdf with the TSdata package.
A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series.
Implements nonlinear autoregressive (AR) time series models. For univariate series, a non-parametric approach is available through additive nonlinear AR. Parametric modeling and testing for regime switching dynamics is available when the transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR). For multivariate series, one can estimate a range of TVAR or threshold cointegration TVECM models with two or three regimes. Tests can be conducted for TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006).
Time series analysis and computational finance.
Routines for the analysis of nonlinear time series. This
work is largely inspired by the TISEAN project, by Rainer
Hegger, Holger Kantz and Thomas Schreiber:
http://www.mpipks-dresden.mpg.de/~tisean/
Implements an Entropy measure of dependence based on the Bhattacharya-Hellinger-Matusita distance. Can be used as a (nonlinear) autocorrelation/crosscorrelation function for continuous and categorical time series. The package includes tests for serial dependence and nonlinearity based on it. Some routines have a parallel version that can be used in a multicore/cluster environment. The package makes use of S4 classes.
Extraction of Factors from Multivariate Time Series. See ?00tsfa-Intro for more details.
A 'fame' interface for 'TSdbi'.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
two-stage procedure for comparing hazard rate functions
which may or may not cross each other
Functions for analysing and forecasting intermittent demand/slow moving items time series.
Implementations of a number of functions used to mine numeric time-series data. It covers the implementation of SAX transformation, univariate motif discovery (based on the random projection method), multivariate motif discovery (based on graph clustering), and several functions used for the ease of visualizing the motifs discovered. The details of SAX transformation can be found in J. Lin. E. Keogh, L. Wei, S. Lonardi, Experiencing SAX: A novel symbolic representation of time series, Data Mining and Knowledge Discovery 15 (2) (2007) 107-144. Details on univariate motif discovery method implemented can be found in B. Chiu, E. Keogh, S. Lonardi, Probabilistic discovery of time series motifs, ACM SIGKDD, Washington, DC, USA, 2003, pp. 493-498. Details on the multivariate motif discovery method implemented can be found in A. Vahdatpour, N. Amini, M. Sarrafzadeh, Towards unsupervised activity discovery using multi-dimensional motif detection in time series, IJCAI 2009 21st International Joint Conference on Artificial Intelligence.
Methods to
retrieve data from several different sources. This include historical
quote data from Yahoo and Oanda, economic data from FRED, and xls and
csv data from different sources.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
Tools for specifying time series regression models
A 'MySQL' interface for 'TSdbi'.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
Temporal SNA tools for continuous- and discrete-time longitudinal networks having vertex, edge, and attribute dynamics stored in the 'networkDynamic' format. This work was supported by grant R01HD68395 from the National Institute of Health.
A "pure R" implementation of the t-SNE algorithm.
An ODBC interface for 'TSdbi'.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
Detection of outliers in time series following the
Chen and Liu (1993) procedure. Innovational outliers, additive outliers,
level shifts, temporary changes and seasonal level shifts are considered.
Basic infrastructure and some algorithms for the traveling
salesperson problem (also traveling salesman problem; TSP).
The package provides some simple algorithms and
an interface to the Concorde TSP solver and its implementation of the
Chained-Lin-Kernighan heuristic. Concorde
itself is not included in the package and has to be obtained separately
from http://www.math.uwaterloo.ca/tsp/concorde.html.
Adjusts for correlations among the rows and columns via
the Transposable Sphering Algorithm when conducting large-scale
inference on the rows of a data matrix.
Prediction intervals for ARIMA and structural time series
models using importance sampling approach with uninformative priors for model
parameters, leading to more accurate coverage probabilities in frequentist
sense. Instead of sampling the future observations and hidden states of the
state space representation of the model, only model parameters are sampled,
and the method is based solving the equations corresponding to the conditional
coverage probability of the prediction intervals. This makes method relatively
fast compared to for example MCMC methods, and standard errors of prediction
limits can also be computed straightforwardly.
Instance feature calculation and evolutionary instance generation
for the traveling salesman problem. Also contains code to "morph" two TSP
instances into each other. And the possibility to conveniently run a couple
of solvers on TSP instances.
A 'PostgreSQL' interface for 'TSdbi'.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
Functions for time series prediction and accuracy assessment using automatic ARIMA modelling. The generated ARIMA models and its yielded prediction errors are intended to be used as baseline for evaluating the practical value of other time series prediction methods and creating a demand for the refinement of such methods. For this purpose, benchmark data from prediction competitions may be used.
Methods to
retrieve data in the Statistical Data and Metadata Exchange ('SDMX') format
from several database. (For example,
EuroStat, the European Central Bank, the Organisation for Economic
Co-operation and Development, the Unesco Institute for Statistics,
and the International Labor Organization.)
This is a wrapper for package 'RJSDMX'.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
Standard SQL query functions used by
SQL plugins packages for the 'TSdbi' interface to time series databases.
It will mainly be used by other packages rather than directly by end
users. The one exception is the function 'TSquery' which can be used to
construct a time series from a database containing observations over
time (e.g. balance statements for multiple years), but where the database
is not specifically designed to store time series (as with other
'TSdbi' SQL plugin packages).
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
An 'SQLite' interface for 'TSdbi'.
Comprehensive examples of all the 'TS*' packages is provided in the
vignette Guide.pdf with the 'TSdata' package.
A ternary search tree is a type of prefix tree with up to three children and the ability for incremental string search. The package uses this ability for word auto-completion and spell checking. Includes a dataset with the 10001 most frequent English words.
Interactive laboratory of Time Series based in Box-Jenkins methodology.
This interface was created to develop a standard procedure
to analyse temporal trend in the framework of the OSPAR convention.
The analysis process run through 4 successive steps : 1) manipulate your data, 2)
select the parameters you want to analyse, 3) build your regulated
time series, 4) perform diagnosis and analysis and 5) read the results.
Statistical analysis call other package function such as Kendall tests
or cusum() function.
U.S. Department of the Treasury, Alcohol and Tobacco Tax and
Trade Bureau (TTB) collects data and reports on monthly beer
industry production and operations. This data package includes
a collection of 10 years (2006 - 2015) worth of data on materials
used at U.S. breweries in pounds reported by the Brewer's Report
of Operations and the Quarterly Brewer's Report of Operations
forms, ready for data analysis. This package also includes historical
tax rates on distilled spirits, wine, beer, champagne, and tobacco
products as individual data sets.
The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response
following stimulation. A common observation in this type of data is that some genes respond with quick,
transient dynamics, while other genes change their expression slowly over time. The existing methods for the
detection of significant expression dynamics often fail when the expression dynamics show a large
heterogeneity, and often cannot cope with irregular and sparse measurements. The method proposed here is
specifically designed for the analysis of perturbation responses. It combines different scores to capture fast and
transient dynamics as well as slow expression changes, and deals with low replicate numbers and irregular
sampling times. The results are given in the form of tables linked to figures. These allow to quickly recognize
the relevance of detection, to identify possible false positives and to distinguish between changes in the early
and later expression. An extension of the method allows the analysis of the expression dynamics of functional
groups of genes, providing a quick overview of the cellular response. The performance of this package was
tested on microarray data derived from lung cancer cells stimulated with epidermal growth factor.
See publication "TTCA: An R package for the identification of differentially expressed genes in time course microarray data".
C source code and R wrappers for the tth/ttm TeX to
HTML/MathML translators.
Computing the first two moments of the truncated multivariate t (TMVT) distribution under the double truncation. Appling the slice sampling algorithm to generate random variates from the TMVT distribution.
Functions and data to construct technical trading rules with R.
Time-Temperature Superposition analysis is often applied to frequency modulated data obtained by Dynamic
Mechanic Analysis (DMA) and Rheometry in the analytical chemistry and physics
areas. These techniques provide estimates of material mechanical properties
(such as moduli) at different temperatures in a wider range of time. This
package provides the Time-Temperature superposition Master Curve at a referred
temperature by the three methods: the two wider used methods, Arrhenius based
methods and WLF, and the newer methodology based on derivatives procedure.
The Master Curve is smoothed by B-splines basis. The package output is composed
of plots of experimental data, horizontal and vertical shifts, TTS data, and TTS
data fitted using B-splines with bootstrap confidence intervals.
This package utilizes training and testing samples to filter out uninformative DNA methylation sites. Surrogate variables (SVs) of DNA methylation are included in the filtering process to explain unknown factor effects.
Implementation of Time to Target plot based on the work
of Ribeiro and Rosseti (2015) <DOI:10.1007/s11590-014-0760-8>,
that describe a numerical method that gives the probability of
an algorithm A finds a solution at least as good as a given
target value in smaller computation time than algorithm B.
This package makes Travel To Work Area from a commuting flow data frame.
Get comments posted on YouTube videos, information on how many
times a video has been liked, search for videos with particular content, and
much more. You can also scrape captions from a few videos. To learn more about
the YouTube API, see <https://developers.google.com/youtube/v3/>.
Provides R Markdown output formats to use Tufte styles for PDF and HTML output.
Custom template and output formats for use with rmarkdown. Produce
Edward Tufte-style handouts in html formats with full support for rmarkdown
features
Perform the conventional Tukey test from aov and aovlist
objects
Provides an R-interface to the Tumblr web API (see Tumblr v2 API on https://www.tumblr.com/docs/en/api/v2). Tumblr is a microblogging platform and social networking website (https://www.tumblr.com).
A tool to obtain tumor growth rates from clinical trial patient data.  Output includes individual and summary data for tumor growth rate estimates as well as optional plots of the observed and predicted tumor quantity over time.
Generic methods for parameter tuning of classification algorithms using multiple scoring functions
Collection of tools to analyze music, extract features
like MFCCs, handling wave files, read mp3, transcription, ...
Also contains functions ported from the rastamat Matlab
package.
Functions to find all matches or non-matches, orphans, and
duplicate or other replicated elements.
Algorithms for accelerating the convergence of slow,
monotone sequences from smooth, contraction mapping such as the
EM and MM algorithms. It can be used to accelerate any smooth,
linearly convergent acceleration scheme.  A tutorial style
introduction to this package is available in a vignette on the
CRAN download page or, when the package is loaded in an R
session, with vignette("turboEM").
Package for analyzing TURF (Total Unduplicated Reach and Frequency) data in R.
No looping in TURF algorithm results in fast processing times. Allows for individual-level
weights, depth specification, and user-truncated combination set(s). Allows user to substitute
Monte Carlo simulated combination set(s) after set(s) exceed a user-specified limit.
Package designed for working with vectors and lists of vectors,
mainly for turning them into other indexed data structures.
An implementation of turtle graphics
(http://en.wikipedia.org/wiki/Turtle_graphics) in R.
Turtle graphics comes from Papert's language Logo and has
been used to teach concepts of computer programming.
DataCamp Light (<https://github.com/datacamp/datacamp-light>) is a light-weight implementation of the DataCamp UI,
that allows you to embed interactive exercises inside HTML documents. The tutorial package makes it easy to create these
HTML files from R Markdown files. An extension to knitr, tutorial detects appropriately formatted code chunks and replaces them
with DataCamp Light readable chunks in the resulting HTML file.
The model, developed at the Vienna University of Technology, is a lumped conceptual rainfall-runoff model, following the structure of the HBV model.
The model runs on a daily or shorter time step and consists of a snow routine, a soil moisture routine and a flow routing routine.
See Parajka, J., R. Merz, G. Bloeschl (2007) Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments, Hydrological Processes, 21, 435-446.
Total Variation Denoising is a regularized denoising method which
effectively removes noise from piecewise constant signals whilst preserving
edges.  This package contains a C++ implementation of Condat's very fast 1D
squared error loss TVD algorithm.  Additional methods and loss functions may
be added in future versions.
Functions for managing cashflows and interest rate curves.
Provides functions for propensity score
estimating and weighting, nonresponse weighting, and diagnosis
of the weights.  This package was originally developed by Drs.
Ridgeway, McCaffrey, and Morral. Burgette, Griffin and
McCaffrey updated the package during 2011-2016.
Maximum likelihood computations for Tweedie families.
In order to create smooth animation between states of data,
tweening is necessary. This package provides a range of functions for
creating tweened data that plugs right into functions such as gg_animate()
from the 'gganimate' package. Furthermore it adds a number of vectorized
interpolaters for common R data types such as numeric, date and colour.
This is an improved implementation of the package 'StreamR' to
capture tweets and store it into R, SQLite, 'postGIS' data base or GIS format. The package
performs a description of harvested data and performs space time exploratory analysis.
Twiddler is an interactive tool that automatically creates
a Tcl/Tk GUI for manipulating variables in any R expression.
See the documentation of the function twiddle to get started.
Provides an interface to the Twitter web API.
This package implements the nonparametric test of equality
between two copulas proposed by Remillard and Scaillet in their
2009 JMVA paper.
Estimation of gene-treatment interactions in randomized clinical trials exploiting gene-treatment independence.
This program computes thresholds and power for a two-stage
genome-wide association study. It follows the methods described
in Skol AD, Scott, LJ, Abecasis GR, Boehnke M (2006) Nature
Genetics doi:10.1038/ng1706 and in the "CaTS" computer program
(http://www.sph.umich.edu/csg/abecasis/CaTS/)
Implements a variety of non-parametric methods for computing one-stage and two-stage confidence intervals, as well as point estimates of threshold values.
Conditional logistic regression with longitudinal follow up and
individual-level random coefficients: A stable and efficient
two-step estimation method.
Provides functions to produce rudimentary ascii graphics
directly in the terminal window. Provides a basic plotting
function (and equivalents of curve, density, acf and barplot)
as well as a boxplot function.
Despite there being a section in RFC 7231
<https://tools.ietf.org/html/rfc7231#section-5.5.3> defining a suggested
structure for 'User-Agent' headers this data is notoriously difficult
to parse consistently. A function is provided that will take in user agent
strings and return structured R objects. This is a 'V8'-backed package
based on the 'ua-parser' project <https://github.com/ua-parser>.
Two Phase I designs are implemented in the package: the classical 3+3 and the Continual Reassessment Method. Simulations tools are also available to estimate the operating characteristics of the methods with several user-dependent options.
Provides a set of functions that can be used to obtain better predictive performance on cost-sensitive and cost/benefits tasks (for both regression and classification). This includes re-sampling approaches that modify the original data set biasing it towards the user preferences.
This package contains latex, knitr and R Markdown templates that
adhere to the UC Berkeley Graduate Division's thesis guidelines. The
templates are located in the inst/ directory.
An algorithm for general-purpose unconstrained non-linear optimization.
The algorithm is of quasi-Newton type with BFGS updating of the inverse
Hessian and soft line search with a trust region type monitoring of the
input to the line search algorithm. The interface of 'ucminf' is
designed for easy interchange with 'optim'.
A client for the Urban Dictionary <http://www.urbandictionary.com/> API.
Provides simple bindings to Unidata's udunits library.
Construct a Hidden Markov Model with states learnt by unsupervised classification.
Allows users to access live UK gas market information via National Grid's API.
A generic reference Bayesian analysis of unidimensional mixtures of Gaussian distributions obtained by a location-scale parameterisation of the model is implemented. Included functions can be applied to produce a Bayesian analysis of Gaussian mixtures with an arbitrary number of components, with no need to define the prior distribution.
Does uniformly most powerful (UMP) and uniformly most
powerful unbiased (UMPU) tests.  At present only distribution implemented
is binomial distribution.  Also does fuzzy tests and confidence intervals
(following Geyer and Meeden, Statistical Science, 2005) for the binomial
distribution (one-tailed procedures based on UMP test and two-tailed
procedures based on UMPU test).
Create, run, and report structural equation and twin models quickly.
If you're just starting out, try typing '?umx'.
A dataset is said to be unbalanced when the class of interest (minority class) is much rarer than normal behaviour (majority class). The cost of missing a minority class is typically much higher that missing a majority class. Most learning systems are not prepared to cope with unbalanced data and several techniques have been proposed. This package implements some of most well-known techniques and propose a racing algorithm to select adaptively the most appropriate strategy for a given unbalanced task.
The package implements top-down and bottom-up algorithms
for nonparametric function estimation in Gaussian noise using
Unbalanced Haar wavelets.
Provides a basic (random) data, grids, 6 models of uncertainty, 3 automatic interpolations (idw, spline, kriging), variogram and basic data visualization.
Consensus clustering by the unification of clustering results from multiple datasets using external specifications.
Computes a universal numeric fingerprint (UNF) for an R data
object. UNF is a cryptographic hash or signature that can be used to uniquely
identify (a version of) a rectangular dataset, or a subset thereof. UNF can
be used, in tandem with a DOI, to form a persistent citation to a versioned
dataset.
Stereological unfolding as implemented in this package consists in
the estimation of the joint size-shape-orientation distribution of spheroidal
shaped particles based on the same measured quantities of corresponding planar
section profiles. A single trivariate discretized version of the (stereological)
integral equation in the case of prolate and oblate spheroids is solved
numerically by the EM algorithm. The estimation of diameter distribution of
spheres from planar sections (Wicksell's corpuscle problem) is also implemented.
Further, the package provides routines for the simulation of a Poisson germ-
grain process with either spheroids, spherocylinders or spheres as grains together
with functions for planar sections. For the purpose of exact simulation a bivariate size-shape
distribution is implemented.
Taking a list of genes, the package collates together the summary
information about those genes from the publicly available resources at Uniprot
and NCBI. Additionally, the package is able to collate publication information
from a search of the NCBI Pubmed database.
Nonparametric estimation of a unimodal or U-shape covariate effect under additive hazards model.
Data from Unicode 8.0.0 and related utilities.
Univarate shrinkage prediction for survival analysis using
in the Cox model.. Especially useful for high-dimensional data,
including microarray data.
Goodness-of-fit tests for the uniform distribution.
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.
An alternative implementation and extension (grpDuplicated) of base::duplicated.matrix, base:anyDuplicated.matrix and base::unique.matrix for matrices of atomic mode, avoiding the time consuming collapse of the matrix into a character vector.
Univariate spline regression. It is possible to add the shape constraint of unimodality and predefined or
self-defined penalties on the B-spline coefficients.
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.
Support for measurement units of physical quantities in R vectors, based on the udunits library from unidata.
Concise TAP (http://testanything.org/) compliant unit testing package. Authored tests can be run using CMD check with minimal implementation overhead.
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.
A collection of utilities for biodiversity data.
Includes the simulation of ecological drift under Hubbell's Unified
Neutral Theory of Biodiversity, and the calculation of various
diagnostics such as Preston curves.  Now includes functionality
provided by Francois Munoz and Andrea Manica.
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 package contains a collection of functions which
implement data classification. It uses unlabeled data to obtain
parameter estimates of models. The functions can be implemented
over a number of models with the best model selected and
displayed.
An integrated package for building and testing uplift models
An implementation of the UPMASK method for performing membership
assignment in stellar clusters in R. It is prepared to use photometry and
spatial positions, but it can take into account other types of data. The
method is able to take into account arbitrary error models, and it is
unsupervised, data-driven, physical-model-free and relies on as few
assumptions as possible. The approach followed for membership assessment is
based on an iterative process, principal component analysis, a clustering
algorithm and a kernel density estimation.
Creates visualizations of intersecting sets using a novel matrix
design, along with visualizations of several common set, element and attribute
related tasks.
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.
Unit root and cointegration tests encountered in applied
econometric analysis are implemented.
Allows using different URL shortening services, which also provide
expanding and analytic functions. Specifically developed for 'Bit.ly', 'Goo.gl'
(both OAuth2) and 'is.gd' (no API key). Others can be added by request.
A toolkit for handling URLs that so far includes functions for URL
encoding and decoding, parsing, and parameter extraction. 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.
A parallel implementation of the bootstrap method requires a CUDA capable GPU
with compute capability >= 3.0, otherwise a debugging version fully coded in R is used.
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 high
resolution data is provided in the 'USAboundariesData' package;
this package provides an interface to access that data.
This package contains functions to read cancer data from SEER (http://seer.cancer.gov/) and IARC (http://www.iarc.fr) to create datasets at the county level based on US census information.
US Census 2000 Designated Places shapefiles and additional
demographic data from the SF1 100 percent files. This data set
contains polygon files in lat/lon coordinates and the
corresponding demographic data for a number of different
variables.
US 2000 Census Tract shapefiles and additional demographic
data from the SF1 100 percent files. This data set contains
polygon files in lat/lon coordinates and the corresponding
demographic data for a number of different variables.
US Census 2010 shape files and additional demographic data
from the SF1 100 percent files. This package contains a number
of helper functions for the UScensus2010blk,
UScensus2010blkgrp, UScensus2010tract, UScensus2010cdp
packages.
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).)
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.
Contains a number of functions that serve
two goals: first, make R more accessible to people migrating from
SPSS by adding a number of functions that behave roughly like their
SPSS equivalents; and second, make a number of slightly more
advanced functions more user friendly to relatively novice users.
A map of the USA from the United States Geological Survey (USGS).
Irucka worked with this data set while a Cherokee Nation Technology
Solutions (CNTS) USGS Contractor and/or USGS employee. It is replaced by
'states2k'.
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 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.
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.
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.
Multi-label learning methods and others utilities to support multi-
label classification in R.
Tools for generating and handling of UUIDs (Universally Unique Identifiers).
A method for estimating log-normalizing constants (or free
energies) and expectations from multiple distributions (such as
multiple generalized ensembles).
An R interface to Google's open source JavaScript engine.
V8 is written in C++ and implements ECMAScript as specified in ECMA-262,
5th edition. In addition, this package implements typed arrays as
specified in ECMA 6 used for high-performance computing and libraries
compiled with 'emscripten'.
A likelihood framework for estimating the effective
coverage of vaccination programs using cross-sectional surveys
combined with administrative data.
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 01/01/2016 - 06/14/2016. 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 (2016 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)'. "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>.
Methods and tools for analysing and validating the outputs
and modelled functions of artificial neural networks (ANNs) in terms
of predictive, replicative and structural validity. Also provides a
method for fitting feed-forward ANNs with a single hidden layer.
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.
An implementation of statistical tests for the validation of rating systems as described in the ECB Working paper ''Advances in multivariate back-testing for credit risk underestimation'', by F. Coppens, M. Mayer, L. Millischer, F.  Resch, S. Sauer, K. Schulze (ECB WP series, forthcoming).
Historical results for the state of Virginia lottery draw games. Data were downloaded from https://www.valottery.com/.
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.
Variance component models: REML estimation, testing fixed effect contrasts through Satterthwaite or Kenward-Roger methods, testing the nullity of variance components through (linear or quadratic) score tests or likelihood ratio tests.
Generation of domain variables, linearisation of several nonlinear 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, 1953), variance estimation for longitudinal, cross-sectional measures and measures of change for single and multistage stage cluster sampling designs (Berger, Y.G.). Several other precision measures are derived - standard error, the coefficient of variation, the margin of error, confidence interval, design effect.
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.
Estimation, Hypothesis Testing, Prediction for Stationary Vector Autoregressive Models
Captures and compiles the genes and variants related to a disease, a phenotype or a clinical feature based on the public databases including HPO (Human Phenotype Ontology, <http://human-phenotype-ontology.github.io/about.html>), Orphanet <http://www.orpha.net/consor/cgi-bin/index.php>, OMIM (Online Mendelian Inheritance in Man, <http://www.omim.org>), ClinVar <http://www.ncbi.nlm.nih.gov/clinvar>, and UniProt (Universal Protein Resource, <http://www.uniprot.org>) and PubMed abstracts. HPO provides a standardized vocabulary of phenotypic abnormalities encountered in human disease. HPO currently contains approximately 11,000 terms and over 115,000 annotations to hereditary diseases. Orphanet is the reference portal for information on rare diseases and orphan drugs, whose aim is to help improve the diagnosis, care and treatment of patients with rare diseases. OMIM is a continuously updated catalog of human genes and genetic disorders and traits, with particular focus on the molecular relationship between genetic variation and phenotypic expression. ClinVar is a freely accessible, public archive of reports of the relationships among human variations and phenotypes, with supporting evidence. UniProt focuses on amino acid altering variants imported from Ensembl Variation databases. For Homo sapiens, the variants including human polymorphisms and disease mutations in the UniProt are manually curated  from UniProtKB/Swiss-Prot. Additionally, PubMed provides the primary and latest source of the information. Text mining was employed to capture the information from PubMed abstracts.
Variables are the fundamental parts of each programming language but handling them might be frustrating for programmers from time to time. 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 as well as their hardware. These functions are written, collected and crafted over some years of experience in statistical data analysis and for each of them there was a need. Functions in this package are suppose to be efficient and easy to use, hence they will be frequently updated to make them more convenient.
Presence of interaction between a SNP and another SNP (or another factor) can result
in heterogeneity of variance between the genotypes of an interacting SNP.
Detecting such heterogeneity gives prior knowledge for constructing a genetic model
underlying complex trait.
Abstract descriptions of (yet) unobserved variables.
Implements a screening procedure proposed by Wanghuan Chu, Runze Li
and Matthew Reimherr (2016) <DOI:10.1214/16-AOAS912> for varying coefficient
longitudinal models with ultra-high dimensional predictors . The effect of each
predictor is allowed to vary over time, approximated by a low-dimensional B-spline.
Within-subject correlation is handled using a generalized estimation equation
approach with structure specified by the user. Variance is allowed to change
over time, also approximated by a B-spline.
Uses a Bayesian model to
estimate the variability in a repeated
measure outcome and use that as an outcome or a predictor
in a second stage model.
This package provides functions for the variance gamma
distributions. 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
parameterizatons for the variance gamma distribution.
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.
An algorithm which identifies the morphometric features that significantly discriminate two taxa and validates the morphological distinctness between them via a Monte-Carlo test, polar coordinates and overlap of the area under the density curve.
Uses a finite mixture model for performing the cluster analysis with variable selection of continuous data by assuming independence between classes. The package deals dataset with missing values by assuming that values are missing at random. The one-dimensional marginals of the components follow Gaussian distributions for facilitating both model interpretation and model selection. The variable selection is led by the Maximum Integrated Complete-Data Likelihood criterion. The maximum likelihood inference is done by an EM algorithm for the selected model. This package also performs the imputation of  missing values.
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).
Provides routines for identifying structural shocks in vector autoregressions (VARs) using sign restrictions.
Computes a portfolio of European options that replicates
the cost of capturing the realised variance of an equity index.
Efficient algorithm for solving discrete mixture
regression model for rare variant association analysis.
Uses variational Bayes algorithm to efficiently search over
model space.  Outputs an approximate likelihood ratio test
as well as variant level posterior probabilities of
association.
Fit and simulate latent position and cluster
models for network data, using a fast Variational Bayes approximation.
Variational algorithms and methods for fitting mixture
models. Main functions are varbayes, vbcomp, vbconstr, mppca,
mmppca and gmmkmsock.
Efficient algorithm for solving ultra-sparse
regularized regression models using a variational
Bayes algorithm with a spike (l0) prior.  Algorithm
is solved on a path, with coordinate updates, and is
capable of generating very sparse models.  There are
very general model diagnostics for controling type-1
error included in this package.
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.
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 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.
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.
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.
Multicategory Vertex Discriminant Analysis: A novel supervised multicategory classification method
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.
Facilities for constructing variance dispersion graphs, fraction-
of-design-space plots and similar graphics for exploring the properties of
experimental designs. The design region is explored via random sampling, which
allows for more flexibility than traditional variance dispersion graphs. A
formula interface is leveraged to provide access to complex model formulae.
Graphics can be constructed simultaneously for multiple experimental designs
and/or multiple model formulae. Instead of using pointwise optimization to
find the minimum and maximum scaled prediction variance curves, which can be
inaccurate and time consuming, this package uses quantile regression as an
alternative.
Uses a modification of the published FORTRAN code in "A Computer Program for Generating Variance Dispersion Graphs" by G. Vining, Journal of Quality Technology, Vol. 25 No. 1 January 1993, to produce variance dispersion graphs. Also produces fraction of design space plots, and contains data frames for several minimal run response surface designs.
Functions for creating variance dispersion graphs, fraction of design space plots, and contour plots of scaled prediction variances for second-order response surface designs in spherical and cuboidal regions. Also, some standard response surface designs can be generated.
This provides web-based visual data-mining tools by adding
interactive functions to 'ggplot2' graphics. Brushing and linking between the
multiple plots is one of the main feature of this package. Currently scatter
plots, histograms, parallel coordinate plots and choropleth maps are supported.
A package for applying 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.
The base 'sets' tools 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::set tools functionality.
A 2D statistical analysis is performed, both numerical and graphical, of a set of vectors. Since a vector has two components (module and azimuth) vector analysis is performed in three stages: modules are analyzed by means of linear statistics, azimuths are analyzed by circular statistics, and the joint analysis of modules and azimuths is done using density maps that allow detecting another distribution properties (i.e. anisotropy) and outliers. Tests and circular statistic parameters have associated a full range of graphing: histograms, maps of distributions, point maps, vector maps, density maps, distribution modules and azimuths.
This package performs a 3D statistical analysis, both numerical and graphical, of a set of vectors. Since a vector has three components (a module and two angles) vectorial analysis is performed in two stages: modules are analyzed by means of linear statistics and orientations are analyzed by spherical statistics. Tests and spherical statistic parameters are accompanied by a graphs as: density maps, distribution modules and angles. The tests, spherical statistic parameters and graphs allow us detecting another distribution properties (i.e. anisotropy) and outliers.
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.
Contains functions used to perform fuzzy clustering of vegetation data under different models. It also includes functions to measure community dissimilarity on the basis of structure and composition.
Handling of vegetation data from Turboveg (<http://www.synbiosys.alterra.nl/turboveg/>) and other sources (<http://www.vegetweb.de>). Taxonomic harmonization given appropriate taxonomic lists (e.g. the German taxonomical standard list "GermanSL", <http://www.botanik.uni-greifswald.de/GermanSL.html>).
This package computes diversity for community data sets
using the methods outlined by Jost (2006, 2007). While there
are differing opinions on the ideal way to calculate diversity
(e.g. Magurran 2004), this method offers the advantage of
providing diversity numbers equivalents, independent alpha and
beta diversities, and the ability to incorporate 'order' (q) as
a continuous measure of the importance of rare species in the
metrics. The functions provided in this package largely
correspond with the equations offered by Jost in the cited
papers. The package computes alpha diversities, beta
diversities, gamma diversities, and similarity indices.
Confidence intervals for diversity measures are calculated
using a bootstrap method described by Chao et al. (2008).  For
datasets with many samples (sites, plots), sim.table creates
tables of all pairwise comparisons possible, and for grouped
samples sim.groups calculates pairwise combinations of within-
and between-group comparisons.
A set of functions for generating HTML to
embed hosted video in your R Markdown documents or Shiny apps.
Draws and displays 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
Utilities for verifying discrete, continuous and probabilistic forecasts, and forecasts expressed as parametric distributions are included.
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 from before this date.
When given a description of a polyhedral set by a system of linear inequalities Ax <= b, produce the list of the vertices of the set.
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>.
Integrated data management library that offers a variety of tools concerning the loading and manipulation of environmental data available from different Venezuelan governmental sources. Facilities are provided to plot temporal and spatial data as well as understand the health of a collection of meteorological data.
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.
An implementation of about 6 major classes of
statistical regression models. At the heart of it are the
vector generalized linear and additive model (VGLM/VGAM)
classes, and 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 VGAM package.
Currently only fixed-effects models are implemented,
i.e., no random-effects models. Many (150+) models and
distributions are estimated by maximum likelihood estimation
(MLE) or penalized MLE, using Fisher scoring. VGLMs can be
loosely thought of as multivariate GLMs. VGAMs are data-driven
VGLMs (i.e., with smoothing). The other classes are RR-VGLMs
(reduced-rank 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). Note that these functions are subject to change;
see the NEWS and ChangeLog files for latest changes.
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 provides an implementation of Linear discriminant analysis and quadratic discriminant analysis that works fine in very high dimension (when there are many more variables than observations).
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.
It will take the vectors of motion for two videos
(coming from a variant of shotdetect code allowing to store
detailed motion vectors in JSON format, for instance) and it
will look for comparing taking out the common chunk.
Then, provided you have some image's hashes it will compare
their signature in order to make up the decision about
chunk similarity of two video files.
ShotDetect is a free software which detects shots and scenes
from a video (http://johmathe.name/shotdetect.html).
Converts Vietnam's provinces' names and ID
across different formats. Handles diacritics and different spellings.
This package implements a fast regression algorithm for
building linear model for large data as defined in the paper
"VIF-Regression: A Fast Regression Algorithm for Large Data
(2011), Journal of the American Statistical Association, Vol.
106, No. 493: 232-247" by Dongyu Lin, Dean P. Foster, and Lyle
H. Ungar.
Contains a function to support the paper 'A sequential multiple change-point detection
procedure via VIF regression' (Accepted by Computational Statistics).
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).
New tools for the visualization of missing
and/or imputed values are introduced, which can be used for exploring the data and the
structure of the missing and/or imputed values. Depending on this structure
of the missing values, the corresponding methods may help to identify the
mechanism generating the missing values and allows to explore the data
including missing values. In addition, the quality of imputation can be
visually explored using various univariate, bivariate, multiple and
multivariate plot methods. A graphical user interface available in the
separate package VIMGUI allows an easy handling of the implemented plot
methods.
This package introduces new tools for the visualization of missing
and/or imputed values, which can be used for exploring the data and the
structure of the missing and/or imputed values. Depending on this structure
of the missing values, the corresponding methods may help to identify the
mechanism generating the missings and allows to explore the data including
missing values. In addition, the quality of imputation can be visually
explored using various univariate, bivariate, multiple and multivariate
plot methods. A graphical user interface allows an easy handling of the
implemented plot methods.
Provides tools for the statistical analysis of vine copula models.
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.
Implementation of the vine graphical model for building
high-dimensional probability distributions as a factorization of
bivariate copulas and marginal density functions. This package
provides S4 classes for vines (C-vines and D-vines) and methods
for inference, goodness-of-fit tests, density/distribution
function evaluation, and simulation.
A lattice violin-plot is overlayed with the arithmetic
mean and standard deviation.
A violin plot is a combination of a box plot and a kernel density plot.
viopoints draws one dimensional scatter plots with jitter
using kernel density estimates in a similar way to violin
plots.
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.
Port of the new 'matplotlib' color maps ('viridis' - the default
-, 'magma', 'plasma' and 'inferno') to 'R'. 'matplotlib' <http://matplotlib.org/
> is a popular plotting library for 'python'. These color maps are designed
in such a way that they will analytically be perfectly perceptually-uniform,
both in regular form and also when converted to black-and-white. They are
also designed to be perceived by readers with the most common form of color
blindness.
Port of the new 'matplotlib' color maps ('viridis' - the default
-, 'magma', 'plasma' and 'inferno') to 'R'. 'matplotlib' <http://matplotlib.org/
> is a popular plotting library for 'python'. These color maps are designed
in such a way that they will analytically be perfectly perceptually-uniform,
both in regular form and also when converted to black-and-white. They are
also designed to be perceived by readers with the most common form of color
blindness. This is the 'lite' version of the more complete 'viridis' package
that can be found at <https://cran.r-project.org/package=viridis>.
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.
Use VirusTotal, a Google service that analyzes files and URLs
for viruses, worms, trojans etc., provides category of the content hosted by a
domain from a variety of prominent services, provides passive DNS information,
among other things. See <http://www.virustotal.com> for more information.
A graphical tool designed to visualize and to give an overview of behavioural observations realized on individuals or groups. ViSiElse allows visualization of raw data during experimental observations of the realization of a procedure. It graphically presents an overview of individuals and group actions usually acquired from timestamps during video recorded sessions. Options of the package allow adding graphical information as statistical indicators (mean, standard deviation, quantile or statistical test) but also for each action green or black zones providing visual information about the accuracy of the realized actions.
Provides an R interface to the 'vis.js' JavaScript charting
library. It allows an interactive visualization of networks.
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', 'randomForest', etc.)
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.
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.
Displays multivariate data, based on Sammon's nonlinear mapping.
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 fitting routines for four versions of the
Vitality family of mortality models.
Provides individual- and aggregate-level graphical depictions of
patterns of treatment and response in patient registries, and a graphical
tool for examining potential for confounding in analyses of observational
data.
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.
Functions, Classes & Methods for estimation, prediction, and
simulation (bootstrap) of Variable Length Markov Chain ('VLMC') Models.
The tools you need to process, analyze, combine, integrate and
plot your fishery data: the georeferenced dataset from the Vessel Monitoring
System (VMS), from the Automatic Information System (AIS) or other tracking
devices, as well as the catches or landings dataset from the Logbook or Vessel
Register. Package 'vmsbase' is equipped by Viewer Tools to visually inspect data
at different steps of the analyses and to produce effective outputs for reports
and scientific publications. Viewers are conceived to show the VMS pings, to
visualize single or multiple tracks for fishing vessels, or to represent the VMS
data on Google Viewer, so that the user can produce easy to interpret and more
realistic visualization of both fishing effort and effort behaviour. Package
'vmsbase' represents the implementation of several R routines which have been
developed by the "Tor Vergata" University of Rome Team involved in the Italian
National Program for the Data Collection Framework for Fisheries Data between
2009-2012.
Using V-algorithm and Newton-Raphson method to obtain multiple-objective optimal design for estimating the shape of dose-response, the ED50 (the dose producing an effect midway between the expected responses at the extreme doses) and the MED (the minimum effective dose level) for the 2,3,4-parameter logistic models and for evaluating its efficiencies for the three objectives.
Voss package provides functionality for generating
realizations of a fractal Brownian function on uniform 1D & 2D
grid with classic and generic versions of the Voss algorithm
(random sequential additions)
Calculates voter transitions comparing two elections, using the function solve.QP() in package 'quadprog'.
Procedures for the manipulation, normalization, and plotting of phonetic and sociophonetic vowel formant data.  vowels is the backend for the NORM website.
Parametric and semiparametric inference for massively parallel
models, i.e., a large number of models with common design matrix, as often
occurs with brain imaging data.
Tools for tree crown structure description based on T-LiDAR data voxelisation
Variable Penalty Dynamic Time Warping for aligning GC-MS chromatograms to a master signal and more. With the appropriate penalty this method performs good alignment without altering the shape of peaks in GC-MS data.
In recognition that there are many factors (genetic loci, macro-genetic factors such as sex,
and environmental factors) that influence the environmental variation, the 'vqtl' package conducts genome
scans that accommodate and target these factors.  The main functions of this package, scanonevar() and
scanonevar.perm() take as input a cross object from the popular 'qtl' package.
Estimation of varying regression segments and a change point in
2-segment regression models with heteroscedastic variances, and with or
without a smoothness constraint at the change point.
vrmlgen creates 3D scatter and bar plots, visualizations of 3D meshes, parametric functions and height maps in web-formats like the Virtual Reality Markup Language (VRML, filetype .wrl) and the LiveGraphics3D format.
A collection of statistical tests for martingale difference hypothesis
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).
Calculates the enrichment of associated variant set (AVS) for an array of genomic regions. The AVS is the collection of disjoint LD blocks computed from a list of disease associated SNPs and their linked (LD) SNPs. VSE generates a null distribution of matched random variant sets (MRVSs) from 1000 Genome Project Phase III data that are identical to AVS, LD block by block. It then computes the enrichment of AVS intersecting with user provided genomic features (e.g., histone marks or transcription factor binding sites) compared with the null distribution.
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.
Designed to facilitate the assimilation, analysis and synthesis of animal location and movement data collected by the VEMCO suite of acoustic transmitters and receivers. As well as database and geographic information capabilities the principal feature of VTrack is the qualification and identification of ecologically relevant events from the acoustic detection and sensor data. This procedure condenses the acoustic detection database by orders of magnitude, greatly enhancing the synthesis of acoustic detection data.
A data.frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner.
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, new
categorical levels (levels seen during application, but not during training).
'vtreat::prepare' should be used as you would use 'model.matrix'.
Contains functions for visualization univariate data: ccdplot and qddplot.
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; however, in subsequent releases we would like
to add functionality for data collected with other systems.
Functions and data for use in visual word recognition research:
Computation of neighbors (Hamming and Levenshtein
distances), average distances to neighbors (e.g., OLD20),
and Coltheart's N. Also includes the LD1NN algorithm to
detect bias in the composition of a lexical decision task. Most of
the functions support parallel execution. Supplies wordlists for
several languages. Uses the string distance functions from the stringdist package by Mark van der Loo.
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 Computing in Science & Engineering (Volume:16, Issue: 6) on Sep. 09, 2014, doi:10.1109/MCSE.2014.96.
R interface to a W3C Markup Validation service.
See <http://validator.w3.org/> for more information.
Multivariate weather generator for daily climate variables based
on weather-states using 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. Data must
include the variable 'Rain' and can accept as many other variables as desired.
waffect (pronounced 'double-u affect' for 'weighted
affectation') is a package to simulate phenotypic (case or
control) datasets under a disease model H1 such that the total
number of cases is constant across all the simulations (the
constrain in the title). The package also makes it possible to
generate phenotypes in the case of more than two classes, so
that the number of phenotypes belonging to each class is
constant across all the simulations. waffect is used to assess
empirically the statistical power of Genome Wide Association
studies.
Square pie charts (a.k.a. waffle charts) can be used
to communicate parts of a whole for categorical quantities. To emulate the
percentage view of a pie chart, a 10x10 grid should be used with each square
representing 1% of the total. Modern uses of waffle charts do not
necessarily adhere to this rule and can be created with a grid of any
rectangular shape. Best practices suggest keeping the number of categories
small, just as should be done when creating pie charts. Tools are provided
to create waffle charts as well as stitch them together, and to use glyphs
for isotype pictogram creation.
Fit the fixed effect panel data model with heteroskedasticity and
autocorrelation correction.
Generates random data sets including: data.frames, lists,
and vectors.
Consider the intersection of two spaces: the complete solution space
to Ax = b and the N-simplex. The intersection of these two spaces is
a non-negative convex polytope. The package walkr samples from this
intersection using two Monte-Carlo Markov Chain (MCMC) methods:
hit-and-run and Dikin walk. walkr also provide tools to examine sample
quality.
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 'libmagic' library provides functions to determine
'MIME' type and other metadata from files through their "magic"
attributes. This is useful when you do not wish to rely solely on
the honesty of a user or the extension on a file name. It also
incorporates other metadata from the mime-db database
<https://github.com/jshttp/mime-db>.
Offers three overarching categories of functions to obtain bird
vocalization recordings from the web, manage sound files, and facilitate
(bio)acoustic analysis in R.
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.
Helpful tools for data processing and visualisation of results of the hydrological model WASIM-ETH.
Tools and functions to calculate actual evapotranspiration
using surface energy balance models.
This package imports U.S. Geological Survey (USGS) daily hydrologic data from USGS web services, plots the data, addresses some common data problems, and calculates and plots anomalies.
Provides support for creating waterfall charts in R
using both traditional base and lattice graphics.
There seems to be no simple way to create 'waterfall charts' in 'ggplot2' currently. This package contains a single function (waterfall) that draws simply a waterfall chart as a 'ggplot2' object. Some flexibility in the appearance is available.
Lets you connect to any of the Consortium of Universities for the Advancement
of Hydrologic Sciences, Inc. ('CUAHSI') Water Data Center 'WaterOneFlow' web services
and read any 'WaterML' hydrological time series data file. To see list of available
web services, see <http://hiscentral.cuahsi.org>. All versions of 'WaterML'
(1.0, 1.1 and 2.0) and both types of the web service protocol ('SOAP' and 'REST') are supported.
The package has six data download functions: GetServices(): show all public web
services from the HIS Central Catalog. HISCentral_GetSites() and HISCentral_GetSeriesCatalog():
search for sites or time series from the HIS Central catalog based on geographic bounding box,
server, or keyword. GetVariables(): Show a data.frame with all variables on the server.
GetSites(): Show a data.frame with all sites on the server. GetSiteInfo(): Show what variables,
methods and quality control levels are available at the specific site. GetValues(): Given a site
code, variable code, start time and end time, fetch a data.frame of all the observation time
series data values. The GetValues() function can also parse 'WaterML' data from a custom URL or
from a local file. The package also has five data upload functions:
AddSites(), AddVariables(), AddMethods(), AddSources(), and AddValues().
These functions can be used for uploading data to a 'HydroServer Lite' Observations
Data Model ('ODM') database via the 'JSON' data upload web service interface.
Methods for watersheds aggregation and spatial drainage network analysis.
Wrap-around Time Series (WATS) plots for interrupted time series
designs with seasonal patterns.
Computes Bayesian wavelet shrinkage credible intervals
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.
Wavelet analysis and reconstruction of time series, cross-wavelets and phase-difference (with filtering options), significance with simulation algorithms.
This package 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.
Wavelet routines that calculate single sets of wavelet
multiple correlations and cross-correlations out of n variables
(either 1D time series, 2D images or 3D arrays). They can later
be plotted in single graphs, as an alternative to trying to
make sense out of several sets of wavelet correlations or
wavelet cross-correlations. The code is based on the
calculation, at each wavelet scale, of the square root of the
coefficient of determination in a linear combination of
variables for which such coefficient of determination is a
maximum. The code provided here is based on the
wave.correlation routine in Brandon Whitcher's waveslim R
package Version: 1.6.4, which in turn is based on wavelet
methodology developed in Percival and Walden (2000); Gencay,
Selcuk and Whitcher (2001) and others.
For multivariate datasets, this function enables the estimation of missing data using the Weighted AVERage of all possible Regressions using the data available.
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.
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.
Supplies bootstrap alternatives to traditional hypothesis-test
and confidence-interval procedures such as one-sample and two-sample
inferences for means, medians, standard deviations, and proportions; simple
linear regression; and more. Suitable for general audiences, including
individual and group users, introductory statistics courses, and more advanced
statistics courses that desire an introduction to bootstrap methods.
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.
Tools for searching and downloading data and statistics from
the World Bank Data API (<http://data.worldbank.org/developers/api-overview>)
and the World Bank Data Catalog API (<http://data.worldbank.org/developers/data-catalog-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.
SOMs can be useful tools to group patterns containing several peaks. If peaks do not always occur at exactly the same position, classical distance measures cannot be used. This package provides SOM technology using the weighted crosscorrelation (WCC) distance.
WCE implements 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.
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.
The package contains the WCQ method for detection of QTL
effects in a small mapping population. It also contains
implementation of the Chen-Qin two-sample and one-sample test
of means.
Search, extract and format data from the World Bank's
World Development Indicators
Functions that help in fetching weather data from
websites. Given a location and a date range, these functions help fetch
weather data (temperature, pressure etc.) for any weather related analysis.
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.
Handle instant weather forecasts and geographical information. It combines multiple sources of information to obtain instant weather forecasts.
Chemical information from around the web. This package interacts
with a suite of web APIs for chemical information.
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.
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.
Takes screenshots of web pages, including Shiny applications.
A Stata-style `webuse()` function for importing named datasets from Stata's online collection.
Utility functions for developing web applications. Includes parsers
for application/x-www-form-urlencoded as well as multipart/form-data
and examples of using the parser with either httpuv or rhttpd.
Uses Protovis to provide web graphics for R (exposes most
low-level functions).  Package is still under active
development and shouldn't be considered stable until version
0.1.  Currently uses a web browser to process JavaScript,
although future version will process JavaScript directly and
return the SVG output.  Also does not properly support discrete
labels (e.g. with histograms) or statistical functions.  See
website for more details.
Provides functions to create factor variables with contrasts based on weighted effect coding. 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 The package also provides functionality for interactions between two factor variables based on weighted effect coding. Please note that this is a beta version: while functional, it does not follow all R conventions.
The WeightedCluster library provides functions to cluster states sequences and weighted data. These functionalities include aggregating replicated cases, an optimized weighted PAM algorithm, function computing cluster quality measures for a range of clustering solutions and miscellaneous functions to plot clustering solutions of state sequences.
Weighted descriptive statistics is the discipline of quantitatively describing the main features of real-valued fuzzy data which usually given from a fuzzy population. One can summarize this special kind of fuzzy data numerically or graphically using this package. To interpret some of the properties of one or several sets of real-valued fuzzy data, numerically summarize is possible by some weighted statistics which are designed in this package such as mean, variance, covariance and correlation coefficent. Also, graphically interpretation can be given by weighted histogram and weighted scatter plot using this package to describe properties of real-valued fuzzy data set.
This packages contains the Weighted Portmanteau Tests as
described in "New Weighted Portmanteau Statistics for Time
Series Goodness-of-Fit Testing' accepted for publication by the
Journal of the American Statistical Association.
Has functions to implement the weighted scores method and CL1 information criteria as an intermediate step for variable/correlation selection for longitudinal categorical and count data in Nikoloulopoulos, Joe and Chaganty (2011, Biostatistics, 12: 653-665) and Nikoloulopoulos (2015a,2015b).
Set of functions for estimating the Vevea and Hedges (1995)
weight-function model in R. 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.  Also now includes some software for quickly recoding survey data and plotting point estimates from interaction terms in regressions (and multiply imputed regressions).  Future versions of the package will be more closely integrated with "anesrake" and additional weighting tools and will provide the option to find weighting benchmarks and weight data using a variety of methodologies.  NOTE: Weighted partial correlation calculations temporarily pulled to address a bug.
The weightTAPSPACK subsets The American Panel Survey (TAPS) data by outcome and covariates, models the attrition rates, imputes data for attrited individuals, and finds weights for analysis.
Provides computational support for flow over weirs, such as sharp-crested, broad-crested, and embankments. Initially, the package supports broad- and sharp-crested weirs.
Convert 'WKT' to 'GeoJSON' and 'GeoJSON' to 'WKT'. Functions
included for converting between 'GeoJSON' to 'WKT', creating both
'GeoJSON' features, and non-features, creating WKT from R objects
(e.g., lists, data.frames, vectors), and linting 'WKT'.
Palettes generated mostly from Wes Anderson movies
This R package provides a computationally efficient way
of fitting weighted linear fixed effects estimators for
causal inference with various weighting schemes.  Imai
and Kim (2012) show that 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
also provides various robust standard errors and a
specification test for standard linear fixed effects
estimators.
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.
Integrates sophisticated mixed modelling methods with a whole genome approach to detecting significant QTL in linkage maps.
Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data. 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.
Non parametric alternative to Kolmogorov-Smirnov based
standard GSEA testing.
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); and Gary
King and Langche Zeng, 2007, "When Can History Be Our Guide?  The
Pitfalls of Counterfactual Inference," International Studies
Quarterly 51 (March).
logicless templating, reuse templates in many programming
languages including R
Shinohara et. al 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 programmatic access to the World Health Organization API.
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.
Retrieve data from the 'Whoapi' (https://whoapi.com) store of
domain information, including a domain's geographic location, registration
status and search prominence.
Provides very fast access to whole genome, population scale variation data
from VCF files and sequence data from FASTA-formatted files.
It also reads in alignments from FASTA, Phylip, MAF and other file formats.
Provides easy-to-use interfaces to genome annotation from UCSC and Bioconductor and gene ontology data
from AmiGO and is capable to read, modify and write PLINK .PED-format pedigree files.
Fit, forecast, predict massive spacio-temporal data
Extends the glmnet and relaxnet packages with polynomial basis expansions. Basis expansion is applied to the predictors and a subset of the basis functions is chosen using relaxnet. Predictors may be screened using correlation or t-tests. Screening is done separately within cross-validation folds. Cross-validation may be used to select the order of basis expansion and alpha, the elastic net tuning parameter.
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"
An API client for the Wikidata <http://wikidata.org/> store of
semantic data.
Provides an interface to the Wikipedia web application programming
interface (API), using internet connexion.Three functions provide details for
a specific Wikipedia page : all links that are present, all pages that link
to, all the contributions (revisions for main pages, and discussions for talk
pages). Two functions provide details for a specific user : all contributions,
and general information (as name, gender, rights or groups). It provides
additional information compared to others packages, as WikipediR. It does not
need login. The multiplex network that can be constructed from the results
of the functions of WikipediaR can be modeled as Stochastic Block Model as in
Barbillon P., Donnet, S., Lazega E., and Bar-Hen A. : Stochastic Block Models
for Multiplex networks: an application to networks of researchers, ArXiv
1501.06444, http://arxiv.org/abs/1501.06444.
Public attention is an interesting field of study. The
internet not only allows to access information in no time on
virtually any subject but via page access statistics gathered
by website authors the subject of attention as well can be
studied. For the omnipresent Wikipedia those access statistics
are made available via 'http://stats.grok.se' a server
providing the information as file dumps as well as as web API.
This package provides an easy to use, consistent and traffic
minimizing approach to make those data accessible within R.
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.
MediaWiki is  wiki platform. Providing the infrastructure of Wikipedia, it also offers very sophisticated archiving functionalities.
This package is built to store these wiki's archives to R object - data-frame, lists, vector and variables. All data are downloaded
with the help of MediaWiki REST API. For instance, you can get all revisions made by a contributor - contrib_list(), all the revisions
of a page page_revisions(), or create corpus of contributors - corpus_contrib_create() - and pages corpus_page_create(). Then, you can
make these corpus rich of data about contributors or pages - corpus_contrib_data() or corpus_page_data().
This package provides functions to perform fast variable
selection based on the Wilcoxon rank sum test in the
cross-validation or Monte-Carlo cross-validation settings, for
use in microarray-based binary classification.
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 draws heavily on the
classes and methods developed in the 'adehabitat' packages.
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.
Analysing convergent evolution using the Wheatsheaf index.
Helps for interfacing with the operating system
particularly for Windows.
Data sets from the World Input Output Database, for the years 1995-2011.
Perform the Wild Scale-Enhanced (WiSE) bootstrap.  Specifically, the user may supply a single or multiple equally-spaced time series and use the WiSE bootstrap to select a wavelet-smoothed model.  Conversely, a pre-selected smooth level may also be specified for the time series.  Quantities such as the bootstrap sample of wavelet coefficients, smoothed bootstrap samples, and specific hypothesis testing and confidence region results of the wavelet coefficients may be obtained.  Additional functions are available to the user which help format the time series before analysis.  This methodology is recommended to aid in model selection and signal extraction.
Note:  This package specifically uses wavelet bases in the WiSE bootstrap methodology, but the theoretical construct is much more versatile.
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.
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'.
Approach to the robustness via Weighted Likelihood.
A GUI R implementation of hierarchical Bayesian models of working memory, used for analyzing change detection data.
Distance discriminant analysis method is one of
classification methods according to multiindex performance
parameters.However,the traditional Mahalanobis distance
discriminant method treats with the importance of all
parameters equally,and exaggerates the role of parameters which
changes a little.The weighted Mahalanobis distance is used in
discriminant analysis method to distinguish the importance of
each parameter.In the concrete application,firstly based on the
principal component analysis scheme,a new group of parameters
and their corresponding percent contributions of the parameters
are calculated ,and the weighted matrix is regarded as the
diagonal matrix of the contributions rates.Setting data to
standardization,then the weighted Mahalanobis distance can be
calculated.Besides the methods metioned above,bayes method is
also given.
Analyzing the texture of an image from a multifractal wavelet leader analysis.
Software to book Wavelet Methods for Time Series Analysis,
Donald B. Percival and Andrew T. Walden, Cambridge University
Press, 2000.
Estimates Poole and Rosenthal W-NOMINATE scores from roll
call votes supplied though a 'rollcall' object from package
'pscl'.
Shows the relationship between an independent and dependent variable through Weight of Evidence and Information Value.
For a given Sentence-Aligned Parallel Corpus, it aligns words for each sentence pair. It considers many-to-one and symmetrization alignments. Moreover, it evaluates word alignment based on this package and some other software or method. It also builds an automatic dictionary of two languages based on given parallel corpus.
Tools for connecting to Wordbank, an open repository for
developmental vocabulary data.
A fast visualization tool for creating wordcloud
by using wordcloud2.js.
Matches words in one file with words in another file and shows index(row number) for the matches
An interface to WordNet using the Jawbone Java API to WordNet.
WordNet (<http://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
(<http://wordnet.princeton.edu/wordnet/license/>) are followed, and
proper reference is made to the project using an appropriate
citation (<http://wordnet.princeton.edu/wordnet/citing-wordnet/>).
This package collects several classical word pools used
most often to provide lists of words in psychological studies
of learning and memory.
An interactive laboratory for research on distributional semantic models ('DSM',
see <https://en.wikipedia.org/wiki/Distributional_semantics> for more information).
Implementing weighted predictiveness curve to visualize the marker-by-treatment relationship and measure the performance of biomarkers for guiding treatment decision.
Supplies permutation-test alternatives to traditional hypothesis-test
procedures such as two-sample tests for means, medians, and standard deviations;
correlation tests; tests for homogeneity and independence; and more. Suitable for
general audiences, including individual and group users, introductory statistics
courses, and more advanced statistics courses that desire an introduction to
permutation tests.
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.
Explore data in the 'wpp2015' (or 2012, 2010) package using a 'shiny' interface.
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.
Fits weighted quantile sum regression models, calculates weighted quantile sum index and estimated component weights.
A wrapper around Michel Scheffers's libassp (Advanced
Speech Signal Processor). The libassp 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.
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.
Function for writing a SNNS pattern file from a data.frame
or matrix.
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.
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.
Contains functions for working with the Worldwide Reference System
(WRS) 1 and 2 systems used by NASA. WRS-1 applies to Landsat 1-3, WRS-2
applies to Landsat 4-8. The package has functions for retrieving a given
path and row as a polygon, and for retrieving the path(s) and row(s)
containing a given raster or vector.
Contains the Worldwide Reference System (WRS) 1 and 2 polygon
data from NASA, for use by the wrspathrow package. WRS-1 and WRS-2
Shape files courtesy of the U.S. Geological Survey, from
http://landsat.usgs.gov/tools_wrs-2_shapefile.php
A collection of implementations of classical and novel
algorithms for weighted sampling without replacement.
Includes performance measurements and results of repeated
experiment runs (for correctness checks) for code in the
'wrswoR' package.
This open-source software package enables researchers to predict
individual ethnicity using his/her surname, geolocation, and other attributes
such as gender and age. The method utilizes the Bayes' rule to compute the
posterior probability of each racial category for any given individual voter.
The package implements methods described in Imai and Khanna (2016) <DOI:10.1093/pan/mpw001>.
Entropy weighted k-means (ewkm) 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)
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) extends this concept by grouping
features and weighting the group in addition to weighting
individual features.
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.
We propose weighted SVM methods with penalization form. By
adding weights to loss term, we can build up weighted SVM
easily and examine classification algorithm properties under
weighted SVM. Through comparing each of test error rates, we
conclude that our Weighted SVM with boosting has predominant
properties than the standard SVM have, as a whole.
Estimation and regression modeling of subdistribution functions for competing risks data with adjustment for covariate-dependent censoring, as described in He et al. (2015).
Perform the calculation of W-test, diagnostic checking, calculate minor allele frequency (MAF) and odds ratio.
Allows form managers to download entries from their respondents
using Wufoo JSON API. Additionally, the Wufoo reports - when public - can be
also acquired programmatically. Note that building new forms within this package
is not supported.
Methods to calculate and interpret climate change signals and time series from climate multi-model ensembles. Climate model output in binary 'NetCDF' format is read in and aggregated over a specified region to a data.frame for statistical analysis. Global Circulation Models, as the 'CMIP5' simulations, can be read in the same way as Regional Climate Models, as e.g. the 'CORDEX' or 'ENSEMBLES' simulations. The package has been developed at the 'Wegener Center for Climate and Global Change' at the University of Graz, Austria.
Book is "Linear Mixed Models: A Practical Guide Using
Statistical Software" published in 2006 by Chapman Hall / CRC
Press
A wrapper function and GUI for the X12 binaries
A graphical user interface for the x12 package
The US Census provides a seasonal adjustment program now
called 'X-13ARIMA-SEATS' building on both earlier Census programs called
X-11 and X-12 as well as the SEATS program by the Bank of Spain. Census
offers both source and binary versions -- which this package integrates
for use by other R packages.
Functions to extract business financial information from
an Extensible Business Reporting Language ('XBRL') instance file and the
associated collection of files that defines its 'Discoverable' Taxonomy
Set ('DTS').
Provides a tool for extracting information (entities and relations between them) in text datasets. It also emphasizes the results exploration with graphical displays. It is a rule-based system and works with hand-made dictionaries and local grammars defined by users. X.ent uses parsing with Perl functions and JavaScript to define user preferences through a browser and R to display and support analysis of the results extracted. Local grammars are defined and compiled with the tool Unitex, a tool developed by University Paris Est that supports multiple languages. See ?xconfig for an introduction.
Extensions of Exponential Random Graph Models (ERGM): Temporal Exponential Random Graph Models (TERGM), Generalized Exponential Random Graph Models (GERGM), Temporal Network Autocorrelation Models (TNAM), and Relational Event Models (REM).
Datasets and definitions of generic functions used in dependencies of the 'xergm' package.
Extreme Gradient Boosting, which is an
efficient implementation of gradient boosting framework.
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.
Interface to the XGobi and XGvis programs for graphical
data analysis.
The central goal of XGR is to provide a data interpretation system. It is designed to make a user-defined gene or SNP list (or genomic regions) more interpretable by comprehensively utilising ontology annotations and interaction networks to reveal relationships and enhance opportunities for biological discovery. XGR is unique in supporting a broad range of ontologies (including knowledge of biological and molecular functions, pathways, diseases and phenotypes - in both human and mouse) and different types of networks (including functional, physical and pathway interactions). There are two core functionalities of XGR. The first is to provide basic infrastructures for easy access to built-in ontologies and networks. The second is to support data interpretations via 1) enrichment analysis using either built-in or custom ontologies, 2) similarity analysis for calculating semantic similarity between genes (or SNPs) based on their ontology annotation profiles, 3) network analysis for identification of gene networks given a query list of (significant) genes or SNPs, and 4) annotation analysis for interpreting genomic regions using co-localised functional genomic annotations (such as open chromatin, epigenetic marks and TF binding sites) and using nearby gene annotations (by ontologies). Together with its web app, XGR aims to provide a user-friendly tool for exploring genomic relations at the gene, SNP and genomic region level.
R scripts for plotting and assessing XHMM whole-exome-sequencing-based CNV calls. XHMM (eXome Hidden Markov Model) is a C++ software package (http://atgu.mgh.harvard.edu/xhmm) written to call copy number variation (CNV) from next-generation sequencing projects, where exome capture was used (or targeted sequencing, more generally). This R package enables the user to visualize both the PCA normalization performed by XHMM and the CNVs it has called.
Conduct the likelihood ratio tests for Hardy-Weinberg equilibrium at marker loci on the X chromosome.
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.
Plotting ggplot2 graphs using the XKCD style.
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.
Provides comprehensive functionality to read, write and format Excel data.
Provides external JAR dependencies for the XLConnect package.
Provide R functions to read/write/format Excel 2007 and Excel 97/2000/XP/2003 file formats.
The xlsxjars package collects all the external jars
required for the xlxs package. This release corresponds to POI
3.10.1.
A toolbox for meta-analysis. This package includes a collection of functions for (1) implementing robust multivariate meta-analysis of continuous or binary outcomes; and (2) testing and correcting of publication bias in multivariate meta-analysis settings.
This is Xiaobei's miscellaneous classes and functions useful when
developing R packages, particularly for OOP using R Reference Class.
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".
Work with XML files using a simple, consistent interface. Built on
top of the 'libxml2' C library.
XML2R is a framework that reduces the effort required to transform
XML content into number of tables while preserving parent to child
relationships.
Convert the output of 'utils::getParseData()' to an 'XML'
tree, that is searchable and easier to manipulate in general.
Fit Markov Networks to a wide range of high-throughput genomics data.
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.
Xpose is collection of functions to be used as a model
building aid for non-linear mixed effects (population) analysis
using NONMEM. It facilitates data set checkout, exploration and
visualization, model diagnostics, candidate covariate identification
and model comparison.
A hierarchical Bayesian approach to assess functional impact of mutations on gene expression in cancer. Given a patient-gene matrix encoding the presence/absence of a mutation, a patient-gene expression matrix encoding continuous value expression data, and a graph structure encoding whether two genes are known to be functionally related, xseq outputs: a) the probability that a recurrently mutated gene g influences gene expression across the population of patients;
and b) the probability that an individual mutation in gene g in an individual patient m influences expression within that patient.
This is the tool set for crystallographer to design and analyze crystallization experiments, especially for ribosome from Mycobacterium tuberculosis.
Can be used for coloring output in terminals.
It was developed for the standard Ubuntu terminal but should be compatible
with any terminal using xterm or ANSI escape sequences. If run in windows,
RStudio, or any other platform not supporting such escape sequences it
gracefully passes on any output without modifying it.
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.
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 three regulatory frameworks are supported: CEM, SA-CCR and
IMM. The probability of default is implied through the credit spreads curve.
Currently, only IRSwaps are supported.
An implementation of Item Response Theory (IRT) in R, comprising of five modules:(1) common and utility functions, (2) estimation/calibration procedures, (3) computerized adaptive testing (CAT) framework, (4) automated test assembly (ATA) framework, and (5) multistage testing (MST) framework. See documentation at https://github.com/xluo11/xxIRT/blob/master/README.md.
A method for creating vertical histograms sharing a y-axis using
base graphics.
This package provides an alternative canonical
correlation/redundancy analysis function, with associated
print, plot, and summary methods.  A method for generating
helio plots is also included.
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 is a simple wrapper for the yakmo K-Means library (developed by Naoki Yoshinaga, see http://www.tkl.iis.u-tokyo.ac.jp/~ynaga/yakmo/). It performs fast and robust (orthogonal) K-Means.
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 new big.read.table() provided here may be
useful for large files when only a subset is needed.
This package implements the libyaml YAML 1.1 parser and emitter (http://pyyaml.org/wiki/LibYAML) for R.
Yield curve or zero-coupon prices interpolation and extrapolation using the Nelson-Siegel, Svensson, Smith-Wilson models, and Hermite cubic splines.
Calculates cryptic scores for genes using the ratio
(Cheung et al., 2008), the 3' enrichment method
(DeGennaro et al., 2013) and the probabilistic
method. It also provide	methods to estimates
cryptic transcription start sites.
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.
Deploy, maintain, and invoke models via the Yhat
REST API.
Modelling the yield curve with some parametric models.
The models implemented are: Nelson-Siegel, Diebold-Li and
Svensson.  The package also includes the data of the term
structure of interest rate of Federal Reserve Bank and European
Central Bank.
The clustering by k-means of using the target variable.
To determine the number of clusters with the variance of
the target variable in the cluster.
Analyzing performances of cricketers and cricket teams
based on 'yaml' match data from Cricsheet <http://cricsheet.org>.
An R implementation of Yplant, combined with the QuasiMC
raytracer. Calculate radiation absorption, transmission and scattering,
photosynthesis and transpiration of virtual 3D plants.
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.
Simple method for comparison of gene
expression generated across different experiments, and on
different platforms; that does not require global
renormalization, and is not restricted to comparison of
identical probes. YuGene works on a range of microarray dataset
distributions, such as between manufacturers. The resulting
output allows direct comparisons of gene expression between
experiments and experimental platforms.
Simulation and Inference for Stochastic Differential Equations.
Yummly.com is one of the world's largest and most powerful recipe search sites and this package aims to provide R bindings for publicly available Yummly.com Recipe API (https://developer.yummly.com/).
Implements principled methods to impute multivariate left-censored data and zeros in compositional data sets.
R package accompanying the book Working with dynamic
models for agriculture and environment, by Daniel Wallach
(INRA), David Makowski (INRA), James W. Jones (U.of Florida),
Francois Brun (ACTA), in preparation for June 2013.
Implements the estimation of local (and global) association measures: Ducher's Z, pointwise mutual information and normalized pointwise mutual information. The significance of local (and global) association is accessed using p-values estimated by permutations. Finally, using local association subgroup analysis, it identifies if the association between variables is dependent on the value of another variable.
A framework that brings together an abundance of common
statistical models found across packages into a unified interface, and
provides a common architecture for estimation and interpretation, as well
as bridging functions to absorb increasingly more models into the
collective library.  Zelig allows each individual package, for each
statistical model, to be accessed by a common uniformly structured call and
set of arguments.  Moreover, Zelig automates all the surrounding building
blocks of a statistical work-flow --procedures and algorithms that may be
essential to one user's application but which the original package
developer did not use in their own research and might not themselves
support. These include bootstrapping, jackknifing, and re-weighting of data.
In particular, Zelig automatically generates predicted and simulated
quantities of interest (such as relative risk ratios, average treatment
effects, first differences and predicted and expected values) to interpret
and visualize complex models.
Add-on package for Zelig 5. Enables the use of a variety of logit
and probit regressions.
Add-on package for Zelig 5. Enables the use of a variety of
ecological inference models.
This package provides an R wrapper for the Zendesk API
Functions to compute compositional turnover using zeta-diversity, the number of species shared by multiple assemblages. The package includes a Zeta.order() function to compute zeta-diversity for a specific number of assemblages, and a Zeta.decline() function to compute zeta-diversity for a range of numbers of assemblages. It also includes additional functions to explain how zeta-diversity varies with distance and with differences of environmental variables between assemblages, using linear regressions and generalized additive models.
Provides MCMC algorithms for the analysis of
zero-inflated count models. The case of stochastic search
variable selection (SVS) is also considered.  All MCMC samplers
are coded in C++ for improved efficiency. A data set
considering the demand for health care is provided.
Zillow, an online real estate company, provides real estate and
mortgage data for the United States through a REST API. The ZillowR package
provides an R function for each API service, making it easy to make API
calls and process the response into convenient, R-friendly data structures.
See <http://www.zillow.com/howto/api/APIOverview.htm> for the Zillow API
Documentation.
Fits observation-driven and parameter-driven models for zero-inflated time series
This package contains a database of city, state, latitude,
and longitude information for U.S. ZIP codes from the
CivicSpace Database (August 2004) augmented by Daniel Coven's
federalgovernmentzipcodes.us web site (updated January 22,
2012). Previous versions of this package (before 1.0) were
based solely on the CivicSpace data, so an original version of
the CivicSpace database is also included.
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 library derives from the most
famous word frequency distribution, Zipf's law.)
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.
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.
The analysis and inference of faunal remains recovered from
archaeological sites concerns the field of zooarchaeology. The zooaRch package
provides analytical tools to make inferences on zooarchaeological data.
Functions in this package allow users to read, manipulate, visualize, and
analyze zooarchaeological data.
ZooImage is a free (open source) solution for analyzing
digital images of zooplankton. In combination with ImageJ, a
free image analysis system, it processes digital images,
measures individuals, trains for automatic classification of
taxa, and finally, measures zooplankton samples (abundances,
total and partial size spectra or biomasses, etc.)
zm(), called with any active plot allow 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
Reproducible and remixable species distribution modelling. The
package reads user submitted modules from an online repository, runs full
SDM workflows and returns output that is fully reproducible.
Combines a forecast of a time series, using the function forecast(), with the dynamic plots from dygraphs.
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.
The zyp package contains an efficient implementation of Sen's slope method (Sen, 1968) plus implementation of Xuebin Zhang's (Zhang, 1999) and Yue-Pilon's (Yue, 2002) prewhitening approaches to determining trends in climate data.
Please send comments and bug reports to
ismrp@jasp.ism.ac.jp
Please send questions and comments to etiennead@gmail.com.
Please send questions and comments regarding NScluster to
ismrp@jasp.ism.ac.jp
Please send questions and comments regarding pbdR to
RBigData@gmail.com
Please send questions and comments regarding 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
Please send questions and comments regarding SAPP to
ismrp@jasp.ism.ac.jp
Please send questions and comments regarding timsac to
ismrp@jasp.ism.ac.jp
Dane R. Van Domelen <vandomed@gmail.com>
Renata T C Yokota <Renata.Yokota@wiv-isp.be>
Pedro Rafael Diniz Marinho <pedro.rafael.marinho@gmail.com>
Carlos J. Gil Bellosta <cgb@datanalytics.com>
Sy Han (Steven) Chiou  <schiou@d.umn.edu>
P Lafaye de Micheaux <lafaye@dms.umontreal.ca>
Robin K. S. Hankin <hankin.robin@gmail.com>
Lafaye de Micheaux Pierre <lafaye@dms.umontreal.ca>
Joao Vitor Dias Monteiro <monte092@umn.edu>
Ricardo de Matos Simoes <ricardo_dematossimoes@dfci.harvard.edu>
Karel Van den Meersche <karel.van_den_meersche@cirad.fr>
Jose Antonio Garcia Bueno <joseagbueno@gmail.com>
Anderson Rodrigo da Silva <anderson.agro@hotmail.com>
Ana Belen Nieto Librero <ananieto@usal.es>
David Alejandro Martell Juarez <alex91599@gmail.com>
A. Jonathan R. Godfrey <a.j.godfrey@massey.ac.nz>
L. A. van der Ark <L.A.vanderArk@uva.nl>
Francesca Marta Lilja Di Lascio <marta.dilascio@unibz.it>
K. Gerald van den Boogaart <support@boogaart.de>
P. Lafaye de Micheaux <lafaye@dms.umontreal.ca>
Dennis J. J. Walvoort <dennis.Walvoort@wur.nl>
Rafael S. de Souza <rafael.2706@gmail.com>
Sjoerd van der Spoel <R@sjoerdvanderspoel.nl>
Ernst van der Maaten <ernst.vandermaaten@gmail.com>
Eduardo L. T. Conceicao <mail@eduardoconceicao.org>
Marcelino de la Cruz Rot <marcelino.delacruz@upm.es>
Alexandre Adalardo de Oliveira <ecovirtualpackage@gmail.com>
Tomas J. Aragon Developer <aragon@berkeley.edu>
Manuel Oviedo de la Fuente <manuel.oviedo@usc.es>
Clayton Vieira Fraga Filho <forestgrowthsoftware@gmail.com>
Eduardo San Miguel Martin
<eduardo.san.miguel.martin@gmail.com>
Shaiful Anuar Abu Bakar <saab@um.edu.my>
Vincent T van Hees <vincentvanhees@gmail.com>
Gabriel Coelho Goncalves de Abreu <abreu_ga@yahoo.com.br>
Geraldine Van der Auwera <vdauwera@broadinstitute.org>
Rafael de Andrade Moral <rafael_moral@yahoo.com.br>
"Markus Loecher, Berlin School of Economics and Law (BSEL)" <markus.loecher@gmail.com>
Sai Thein Than Tun <theinthantun.sai@gmail.com>
Alejandro Quintela del Rio <aquintela@udc.es>
Jorge Luis Ojeda Cabrera <jojeda@unizar.es>
Eufrasio de A. Lima Neto <eufrasio@de.ufpb.br>
Camilo Antonio Suarez Bolanos <caasuarezbo@unal.edu.co>
Ricardo Jorge de Almeida Queiroz Filho <rjaqfcin@gmail.com>
Jan van der Laan <djvanderlaan@unrealizedtime.nl>
"Antoine Tremblay, Dalhousie University" <trea26@gmail.com>
"Robin K. S. Hankin" <hankin.robin@gmail.com>
Elizabeth Holmes - NOAA Federal <eli.holmes@noaa.gov>
Fernando Ferraz do Nascimento <fernandofn@ufpi.edu.br>
Antonio Hermes M. da Silva-Junior <hermes@ccet.ufrn.br>
Alysha M De Livera <alyshad@unimelb.edu.au>
Stephen L R Ellison <s.ellison@lgc.co.uk>
Cherise R. Chin Fatt <cherise.chinfatt@utdallas.edu>
Marcelino de la Cruz <marcelino.delacruz@upm.es>
Julio Cesar Hernandez Sanchez <juliocesar_avila@usal.es>
Pierre Lafaye de Micheaux <lafaye@dms.umontreal.ca>
Rune Haubo Bojesen Christensen <rune.haubo@gmail.com>
Euloge Clovis Kenne Pagui <kenne@stat.unipd.it>
Joaquin Bienvenido Ordieres Mere <j.ordieres@upm.es>
ACHIEPO Odilon Yapo M. <kingodilon@gmail.com>
Marieke van der Maaten-Theunissen <marieketheunissen@gmail.com>
Peter J. van der Most <p.j.van.der.most@umcg.nl>
"Shingo Yamamoto (gloops, Inc.)" <si.yamamoto@gloops.com>
Vito M. R. Muggeo <vito.muggeo@unipa.it>
Sy Han (Steven) Chiou <schiou@hsph.harvard.edu>
Raymond K. W. Wong <raymondkww.dev@gmail.com>
María del Carmen Calatrava Moreno
<mc.calatrava.moreno@gmail.com>
Titus von der Malsburg <malsburg@posteo.de>
Rutger M. van den Bor <r.m.vandenbor@umcutrecht.nl>
Marcelino de la Cruz <marcelino.delacruz@urjc.es>
Jakson Alves de Aquino <jalvesaq@gmail.com>
Prof. Juan David Velasquez H. <jdvelasq@unal.edu.co>
Willem Robert van Hage <willem.van.hage@synerscope.com>
Frederick Kin Hing Phoa <fredphoa@stat.sinica.edu.tw>
Stephen A Sefick Jr. <ssefick@gmail.com>
Daniel A. Dos Santos <pseudalopex_79@yahoo.com>
Jesus Maria Rodriguez Rodriguez <jesusmro@ono.com>
Gabriel Henrique Oliveira Assuncao <gabrielhenryoliver@hotmail.com>
K. Gerald van den Boogaart <boogaart@math.tu-freiberg.de>
Antonio Fabio Di Narzo <antonio.fabio@gmail.com>
Joerg Schlarmann (aka Produnis) <schlarmann@produnis.de>
Olivier M. F. Martin <olivmrtn@gmail.com>
Maintainers are not available to give advice on using a package
they did not author.
Several parts are still preliminary and may be changed in the
future. This typically includes function and argument names, as
well as defaults for arguments and return values.
Several parts are still preliminary and may be changed in the
future. this typically includes function and argument names, as
well as defaults for arguments and return values.
SEVERAL PARTS ARE STILL PRELIMINARY AND MAY BE CHANGED IN THE
FUTURE. THIS TYPICALLY INCLUDES FUNCTION AND ARGUMENT NAMES, AS
WELL AS DEFAULTS FOR ARGUMENTS AND RETURN VALUES.
The header file blaswrap.h, f2c.h and fgsg.h are from the
VisualStudio library created by Julie Langou.
This software comes with NO warranty! It is NOT intended to be
used in clinical applications! For evaluation only!
Package stable is available at http://www.robustanalysis.com
In order to use this package you need your personal Project Vote
Smart API key. To get an API-key you need to sign up for access
to PVS' API (see http://votesmart.org/share/api for details).
Whenever you are using pvsR make sure that your personal PVS
API key is saved as a character string in the variable pvs.key
(pvs.key <- "yourkey"). If there is no valid PVS API key saved
in the variable pvs.key the functions in this package won't
work. This program is free software; you can redistribute it
and/or modify it under the terms of the GNU General Public
License as published by the Free Software Foundation; either
version 2 of the License, or (at your option) any later
version. This program is distributed in the hope that it will
be useful, but WITHOUT ANY WARRANTY; without even the implied
warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the GNU General Public License for more details.
More information about the system requirements can be found in
the README file.
For details and derivation, see Braumoeller, Bear F. "Guarding
Against False Positives in Qualitative Comparative Analysis."
Forthcoming, Political Analysis.
This will be used generally to communicate with HTTP servers and
specifically in the SOAP package, HTML forms and for accessing
data on Web sites that require more state information than
simply URL access (e.g. cookies).
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".
See http://www.json.org/JSON_checker/test.zip for tests. We now
use code from the libjson project
(http://libjson.sourceforge.net).
The files configure.in, cleanup, Makevars.in and Makevars.win are
based on the same files found in RPostgreSQL. I thank Dirk
Eddelbuettel for giving the go ahead to reuse their build
setup. Copyright of the unmodified protions remains with the
original authors. The files in src/libpq/ are part of
PostgreSQL. Please refer to http://www.postgresql.org/ for
their copyright and license.
The name "Scrabble" is a trademark of Hasbro, Inc. in the United
States and Canada; elsewhere, it is a trademark of Mattel.
This is experimental software distributed free of charge and
comes with no warranty!  Exercise professional caution.
In version 2.4.0 of this package, a new approach to garbage
collection has been implemented and it is experimental. You can
disable it via the configuration option --enable-nodegc=no.
However, you are encouraged to use this and report problems as
the results are beneficial and being able to produce any errors
should they occur will be very helpful.
2015-01-03 19:56:29 UTC; Steven Harris Ranney
2012-06-11 14:36:21 UTC; Sophie Baillargeon
2010-01-31 13:29:31 UTC; Jens Henrik Badsberg
2015-02-26 17:45:29 UTC; Sophie Baillargeon
2015-08-23 02:08:23 UTC; Fernando de Villar
2016-06-21 08:12:20 UTC; LARMARANGE Joseph
2016-02-23 18:10:11 UTC; LARMARANGE Joseph
2014-08-28 18:37:46 UTC; Sophie Baillargeon
2016-08-15 00:57:22 UTC; Sebastian Calonico
2016-07-26 19:41:07 UTC; Timothy Schwinghamer
2014-10-17 18:39:03 UTC; Christiane Dargatz
2014-12-04 17:04:02 UTC; Sophie Baillargeon
2016-03-19 23:54:53 UTC; Sophie Baillargeon
Image Magick (for reading non PPM format), dcraw
(for reading RAW images).
Optionally Latte-integrale, Bertini, and Macaulay2.
Cygwin is required for each of the above for Windows users. See
INSTALL file for details.
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 JDK 1.2 or higher (for JRI/REngine JDK 1.4 or
higher), GNU make
Requires external zip utility, available in path.
On windows, it's sufficient to install RTools.
JAGS (>= 3.4.0) (see
http://mcmc-jags.sourceforge.net)
Preferred genomic operations engine: BEDtools,
BEDOPS and Tabix.
OpenBUGS (>= 3.2.2), hence Windows or Linux
MAGeCK (=0.51, from
http://sourceforge.net/p/mageck/wiki/Home/), bowtie2
(http://bowtie-bio.sourceforge.net/bowtie2/index.shtml)
OpenCL library; double-precision AMD or Nvidia GPU;
GNU make
xclip (http://sourceforge.net/projects/xclip/) or
xsel (http://www.vergenet.net/~conrad/software/xsel/) for
accessing the X11 clipboard
Java (>= 7.0); Stanford CoreNLP
<http://nlp.stanford.edu/software/corenlp.shtml> (>= 3.5.2)
couchDB instance to connect to and work with.
nvcc (release >= 3.1) (NVIDIA Cuda Compiler
driver); Linux operating system; GNU make.
libcurl: libcurl-devel (rpm) or
libcurl4-openssl-dev (deb).
xclip <http://sourceforge.net/projects/xclip/> or
xsel <http://www.vergenet.net/~conrad/software/xsel/> for
accessing the X11 clipboard
none, one or more of JAGS (>= 3.0.0), WinBUGS (>=
1.4), OpenBUGS (>= 3.2.2)
GLPK library package (e.g., libglpk-dev on
Debian/Ubuntu)
Xft (only needed for platforms other than OSX and
Windows)
Python (>= 2.7 or >= 3.5) and elex package
Debian or Ubuntu system with access to Goto Blas,
Intel MKL, Atlas development build as well as a Nvidia GPU with
CUDA support
zlib headers and library. OpenSSL headers and
library. LibSSH2 (optional on non-Windows) to enable the SSH
transport.
Nvidia's CUDA toolkit (>= release 5.0) and Nvidia
GPU with compute capibility >=2.0
C++11 (supporting at least std=c++0x), OpenCL
shared library (provided by an SDK such as AMD/NVIDIA) and
OpenCL headers including the C++ header file (provided by
Khronos if not by SDK)
libhdf5 (>= 1.8.12) with C++ interface
(--enable-cxx=yes) and v18 API enabled
BLAS/LAPACK libraries, PLASMA library , NVIDIA CUDA
toolkit, MAGMA library
Apache Hadoop >= 2.6.0
(https://hadoop.apache.org/releases.html#Download); Obsolete:
Hadoop core >= 0.19.1 and <= 1.0.3 or CDH3
(http://www.cloudera.com); standard unix tools (e.g., chmod)
ImageMagick (http://imagemagick.org) or
GraphicsMagick (http://www.graphicsmagick.org)
A C library with the fesetround/fegetround
functions.
OpenBabel (>= 2.3.1) with headers.
http://openbabel.org
Package vignettes based on R Markdown v2 require
Pandoc (http://pandoc.org). The function rst2pdf() and
vignettes based on reStructuredText require rst2pdf
(https://github.com/rst2pdf/rst2pdf).
ImageJ (>=1.48), ij.jar (see
http://imagej.nih.gov/ij/), Java (>=1.6.0)
Docker (see
<https://docs.docker.com/engine/installation/>), Rabix (see
<https://github.com/rabix/rabix>)
JAGS (>= 3.0.0) (see
http://mcmc-jags.sourceforge.net)
At least trial version of LocalSolver to be
downloaded from http://www.localsolver.com/download.html
ImageMagick++: ImageMagick-c++-devel (rpm) or
libmagick++-dev (deb)
ADMB version 11 (http://admb-project.org/) for
use.admb=TRUE; see readme.txt
JAGS (>= 4.1) for the script version, both JAGS and
GTK+ for the GUI version. For install instructions, see README
file.
MonetDB, available from http://www.monetdb.org or
MonetDBLite R package
jags (>= 4.0.0) (see
http://mcmc-jags.sourceforge.net)
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.
pandoc, ipython (>= 3.0) or jupyter,
ipython/jupyter notebook optional dependencies, pywin32 (on
windows)
A compiler with C++11 support for the thread
library, Requires Rtools >= 33 (i.e. R >= 3.3.0) to build on
Windows.
pandoc (http://johnmacfarlane.net/pandoc) for
exporting markdown files to other formats.
For the MERLIN wrapper, MERLIN
(www.sph.umich.edu/csg/abecasis/merlin) must be installed and
pointed to in the PATH environment variable.
The 'Japanese.Rnw' vignette requires uplatex and
dvipdfmx.
OpenMPI (>= 1.5.4) on Solaris, Linux, Mac, and
FreeBSD. MS-MPI (Microsoft HPC Pack 2012) or MPICH2 (>=
1.4.1p1) 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.
OpenMPI (>= 1.5.4) on Solaris, 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 and Mac.
(Parallel) HDF5 and (Parallel) NetCDF4 (4.1 or later)
libraries. No MPI library required on Windows.
OpenMPI (>= 1.5.4) on Solaris, Linux, Mac, and
FreeBSD. No MPI library required on Windows yet.
Linux, Mac OSX, and Windows, or ZeroMQ library >=
4.0.4. Solaris 10 needs ZeroMQ library 4.0.7 and OpenCSW.
Poppler C++ interface library and headers
Phoenix NLME with Phoenix Modeling Language (PML)
license
For Windows users, Rtools (see
http://cran.r-project.org/bin/windows/Rtools/).
Python 2.7.x or Python 3.2.x-3.4.x, NumPy (Python
scientific computing package)
pandoc (>= 1.12.3) -
http://johnmacfarlane.net/pandoc
JAGS (>= 3.2.0) (see
http://mcmc-jags.sourceforge.net)
proj 4.4.6 or higher (http://proj.maptools.org/)
Pasting to clipboard requires the xclip command on
BSD and Linux or the pbcopy command on Mac OS.
Python (>= 2.7.0) with header files and shared
library (UNIX) / static library (Windows)
Qt4 libraries and headers (http://qt.nokia.com),
cmake (http://www.cmake.org)
OpenBugs for functions bugs() and openbugs() or
WinBUGS 1.4 for function bugs()
linux (>= 3.0), libapparmor-dev (optional)
A valid Bloomberg installation. The API headers and
dynamic library are downloaded from
<https://github.com/Rblp/blp> during the build step. See
<http://bloomberg.github.io/blpapi-docs/cpp/3.8> as as
<http://www.bloomberglabs.com/api/> for API documentation. A
compiler recent enough for (at least partial) C++11 support;
g++-4.6.* or later should be sufficient and g++-4.9.* or later
is preferred.
GMP (GNU MP bignum library from http://gmplib.org/)
A Debian-based system with the libapt-pkg-dev
package
A 64-bit POSIX OS such as Linux or OS X with IANA
time zone data in /usr/share/zoneinfo as well as a C++11
compiler.
A POSIX system. Currently Linux and OS X are known
to work.
A C++11 compiler. Version 4.6.* of g++ (as
currently in Rtools) is insufficient; versions 4.8.*, 4.9.* or
later will be fine.
Octave (>= 3.2.4) and its development files
GNU make, Windows: cmd.exe and cscript.exe,
Solaris: g++ is required
The 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) is required.
MsgPack support is activated if the (optional) RcppMsgPack
package is detected; it can be installed from the ghrr drat
(see Additional_repositories below).
DieHarder library (>= 3.31.1) from
http://www.phy.duke.edu/~rgb/General/dieharder.php, GNU GSL for
the GSL random-number generators
MOSEK (http://www.mosek.com) and MOSEK License for
use of Rmosek, optional use of the pogs optimizer may require
CUDA/GPU accoutrements.
for building from source: GDAL >= 1.6.3, library
from http://trac.osgeo.org/gdal/wiki/DownloadSource and PROJ.4
(proj >= 4.4.9) from http://download.osgeo.org/proj/; GDAL OSX
frameworks built by William Kyngesburye at
http://www.kyngchaos.com/ may be used for source installs on
OSX.
GEOS (>= 3.2.0); for building from source: GEOS
from http://trac.osgeo.org/geos/; GEOS OSX frameworks built by
William Kyngesburye at http://www.kyngchaos.com/ may be used
for source installs on OSX.
OpenGL, GLU Library, zlib (optional), libpng
(>=1.2.9, optional), FreeType (optional)
R built as a shared or static library, 'MPI'
library.
Java (>= 1.5), zlib headers and library.
Oracle Java 7,Apache Kafka 2.8.0-0.8.1.1
notepad.exe, mark.exe (>= 8.0) (or mark32.exe and
mark64.exe) and rel_32.exe (see README.txt)
libmariadb-client-dev | libmariadb-client-lgpl-dev
| libmysqlclient-dev (deb), mariadb-devel (rpm), mariadb |
mysql-connector-c (brew), mysql56_dev (csw)
Oracle Instant Client or Oracle Database Client
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 2.2.0 or
later. On Debian/Ubuntu these are libprotoc-dev and
libprotobuf-dev, while on Fedora protobuf-devel and
protobuf-compiler are needed.
The 'curl' binary has to be in the path (and this
is checked at package startup), a user API key (which can be
obtained from http://www.pushbullet.com), and one or more
devices to push messages to which may be any one of an (Android
or iOS) phone, the (Chrome or Firefox, or Opera or Safari)
browser or (Windows or Mac) desktop application provided the
corresponding Pushbullet 'app' has been installed on any one of
these.
Windows, Python (>= 2.4.0), ArcGIS (>= 9.2)
Python (>= 2.7) and Python headers and libraries
(See the INSTALL file)
QuantLib library (>= 1.7.0) from
http://quantlib.org, Boost library from http://www.boost.org
need the RDRAND instruction on Intel CPU. and C
compiler must be able to compile a GNU-style in-line assembler.
NW RFC SDK downloaded from http://service.sap.com
Tcl/Tk (>= 8.5), Tktable (>= 2.9, optional)
The Boost 'program_options' library
(http://boost.org) is required.
Python (>=2.6) in path and NumPy module installed,
ghostscript (>=9.0)
ZeroMQ >= 3.0.0 libraries and headers (see
<http://www.zeromq.org/>; Debian packages libzmq3, libzmq3-dev,
Fedora packages zeromq3, zeromq3-devel)
GLPK library, including -dev or -devel part
zlib headers and libraries, optionally also bzip2
and POSIX-compliant regex functions.
(PDF)LaTeX (http://www.latex-project.org/) with
'pdfpages' package for studentGrowthPlot option in visualizeSGP
to bind together student growth plots into school catalogs
little-endian processor required for some functions
(see README)
Komodo Edit (http://www.openkomodo.com), SciViews-K
(http://www.sciviews.org/SciViews-K)
Antiword (<http://www.winfield.demon.nl/>) for
reading MS Word files, pdfinfo and pdftotext from Poppler
(<http://poppler.freedesktop.org/>) for reading PDF
Teradata Aster Database 5.20 (AD5.20) or higher,
Teradata Aster Analytical Foundation 5.20 (AA5.20) or higher.
PARI/GP >= 2.3.0 [strongly recommended for
logkda()]
nvcc (release >= 7.1) (NVIDIA Cuda Compiler
driver); GNU make
V8: libv8-dev (deb), v8-devel (rpm), v8-3.14 (arch)
libmagic (>= 5.14) for Unix/Linux/macOS; Rtools
3.3+ for Windows
PhantomJS (http://phantomjs.org) for taking
screenshots, ImageMagick (http://www.imagemagick.org) or
GraphicsMagick (http://www.graphicsmagick.org) and OptiPNG
(http://optipng.sourceforge.net) for manipulating images.
Java (>= 5.0); WordNet database files (direct
download:
<http://wordnetcode.princeton.edu/3.0/WNdb-3.0.tar.gz>; Debian
and Fedora package: wordnet)
Perl (>= 5.0), Unitex (>= 3.0
http://www-igm.univ-mlv.fr/~unitex/)
The standalone program xgobi must be installed
additionally, see file README, or INSTALL.windows under Windows
libxml2: libxml2-dev (deb), libxml2-devel (rpm)
Accurate, Adaptable, and Accessible Error Metrics for Predictive
Models
Access to Abbyy Optical Character Recognition (OCR) API
Tools for Approximate Bayesian Computation (ABC)
Data Only: Tools for Approximate Bayesian Computation (ABC)
ABCDE_FBA: A-Biologist-Can-Do-Everything of Flux Balance
Analysis with this package
Implementation of Artificial Bee Colony (ABC) Optimization
Approximate Bayesian Computational Model for Estimating P2
Approximate Bayesian Computation via Random Forests
Modelling Multivariate Data with Additive Bayesian Networks
Improved False Positive Control of Gene-Permuting GSEA with
Absolute Filtering
Abundant regression and high-dimensional principal fitted
components
Abrupt Change-Point or Aberration Detection in Point Series
Functions for Processing and Analyzing Accelerometer Data
Functions for Processing Minute-to-Minute Accelerometer Data
Missing Value Imputation for Accelerometer Data
Creation and Evaluation of Acceptance Sampling Plans
Data Quality Visualization Tools for Partially Accruing Data
Tools for Autoregressive Conditional Duration Models
Optimal Bayesian Experimental Design using the ACE Algorithm
ace() and avas() for selecting regression transformations
Estimating Dynamic Heritability and Twin Model Comparison
Align-and-Count Method comparisons of RFLP data
Implements ACME Estimator of Bird and Bat Mortality by Wind
Turbines
Affymetrix SNP Probe-Summarization using Non-Negative Matrix
Factorization
Modelling dependence with multivariate Archimax (or any
user-defined continuous) copulas
Convenience functions for analytical Customer Relationship
Management
A Cost-Minimal Regular Spanning Subgraph with TreeClust
Download, Manipulate, and Present American Community Survey and
Decennial Data from the US Census
Gene Enrichment Analysis from ACSN Maps or GMT Files
Algorithmic Complexity for Short Strings
Data Only: Algorithmic Complexity of Short Strings (Computed via
Coding Theorem Method)
A Companion Package for the Book "A Course in Statistics with R"
Asymptotic Classification Theory for Cognitive Diagnosis
Actuarial Functions and Heavy Tailed Distributions
The R Package Ada for Stochastic Boosting
Applies Multiclass AdaBoost.M1, SAMME and Bagging
Discrete and Global Optimization Routines
A Class of Adaptive Elastic Net Methods for Censored Data
Adaptive Semiparametric Regression with Simultaneous Confidence
Bands
Implementation of a generic adaptive Monte Carlo Markov Chain
sampler
Binomial and Multinomial Additive Hazards Models
Fit Additive Hazards Models for Survival Analysis
Discover and Install Useful RStudio Addins
Additivity Tests in the Two Way Anova with Single Sub-class
Numbers
A Package for 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
adephylo: exploratory analyses for the phylogenetic comparative
method
Adequacy of Probabilistic Models and General Purpose
Optimization
calculate ad hoc distance thresholds for DNA barcoding
identification
An Interpretation of the ADM method - automated detection
algorithm
Adaptive Mixture of Student-t distributions
Admixture Graph Manipulation and Fitting
Regularized Model with Selecting the Number of Non-Zeros
Fast Clustering Using Adaptive Density Peak Detection
Upper Clopper-Pearson Confidence Limits for Burn-in Studies
under Additional Available Information
Wavelet Analysis of Genomic Data from Admixed Populations
Change Point Analysis in ARIMA Forecasting
Download and Process AEMO Price and Demand Data
Model-Based Estimation of Confounder-Adjusted Attributable
Fractions
Hybrid Simulation and Genome Scan for Dominant Markers
Accelerated Failure Time Model with Generalized Estimating
Equations
Aggregate Numeric, Date and Categorical Variables by an ID
Aggregation Operators and Preordered Sets
Statistical Tools for Measuring Agreement
Statistical Procedures for Agricultural Research
Calculate Agreement or Consensus in Ordered Rating Scales
Estimation in Adaptive Group Sequential Trials
Miscellaneous plotting and utility functions
Regularization for semiparametric additive hazards regression
Fast Searching for Multiple Keywords in Multiple Texts
Estimation and Testing of Average Hazard Ratios
Model Selection and Multimodel Inference Based on (Q)AIC(c)
Estimation of Box-Cox Power Transformation Parameter
Tools for reading AIDA (http://aida.freehep.org/) files into R
Interpolation of Irregularly and Regularly Spaced Data
Adaptive Kmeans algorithm based on threshold
Immunoglobulin Clonal Lineage and Diversity Analysis
Quantile Regression Using Asymmetric Laplace Distribution
Estimating Absolute Protein Quantities from Label-Free LC-MS/MS
Proteomics Data
Haplotype Two Snips Out of a Paired Group of Patients
Comparison of Alternative Multiple Sequence Alignments
Alignment of Phonetic Sequences Using the 'ALINE' Algorithm
Generate Age-Length Keys for fish populations
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
A fast, unbiased and exact allelic exact test
Computes all of a word's possible spellings
R Client for the Lagotto Altmetrics Platform
Generalization of the Convex Hull of a Sample of Points in the
Plane
Obtain Alpha-Outlier Regions for Well-Known Probability
Distributions
Implementation of the 3D Alpha-Shape for the Reconstruction of
3D Sets from a Point Cloud
Data to accompany Applied Linear Regression 3rd edition
Data to accompany Applied Linear Regression 4rd 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
Optimal Experimental Designs for Accelerated Life Testing
Compare Gene Expressions from 2-Treatment RNA-Seq Experiments
European Commission Annual Macro-Economic (AMECO) Database
Adaptive Management of Epidemiological Interventions
Additive and Multiplicative Effects Models for Networks and
Relational Data
This package includes pricing function for selected American
call options with underlying assets that generate payouts
A Multidirectional Optimum Ecotope-Based Algorithm
Generates Samples or Complete List of Brazilian IBGE (Instituto
Brasileiro De Geografia e Estatistica) Census Households,
Geocoding it by Google Maps
Statistical Analysis of Amplicon Data of the Same Sample to
Identify Artefacts
Simple and Canonical Correspondence Analysis
Analogue and Weighted Averaging Methods for Palaeoecology
Additional Functions for Use with the Analogue Package
Model Layer for Automatic Data Analysis via CSV File
Interpretation
Functions for analysis of fMRI datasets stored in the ANALYZE or
NIFTI format
Bidirectional Connector to Anametrix API
Assigning Ancestry Based on Population References
Statistical analysis of surveys with anchoring vignettes
An extended Bayesian Learning Technique developed by Dr. Geoff
Webb
Adaptive Neuro Fuzzy Inference System in R
Simulate a Bus Route Creel Survey of Anglers
Animal track reconstruction for high frequency 2-dimensional
(2D) or 3-dimensional (3D) movement data
A Gallery of Animations in Statistics and Utilities to Create
Animations
AnnotLists: A tool to annotate multiple lists from a specific
annotation file
Anonymize Data Containing Personally Identifiable Information
Statistical Methods for Anthropometric Data
Analysis of Overdispersed Data using S3 methods
aoristic analysis with spatial output (kml)
Format Outputs of Statistical Tests According to APA Guidelines
Process the Apache Web Server Access Log Files
Create American Psychological Association (APA) Style Tables
Phylogenetic Methods for Multiple Gene Data
Datasets from Hosmer, Lemeshow and Sturdivant, "Applied Logistic
Regression" (3rd ed.)
Another Plot PACKage: stem.leaf, bagplot, faces, spin3R,
plotsummary, plothulls, and some slider functions
Pre- and Postprocessing for AP-MS data analysis based on
spectral counts
Compute Appell's F1 hypergeometric function
Approximate Path for Penalized Likelihood Estimators
Functions and Data Sets for 'Applied Predictive Modeling'
Amyloid Propensity Prediction Neural Network
Bayesian prediction of complex computer codes
Datasets from Draper and Smith "Applied Regression Analysis"
(3rd Ed., 1998)
Tools for the a Priori Comparison of Regression Modelling
Strategies
Amdahl's Profiler, Directed Optimization Made Easy
General Utility Functions for the 'Agricultural Production
Systems Simulator'
Edit, Run and Evaluate APSIM Simulations Easily Using R
apsrtable model-output formatter for social science
Average Positive Predictive Values (AP) for Binary Outcomes and
Censored Event Times
Functions to help display air quality model output and
monitoring data
Interface methods to use with an ActiveQuant Master Server
AquaEnv - an integrated development toolbox for aquatic chemical
model generation
Segmentation of an autoregressive Gaussian process of order 1
Rigorous Data Reduction and Error Propagation of Ar40 / Ar39
Data
Fitting Univariate Censored Linear Regression Model with
Autoregressive Errors
Example Datasets from Archaeological Research
Plant Root System Architecture Analysis Using DART and RSML
Files
Tools for Storing, Restoring and Searching for R Objects
Tools for Archiving, Managing and Sharing R Objects via GitHub
Activated Region Fitting, fMRI data analysis (3D)
Fractional ARIMA (and Other Long Memory) Time Series Modeling
Arfima-MLM Estimation For Repeated Cross-Sectional Data
Command line optional and positional argument parser
Improved Communication to Users with Respect to Problems in
Function Arguments
Data Analysis Using Regression and Multilevel/Hierarchical
Models
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
Tools for Simulating Direct Behavioral Observation Recording
Procedures Based on Alternating Renewal Processes
Apply a Function to a Margin of an Array
Aligned Rank Transform for Nonparametric Factorial Analysis
Time-Varying DBN Inference with the ARTIVA (Auto Regressive TIme
VArying) Model
Gene and Pathway p-values computed using the Adaptive Rank
Truncated Product
Mining Association Rules and Frequent Itemsets
Mining NB-Frequent Itemsets and NB-Precise Rules
Visualizing Association Rules and Frequent Itemsets
Data Sets for "Applied Survival Analysis Using R""
A Collection of Statistical Tools for Biologists
Export R objects to several markup languages
Assign Random Colors to Unique Items in a Vector
Simulations for Adaptive Seamless Designs
Linkage Map Construction using the MSTmap Algorithm
Animal Social Network Inference and Permutations for Ecologists
A collection of functions for estimating centrographic
statistics and computational geometries for spatial point
patterns
Bayesian Inference on Causal Genetic Variants using Affected
Sib-Pairs Data
A General Framework for Multivariate Analysis with Optimal
Scaling
Augments the Use of 'Asreml' in Fitting Mixed Models
Readable Check Functions to Ensure Code Integrity
A Lightweight Core of the 'assertive' Package
Assertions to Check Properties of Strings
Assertions to Check Properties of Dates and Times
Assertions to Check Properties of Matrices
Assertions to Check Properties of Models
Assertions to Check Properties of Numbers
Assertions to Check Properties of Variables
Assertive Programming for R Analysis Pipelines
Optimal pricing of assets with fixed expiry date
A Suite of R Functions Implementing Spline Smoothing Techniques
Adaptive Subgroup Selection in Group Sequential Trials
Calculate the Assortativity Coefficient of Weighted and Binary
Networks
Statistical Tests for Genetic Association Studies
A Computational Tool for Astrochronology
Astronomy: time and position functions, misc. utilities
Applied Statistical Time Series Analysis
Average Shifted Visual Predictive Checks
Asymmetric Linkage Disequilibrium (ALD) for Polymorphic Genetic
Data
The Slide-Vector Model for Multidimensional Scaling of
Asymmetric Data
Regression Analysis of Sparse Asynchronous Longitudinal Data
Calculate Power Utilizing Asymptotic Likelihood Ratio Methods
Inference for Average Treatment Effects using Covariate
Balancing
A GTK GUI for teaching basic concepts in statistical inference,
and doing elementary bayesian tests
Automatically Tuned Markov Chain Monte Carlo
Acoustic Traveltime Calculations for 1-D Atmospheric Models
Support Querying Axibase Time-Series Database
Threshold independent performance measures for probabilistic
classifiers
Variable Selection with Random Forest and the Area Under the
Curve
Approximate Unconditional and Permutation Tests
Sparse Autoencoder for Automatic Learning of Representative
Features from Unlabeled Data
Display Multiple Images with Scaled Colors
Automated Hierarchical Multiple Regression with Assumptions
Checking
Partial Least Squares Regression with Backward Selection of
Predictors
Minimum Distance Estimation in Autoregressive Model
Performs Specification Search in Structural Equation Models
Automated Vector Autoregression Models and Networks
Calculation of Average Population Attributable Fractions and
Confidence Intervals
Client for the Amazon Alexa Web Information Services API
Class and Methods Definitions for Packages 'aws', 'adimpro',
'fmri' and 'dti'
Interface with Azure Machine Learning Datasets, Experiments and
Web Services
Adaptive differential evolution, b6e6rl variant
Bayesian Bacterial Growth Curve Analysis in R
Bayesian Bootstrap Predictive Mean Matching - Multiple and
Single Imputation for Discrete Data
Bubble Chart to Compare Biological Annotations by using DAVID
Modeling Framework for Cellular Communities in their
Environments
Bayesian Analysis of Computer Code Output (BACCO)
Bayesian Augmented Control for Clinical Trials
Reimplementations of Functions Introduced Since R-3.0.0
Learning Causal Cyclic Graphs from Unknown Shift Interventions
Exploring Portfolio-Based Conjectures About Financial
Instruments
Choice of the Hyperparameter Omega in the Bayesian Adjustment
for Confounding (BAC) Algorithm
Create Badges for 'Travis', 'Repostatus' 'Codecov.io' Etc in
Github Readme
Bayesian Average Error approach to Sample Size Determination
Ensemble bagging and boosting classifiers
Balanced and Spatially Balanced Sampling
Functions and Datasets for Books by Jeff Gill
Bayesian Meta-Analysis of Diagnostic Test Data
Analysis and Visualization of Macroevolutionary Dynamics on
Phylogenetic Trees
Functions for simple A/B split test and multi-armed bandit
analysis
Batch Effect Removal and Addon Normalization (in Phenotype
Prediction using Gene Data)
Bayesian Prediction of Stochastic Processes
Species Identification using DNA Barcodes
Bayesian Model Averaging using Bayesian Adaptive Sampling
Infrastructure for Computing with Basis Functions
Recovering a Basic Space from Issue Scales
Age-Specific Survival Analysis from Incomplete
Capture-Recapture/Recovery Data
Big Data Statistical Analysis for High-Dimensional Models
Batching Routines in Parallel and Passing Command-Line Arguments
to R
Statistical Experiments on Batch Computing Clusters
Consistent Batch Means Estimation of Monte Carlo Standard Errors
Convert Categorical Representations of Logicals to Actual
Logicals
An R Package for Data Reduction by Battery Reduction
Bayesian Feature Allocation Model for Tumor Heterogeneity
Bayesian Estimation of Mixtures of Multivariate Bernoulli
Distributions
Miscellaneous Functions for Bioinformatics and Bayesian
Statistics
An Implementation of Rubin's (1981) Bayesian Bootstrap
Power Calculations and Bayesian Analysis of Count Distributions
and FECRT Data using MCMC
Bayesian Analysis of Censored Regression Models Under Scale
Mixture of Skew Normal Distributions
Functions and Datasets for the book "Bayesian Data Analysis"
The Bayesian Dynamic Conditional Correlation GARCH Model
Graphical User Interface for bayesTFR, bayesLife and bayesPop
Computation of Bayes Factors for Common Designs
Bayesian Estimation of the GARCH(1,1) Model with Student-t
Innovations
Scalable Rejection Sampling for Bayesian Hierarchical Models
Bayesian Analysis of Generalized Elliptical Semi-Parametric
Models and Flexible Measurement Error Models
Bayesian Regression Model with Mixture of Two Scaled Inverse Chi
Square as Hyperprior
Bayesian Melding of GPS and DR Path for Animal Tracking
Bayesian Beta regression: joint mean and precision modeling
Designing Bayesian Multi-Arm Multi-Stage Studies
Mixtures-of-Experts Markov Chain Clustering and Dirichlet
Multinomial Clustering
Default Bayesian Hypothesis Tests for Correlation, Partial
Correlation, and Mediation
Bayesian Mixture Survival Models using Additive
Mixture-of-Weibull Hazards, with Lasso Shrinkage and
Stratification
BayesNI: Bayesian Testing Procedure for Noninferiority with
Binary Endpoints
Hierarchical Bayesian Model for a Hazard Function
Hierarchical Bayesian analysis of ecological count data
Bayesian Analysis of Small Area Estimation
Computation of Bayes factors for interrupted time-series designs
MCMC Sampling of Bayesian Linear Models via Summary Statistics
Bayesian Survival Regression with Flexible Error and Random
Effects Distributions
Bayesian thresholds mixed-effects models for categorical data
Bayes Factors, Model Choice and Variable Selection in Linear
Models
R Utilities Accompanying the Software Package BayesX
R Package Distribution of the BayesX C++ Sources
Bayesian analysis of haplotype association using Markov Chain
Monte Carlo
R Functions for Bayesian Hazard Rate Estimation
R Package for Baylor University Educational Psychology
Quantitative Courses
Bayesian Fitting of Ornstein-Uhlenbeck Models to Phylogenies
Bayesian Analysis of Significantly Mutated Genes in Cancer
On Bayesian analysis of Threshold autoregressive model (BAYSTAR)
Solving and Optimizing Large-Scale Nonlinear Systems
Bayesian bandwidth estimation and semi-metric selection for the
functional kernel regression with unknown error density
Bayesian bandwidth estimation for multivariate kernel regression
with Gaussian error
Bayesian Estimation of Incoherent Neutron Scattering Backgrounds
Miscellaneous Helper Functions for B. Bischl
Tools for General Maximum Likelihood Estimation
Gene Regulatory Network Inference with Bc3net
Bias-Corrected Bayesian Classification with Selected Features
Business Cycle Dating and Plotting Tools
Bayesian composition estimator: estimating sample (taxonomic)
composition from biomarker data
The Bayesian Causal Effect Estimation Algorithm
Bayesian Models for Cost-Effectiveness Analysis in the Presence
of Structural Zero Costs
Radiocarbon Dating, Age-Depth Modelling, Relative Sea Level Rate
Estimation, and Non-Parametric Phase Modelling
Bayesian Palaeoclimate Reconstruction from Pollen Data
Bayesian Hierarchical Clustering Using Spike and Slab Models
Bayesian Analysis of Change Point Problems
Behavioral change point analysis of animal movement
Bayesian Multiple Changepoint Detection Using Metadata
Advanced Analysis of B Cell Receptor Repertoire Data
Bayesian Continual Reassessment Method for Phase I
Dose-Escalation Trials
Cross-Validation for the SVD (Bi-Cross-Validation)
Bayesian Graph Selection Based on Birth-Death MCMC Approach
Optimisation of Bayesian Decision Problems
Inference and design for predictive values in binary diagnostic
tests
Remove Weekends and Holidays from ggplot2 Axes
Routines for Block Diagonal Symmetric matrices
Bayesian Inference for Discrete Weibull Regression
Analysis of Illumina BeadArray SNP data including MSV markers
Visualization via Beanplots (like Boxplot/Stripchart/Violin
Plot)
Bayesian Estimate of Age-specific Nest Survival Probabilities
Bayesian Analysis of Heterogeneous Treatment Effect
Quantifies effects of geo/eco distance on genetic
differentiation
Matrices Backed by Binary PED Files (PLINK)
Genomic Region Processing using Tools Such as BEDtools, BEDOPS
and Tabix
Easily Play Notification Sounds on any Platform
The Bee Swarm Plot, an Alternative to Stripchart
Download Historical Data from the Belgrade Stock Exchange
28 benchmark densities from Berlinet/Devroye (1994)
Benchmark and Frontier Analysis Using DEA and SFA
Benford Analysis for Data Validation and Forensic Analytics
Statistical Tests for Evaluating Conformity to Benford's Law
Bent-Cable Regression for Independent Data or Autoregressive
Time Series
Bayesian analysis for exponential random graph models
Function Collection Related to Plotting and Hydrology
Bessel -- Bessel Functions Computations and Approximations
Bayesian Estimation Supersedes the t-Test
Mini Games from Adventures of Beta and Bit
Detecting rare variants for quantitative traits using nuclear
families
Partitioning beta diversity into turnover and nestedness
components
Functions to incorporate taxonomic uncertainty on multivariate
analyses of ecological data
Simulation, estimation and forecasting of Beta-Skew-t-EGARCH
models
Bayesian Evaluation of Variant Involvement in Mendelian
Disorders
Breaks For Additive Season and Trend (BFAST)
Binary Generalized Extreme Value Additive Models
Bayesian Estimation in Generalized Linear Models
Example BGM Files for the Atlantis Ecosystem Model
Gaussian Mixture Modeling Algorithms And The Belief-based
Mixture Modeling
Markov Beta and Gamma Processes for Modeling Hazard Rates
Block Gibbs Sampler with Incomplete Multinomial Distribution
Useful Functions for Box, Hunter and Hunter II
Bias correction of the parameter estimates of the beta
regression model
Bibliometric and Co-Citation Analysis Tool
Reading Mass Spectrometric Search Results
Calculates the bidimensional regression between two 2D
configurations
Inferences for bi- and trifactorial trial designs
Tools for Survey Statistics in Educational Assessment
BLAS routines for native R matrices and big.matrix objects
Utilities for 'big.matrix' Objects from Package 'bigmemory'
Case-Control Analysis of Multi-Allelic Loci
Scalable Least-Angle Regression and Lasso
Big Lasso: Extending Lasso Model Fitting to Big Data in R
bounded memory linear and generalized linear models
Manage Massive Matrices with Shared Memory and Memory-Mapped
Files
A shared resource interface for Bigmemory Project packages
PCA, Transpose and Multicore Functionality for 'big.matrix'
Objects
Interface with Google BigQuery with Shiny Compatibility
Big Quadratic Inverse Covariance Estimation
Generalized Linear Models (GLM) for Large Data Sets
An Interface to Google's 'BigQuery' 'API'
Generalized Ridge Regression (with special advantage for p >> n
cases)
Table, Apply, and Split Functionality for Matrix and
'big.matrix' Objects
Top Scoring Pair based methods for classification
Dimension Reduction Methods for Multivariate Time Series
Power for SNP analyses using silver standard cases
Estimates Mixture Models for Case-Control Data
Variable Selection for Binary Data Using the EM Algorithm
Mean and Variance Modeling of Binary Data
Multi-Class Discriminant Analysis using Binary Predictors
Methods for Analyzing Binned Income Data
Evaluation and experimental design for binomial group testing
Asymptotic simultaneous confidence intervals for many-to-one
comparisons of proportions
Data Generation with Binary and Continuous Non-Normal Components
Simultaneous Generation of Multivariate Binary and Normal
Variates
Binomial Confidence Intervals For Several Parameterizations
'Taxonomic' Specification and Parsing Methods
Generates binomial random numbers via the coupling from the past
algorithm
Efficient MCMC for Binomial Logit Models
Confidence intervals and sample size determination for a
binomial proportion under simple random sampling and pooled
sampling
Performing diagnostics on binomial regression models
Concurrent Generation of Binary, Ordinal and Continuous Data
Cut Numeric Values into Evenly Distributed Groups
Exact Binary Sequential Designs and Analysis
Data Preprocessing, Binning for Classification and Regression
Feature Selection and Classification with the Embedded
Validation Procedures for Biomedical Data Analysis
Package for Community Ecology and Suitability Analysis
Multilevel Modeling of Dendroclimatical Fluctuations
Biodiversity Assessment Using Functional Tools
Process Biogas Data and Predict Biogas Production
Point Data Quality Assessment and Coordinate Conversion
BioGeography with Bayesian (and Likelihood) Evolutionary
Analysis in R Scripts
Simulation of Dynamic Microbial Inactivation
Predict environmental conditions from biological observations
An interface package (beta) for the BIOM file format
Find Biomarkers in Two-Class Discrimination Problems
Functional Annotation and Biological Data Retrieval with R
Ensemble Platform for Species Distribution Modeling
Utilities for the BIOM (Biological Observation Matrix) Format
Visualization of Overlapping Results with Heatmap
Simulation of deterministic and stochastic biochemical reaction
networks using Petri Nets
Search and Download Papers from the bioRxiv Preprint Server
From BIOlogical Sequences to MultiDimensional Scaling
Tools for Electromyogram Signals (EMG) Analysis
Calculation of Freshwater Biotic Indices
Tools for Biometry and Applied Statistics in Agricultural
Science
Visualising Bipartite Networks and Calculating Some (Ecological)
Indices
Bootstrap on Classical Biplots and Clustering Disjoint Biplot
BIPOD (Bayesian Inference for Partially Observed diffusions)
Methods to Analyse Ring Re-Encounter Data
Tools to find bad commits with git bisect
Toolkit to Identify Candidate Synthetic Lethality
Bayesian Isotonic Regression with Bernstein Polynomials
A S3 Class for Vectors of 64bit Integers
Binarization and Trinarization of One-Dimensional Data
Bayesian Inference of Transmission Routes Using Genome Sequences
Estimating the Parameters of Some Bivariate Distributions
Sample size calculations for bivariate longitudinal data
Generation of Bivariate Uniform Data and Its Relation to
Bivariate Binary Data
Conduct Univariate and Bivariate Wavelet Analyses
Functions to compute the biweight mean vector and covariance &
correlation matrices
Business Days Calculations and Utilities
Black Box Optimization and Exploration of Parameter Space
Plots (Slightly Extended) Bland-Altman Plots
Calculate and Analyze Blau Status for Measuring Social Distance
Black-Litterman and Copula Opinion Pooling Frameworks
A New Link Function that Blends Two Specified Link Functions
Analyze biotic homogenization of landscapes
Data Exploration with Multiple Machine Learning Algorithms
Fitting block ERGM given the block structure on social networks
Binomial linear and linear-expit regression
Data Files and Functions Accompanying the Book "Bayesian Data
Analysis in Ecology using R, BUGS and Stan"
Coclustering Package for Binary, Categorical, Contingency and
Continuous Data-Sets
blockmatrix: Tools to solve algebraic systems with partitioned
matrices
Creates strings that show a text message in 8 by 8 block letters
An R package for Generalized and classical blockmodeling of
valued networks
Latent and Stochastic Block Model Estimation by a 'V-EM'
Algorithm
Randomization for block random clinical trials
Nested Block Designs for Unstructured Treatments
Block, Assign, and Diagnose Potential Interference in Randomized
Experiments
Statistical Comparisons with Distance-Function Based Permutation
Tests
Request Data from the U.S. Bureau of Labor Statistics API
An API Wrapper for the Bureau of Labor Statistics (BLS)
Benchmark dose analysis for dose-response data
Mediation analysis with missing data using bootstrap
Bayesian Sampling for Stick-Breaking Mixtures
The pseudo-likelihood method for pairwise binary markov networks
Bundle Methods for Regularized Risk Minimization Package
Bayesian Models for Rare Variant Association Analysis
Data Generator based on Bayesian Network Model
Bayesian Network Structure Learning, Parameter Learning and
Inference
Bagged k-Nearest Neighbors Survival Prediction
Bayesian Estimation for Normal Heteroscedastic Nonlinear
Regression Models
Ferguson-Klass Type Algorithm for Posterior Normalized Random
Measures
A Bayesian Nonparametric Algorithm for Time Series Clustering
Bayesian Non- and Semi-Parametric Model Fitting
Spatial Implementation of Bayesian Networks and Mapping
Bayesian Network Structure Learning from Data with Missing
Values
Bayesian Output Analysis Program (BOA) for MCMC
Board Games and Tools for Building Board Games
Profilling of Peripheral Blood Mononuclear Cells using CyTOF
Bacterium and Virus Analysis of Orthologous Groups (BOG) is a
Package for Identifying Differentially Regulated Genes in the
Light of Gene Functions
Interface to the Boilerpipe Java Library
Bayesian Optimal INterval (BOIN) Design for Single-Agent and
Drug- Combination Phase I Clinical Trials
Functions for Elementary Bayesian Inference
An Improved Multiple Testing Procedure for Controlling False
Discovery Rates
Construction, Simulation and Analysis of Boolean Networks
Boosted Multivariate Trees for Longitudinal Data
A modular framework to bag or boost any estimation procedure
Optimized GWAS cohort subset selection for resequencing studies
Bootstrap Functions (Originally by Angelo Canty for S)
Bootstrapped Confidence Intervals for (Negative) Likelihood
Ratio Tests
Bootstrap Methods for Various Network Estimation Routines
Bootstrap Prediction Intervals and Bias-Corrected Forecasting
Bootstrapped Response and Correlation Functions
A bootstrap test for the probability of ruin in the classical
risk process
Bootstrap Subsamplings of Sparse Partial Least Squares -
Discriminant Analysis for Classification and Signature
Identification
Functions for the Book "An Introduction to the Bootstrap"
Fast, Exact Bootstrap Principal Component Analysis for High
Dimensional Data
Robust Performance Hypothesis Testing with the Sharpe Ratio
Bootstrap Tolerance Levels for Credit Scoring Validation
Statistics
Test Stationarity using Bootstrap Wavelet Packet Tests
Bayesian Ordination and Regression AnaLysis
Wrapper Algorithm for All Relevant Feature Selection
a Bunch of Structure and Sequence Analysis
Analytic Solutions for (ground-water) Boussinesq Equation
Downloads Box Office Information for Given Dates (How Much Each
Movie Earned in Theaters)
Double Box Plot for Two-Axes Correlation
Biplot of Multivariate Data Based on Principal Components
Analysis
Beta Product Confidence Procedure for Right Censored Data
bPeaks: an intuitive peak-calling strategy to detect
transcription factor binding sites from ChIP-seq data in small
eukaryotic genomes
Bayesian Phylogeographic and Ecological Clustering
Visualize Combined Action Response Surfaces and Report BRAID
Analyses
Fitting Dose Response with the BRAID Combined Action Model
Helper functions to misc3d and rgl packages for brain imaging
Basic wavelet analysis of multivariate time series with a
visualisation and parametrisation using graph theory
Simulation and Estimation for Branching Processes
Bootstrapped Robustness Assessment for Qualitative Comparative
Analysis
Species Richness Estimation and Modeling
An R Package for Multiple Break-Point Detection via the
Cross-Entropy Method
Templating Framework for Report Generation
Extracting Usable Data from the Grad Cafe Results Search
Bias reduction in binomial-response generalized linear models
Brier score decomposition of probabilistic forecasts for binary
events
An Implementation of the Bridge Distribution with Logit-Link as
in Wang and Louis (2003)
Bayesian Regularization for Feed-Forward Neural Networks
Convert Statistical Analysis Objects into Tidy Data Frames
A Compression Format Optimized for the Web
Bayesian Inference on the Ratio of Two Poisson Rates
Interface to the 'OpenBUGS' MCMC Software
Statistical methods for safety assessment in agricultural field
trials
Bayesian State-Space Models for Animal Movement
Bayesian Survival Model with Lasso Shrinkage Using Generalized
Weibull Regression
Nonparametric Smoothing of the Hazard Function
Bayes Screening and Model Discrimination
bspmma: Bayesian Semiparametric Models for Meta-Analysis
Asymptotic Covariance Matrices of Some BSS Mixing and Unmixing
Matrix Estimates
Birnbaum-Saunders Model Based on Skew-Normal Distribution
Temporal Exponential Random Graph Models by Bootstrapped
Pseudolikelihood
Estimates univariate function via Bayesian trend filtering
Modelling Heterogeneity in Paired Comparison Data
Training and Analysing Asynchronous Boolean Models
Buckley-James Regression for Survival Data with High-Dimensional
Covariates
Analyze Bunching in a Kink or Notch Setting
Markov model for bursty behavior in streams
Bayesian Analysis of a Vector Autoregressive Model with
Stochastic Volatility and Time-Varying Parameters
A Simple alternative to proportional Venn diagrams
The Stark-Parker algorithm for bounded-variable least squares
Solvers for Boundary Value Problems of Differential Equations
Bayesian Variant Selection: Bayesian Model Uncertainty
Techniques for Genetic Association Studies
Baumgartner Weiss Schindler Test of Equal Distributions
Extended Inference for Lasso and Elastic-Net Regularized Cox and
Generalized Linear Models
Infering large-scale gene networks with C3NET
C5.0 Decision Trees and Rule-Based Models
Simple, Multiple and Joint Correspondence Analysis
Bootstrap Confidence Regions for Correspondence Analysis
Classification Accuracy and Consistency under Item Response
Theory
Conditional Density Estimation Network Construction and
Evaluation
This package performs the CADF unit root test proposed in Hansen
(1995)
Conditional Akaike information criterion for lme4
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
Calculations for All Common Subsequences
Multiple imputation using MICE and Random Forest
Automated Parameter Estimation for Complex (Ecological) Models
Calibration of Scatterplot and Biplot Axes
Weighting and Estimation for Panel Data with Non-Response
Bayesian calibration of complex computer codes
Improved Allele-Specific Copy Number of SNP Microarrays for
Downstream Segmentation
Finite Mixture Models and Meta-Analysis Tools - Based on C.A.MAN
Camera Trap Data Management and Preparation of Occupancy and
Spatial Capture-Recapture Analyses
Estimation of Temporal Ordering of Cancer Abnormalities
Visualizing Generalized Canonical Discriminant and Canonical
Correlation Analysis
Accessing Intra-Tumor Heterogeneity and Tracking Longitudinal
and Spatial Clonal Evolutionary History by Next-Generation
Sequencing
Directly Extracts Complete CANSIM Data Tables
Combined Analysis of Pleiotropy and Epistasis
Comparative Analyses of Phylogenetics and Evolution in R
Numbers Figures and Creates Simple Captions
CAlibrating Penalities Using Slope HEuristics
Estimates population size from non-invasive sampling
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
Estimation of the Number of Fatalities from Carcass Searches
Identification of Cardinal Dates in Ecological Time Series
Cardiovascular Safety Exposure-Response Modeling in Early-Phase
Clinical Studies
High-Dimensional Regression and CAR Score Variable Selection
Statistical package for population size estimation in
capture-recapture models
Estimation of caribou abundance based on large scale
aggregations monitored by radio telemetry
Functions for Statistics Classes at Carleton College
Ecological Quality Ratios Calculation and Plot
A Collection of Database, Data Structure, Visualization, and
Utility Functions for R
Build Common Tables of Summary Statistics for Reports
CRISPR AnalyzeR for Pooled CRISPR Screens
Reparameterized and marginalized posterior sampling for
conditional autoregressive models, OpenCL implementation
Censored Autoregressive Model with Exogenous Covariates
Identify Similar Cases for Qualitative Case Studies
Analysis of categorical-variable datasets with missing values
Categorical Data Analysis Program Package
Fishery Stock Assessment by Generalized Depletion Models
High Dimensional Factor Analysis and Confounder Adjusted Testing
and Estimation
Community Assembly by Traits: Individuals and Beyond
An R Package for Simulating IRT-Based Computerized Adaptive
Tests
Tools: moving window statistics, GIF, Base64, ROC AUC, etc
Procedures to Generate Patterns under Computerized Adaptive
Testing
Special models for categorical variables
Tools for Estimating Causal Dose Response Functions
Deriving Expressions of Joint Interventional Distributions and
Transport Formulas in Causal Models
Methods for Estimating Causal Effects from Observational Data
Estimation of Causal Effects with Generalized Additive Models
Selection Bias Approach to Sensitivity Analysis for Causal
Effects
Analysis utilities for binary classification and Causata users
Statistics Netherlands (CBS) Open Data API Client
Bayesian Canonical Correlation Analysis and Group Factor
Analysis
(Robust) Canonical Correlation Analysis via Projection Pursuit
Concordance Correlation Coefficient for Repeated (and
Non-Repeated) Measures
Combined Cluster and Discriminant Analysis
CCDr Algorithm for Learning Sparse Gaussian Bayesian Networks
Cox Model for Case-Cohort Data with Stratified
Subcohort-Selection
Convex Clustering Methods and Clustering Indexes
Simulate Congruence Class Model for Networks
Significance Tests for Canonical Correlation Analysis (CCA)
One and two locus GWAS of binary phenotype with
case-control-population design
Cultural Consensus Theory applications to data
Coupled-Dipole Approximation for Electromagnetic Scattering by
Three-Dimensional Clusters of Sub-Wavelength Particles
Retrieve U.S. Flu Season Data from the CDC FluView Portal
Conditional Distance Correlation and Its Related Feature
Screening Method
Evaluate Differentially Private Algorithms for Publishing
Cumulative Distribution Functions
Quantile Regression for Random Variables on the Unit Interval
Coordinate Descent Algorithms for Lasso Penalized L1, L2, and
Logistic Regression
Tools to Download and Work with USDA Cropscape Data
Components of Canadian Monetary and Credit Aggregates
Phylogenetically Classifies Retention Mechanisms of Duplicate
Genes from Gene Expression Data
Constrained Dual Scaling for Detecting Response Styles
Statistical Inference of C- And D-Vine Copulas
Benchmark for the CEC 2005 Special Session on Real-Parameter
Optimization
Benchmark functions for the Special Session and Competition on
Real-Parameter Single Objective Optimization at CEC-2013
Collection of Common Astronomical Conversion Routines and
Functions
Translate Spreadsheet Cell Ranges to Rows and Columns
Functions to fit cell volume distributions and thereby estimate
cell growth rates and division times
Censored Linear Mixture Regression Models
Fits Normal and Student-t Censored Regression Model
Cross-Entropy R Package for Optimization
Discriminant Analysis of Time Series in the Presence of
Within-Group Spectral Variability
Context Driven Exploratory Projection Pursuit
Outlier Detection Using the Iterated RMCD Method of Cerioli
(2010)
Covariance Estimation Regularized by Nuclear Norm Penalties
Cause-Specific Framework for Competing-Risk Analysis
Estimate quantiles using any order Cornish-Fisher expansion
Canadian Forest Fire Danger Rating System
Compare Groups, Analytically and Graphically
Calculate AUC-type measure when gold standard is continuous and
the corresponding optimal linear combination of variables with
respect to it
R-Based API for Accessing the MSKCC Cancer Genomics Data Server
(CGDS)
Microarray CGH analysis using the Smith-Waterman algorithm
Detecting hot spot on CGH array data with fused lasso
regression
Segmentation Methods for Array CGH Analysis
Statistical Methods and Models for Claims Reserving in General
Insurance
Methods for Nonparametric Changepoint Detection
Change Point Estimation for Clustered Signals
Markov Model for the Online Multi-Channel Attribution Problem
Shiny Web Application for the Multichannel Attribution Problem
Charge Transfer Rates and Charge Carrier Mobilities
Install Packages from Snapshots on the Checkpoint Server for
Reproducibility
Analysis and Visualisation of Ecological Communities
Calibration Functions for Analytical Chemistry
Multivariate Statistical Analysis in Chemometrics
Chemometrics with R - Multivariate Data Analysis in the Natural
Sciences and Life Sciences
Multiple Testing Methods for Exploratory Research
Closest History Flow Field Forecasting for Bivariate Time Series
Calculation of standard deviation scores adduced from different
growth standards
Statistical Methods for Phenology Analysis in Temperate Fruit
Trees
Toolkit of Helper Functions to Pre-Process Amplification Data
Nonparametric Methods for Identifying Differential Enrichment
Regions with ChIP-Seq Data
Chemical Thermodynamics and Activity Diagrams
Simplify the Creation of Choropleth Maps in R
Contains an Administrative-Level-1 Map of the World
Contains maps used by the choroplethr package
Interface to Chromosome Counts Database API
Analysis of chromosomal interactions data (correction,
segmentation and comparison)
Chronological Objects which can Handle Dates and Times
Chunkwise Text-File Processing for 'dplyr'
Generative Models for Complex Networks with Conditionally
Independent Dyadic Structure
Weighted summary of cumulative incidence functions
Co-Information based N-Order Epistasis Detector and Visualizer
Statistical Analysis of Circular Data using Nonnegative
Trigonometric Sums (NNTS) Models
Detection of Outliers in Circular-Circular Regression
Circular Statistics, from "Topics in circular Statistics" (2001)
CIT Breast Cancer Molecular SubTypes Prediction
CIT Colon Cancer Molecular SubTypes Prediction
An RStudio Addin to Insert BibTex Citation in Rmarkdown
Documents
RStudio Add-in to Insert Markdown Citations
Visualization of structure and contents of a database
Client for the Comprehensive Knowledge Archive Network ('CKAN')
'API'
Optimal and Fast Univariate k-Means Clustering
C++ implementations of phylogenetic cladogenesis calculations
Time Series Modeling for Climate Change Proxies
Construct Graphs of S4 Class Hierarchies
Explore classification models in high dimensions
Classification Accuracy and Consistency under IRT models
Robust multivariate classification using highly optimised SVM
ensembles
Cleaning Geometries from Spatial Objects
Simultaneous Variables Clustering and Regression
Model-Based Clustering of Categorical Sequences
Analyzes Clickstreams Based on Markov Chains
Easily Download and Visualise Climate Data from CliFlo
Censoring Data and Likelihood-Based Correlation Estimation
Climate Classification According to Several Indices
Constrained L1-minimization for Inverse (covariance) Matrix
Estimation
Statistical Methods for Climate Sciences
Clinical Trial Design and Data Analysis Functions
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
Lasso Estimation of Conditional Logistic Regression Models
Central Limit Theorem Experiments (Theoretical and Simulation)
Cluster-Robust (Sandwich) Variance Estimators with Small-Sample
Corrections
Clustering Method Based on Local Shrinking
Clustering and Visualization of Mixed-Type Data
Wilcoxon Rank Sum Test for Clustered Data
"Finding Groups in Data": Cluster Analysis Extended Rousseeuw et
al.
Location and Visualization of Clustered Somatic Mutations
Explore clustering interactively using R and GGobi
Random Cluster Generation (with Specified Degree of Separation)
Identifying clusters in genomics data by recursive partitioning
Optimal Distance-Based Clustering for Multidimensional Data with
Sequential Constraint
Integrative Clustering for Heterogeneous Biomedical Datasets
Power calculations for cluster-randomized and cluster-randomized
crossover trials
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
Clustering of Observations with Geographical Constraints
k-Prototypes Clustering for Mixed Variable-Type Data
Variable Selection in Clustering by Mixture Models for Discrete
Data
Methods for joint dimension reduction and clustering
Clustering of Variables Around Latent Variables
Variable Selection for Model-Based Clustering
Covariance Matrix Adapting Evolutionary Strategy
Covariance Matrix Adaptation Evolution Strategy
Computational Methods for Numerical Analysis
Control Charts for Conway-Maxwell-Poisson Distribution
Subdistribution Analysis of Competing Risks
Analysis of Competing Risks Using Quantile Regressions
Misc Functions of the Center for the Mathematical Research
The Complex Multivariate Gaussian Distribution
A Package for Coincidence Analysis (CNA)
Canonical Non-Symmetrical Correspondence Analysis in R
Maximum Likelihood Estimation of a Log-Concave Density Function
Pre-process DNA Copy Number (CN) Data for Detection of CN Events
Association Analysis of CNV Data and Imputed SNPs
Example data sets for association analysis of CNV data
A Collection of Functions to Help with Analysis of Coarsely
Observed Data
COnstrained B-Splines (Sparse Matrix Based)
COmbat CO-Normalization Using conTrols (COCONUT)
Extracts Shared Variation in Collections of Datasets Using
Regression Models
Statistical Comparisons of Two or more Alpha Coefficients
Output Analysis and Diagnostics for MCMC
Markov chain Monte Carlo burn-in based on "bridge" statistics
Automated C Code Generation for Use with the 'deSolve' and
'bvpSolve' Packages
Alternative Factor Coding Matrices for Linear Model Formulae
Robust Coefficient Alpha and Omega with Missing and Non-Normal
Data
Species coexistence modeling and analysis
Conditional Inference Procedures in a Permutation Test Framework
Simultaneous Confidence Interval for Multinomial Proportion
Consistent Monitoring of Stationarity and Cointegrating
Relationships
Parameter Estimation and Inference in a Cointegrating Regression
Collocation Inference for Dynamic Systems
Auxiliary Package for Package 'CollapsABEL'
Colocalisation tests of two genetic traits
Implementation of Colored Independent Component Analysis and
Spatial Colored Independent Component Analysis
Plot and add custom coloring to Venn diagrams for 2-dimensional,
3-dimensional and 4-dimensional data
Color Calculations with Emphasis on Spectral Data
Tools for colors in a Hue-Saturation-Value (HSV) color model
A Colour Picker Widget for Shiny Apps, RStudio, R-markdown, and
'htmlwidgets'
Synergy/Antagonism Analyses of Drug Combinations
Estimation of Optimal Portfolio Weights by Combining Simple
Portfolio Strategies
Construction Methods of some Series of PBIB Designs
Exact Test from the Combinations of Mutually Exclusive
Alterations (CoMEt) Algorithm
Computational Methods for Immune Cell-Type Subsets
Print Nicely Formatted Comments for Use in Script Files
Bindings to the CommonMark Reference Implementation
Extract and plot common trends from a cointegration system.
Calculate P-value for Johansen Statistics
Comparative Phylogeographic Analysis using the Community Tree
Framework
Creates empty plots with compact axis notation
Compare Two Correlated C Indices with Right-censored Survival
Outcome
Interface to Diverse Estimation Methods of Causal Networks
Do a Git Style Diff of the Rows Between Two Dataframes with
Similar Structure
comparison of medical forms in CDISC ODM format
Correct for Verification Bias in Diagnostic Accuracy & Agreement
Multivariate likelihood ratio calculation and evaluation
Event-specific incidence rates for competing risks data
Tools for Retrieval and Storage of Functional Genomics Data
Conway-Maxwell-Poisson GLM and distribution functions
Numerically Evaluate Integrals and Derivatives (also Higher
Order) of Vector- And Complex-Valued Functions
Robust Linear Regression with Compositional Data as Covariates
Regression Estimation Based on the Compound Covariate Method
Under the Cox Proportional Hazard Model
Distribution function of quadratic forms in normal variables
Composite-Likelihood Based Analysis of Random Fields
Human-Friendly Text from Unknown Strings
Optimisation with Continuous Convex Piecewise (Linear and
Quadratic) Functions
Approximate conditional inference for logistic and loglinear
models
Parameter estimation in conditional GEE for recurrent event gap
times
Conditional Density Estimation with Neural Network Conditional
Mixtures
Condition Number Regularized Covariance Estimation
Estimation of the Conditional Survival Function for Ordered
Multivariate Failure Time Data
Conditional Visualization for Statistical Models
Primal or Dual Cone Projections with Routines for Constrained
Regression
Confidence Estimation of Environmental State Classifications
Manage Environment Specific Configuration Values
Conformal Prediction for Regression and Classification
Configural Frequencies Analysis Using Log-Linear Modeling
Algorithms for Fitting Circles, Ellipses and Conics Based on the
Work by Prof. Nikolai Chernov
A package to check the cancellation axioms of conjoint
measurement
A Tool for Reproducible Research by Converting 'LaTeX' Files
Generated by R Sweave to Rich Text Format Files
Tools for working with connectivity matrices
Conover-Iman Test of Multiple Comparisons Using Rank Sums
Partial Linear Least-Squares Regression using Constrained
Splines
Compute the Median Ranking(s) According to the Kemeny's
Axiomatic Approach
Constrained, Covariance-Matching Constrained and Universal Point
or Block Kriging
Model-Based Clustering and Classification with the Multivariate
Contaminated Normal Distribution
Contouring of Non-Regular Three-Dimensional Data
Median Comparison for Two-Sample Right-Censored Survival Data
Quantifies and assesses the significance of convergent evolution
Income Concentration Analysis with Complex Survey Samples
Probabilistic Species Co-Occurrence Analysis in R
Co-Operation: Fast Covariance, Correlation, and Cosine
Similarity Operations
Cooperative aspects of optimal trees in weighted graphs
General Bivariate Copula Theory and Many Utility Functions
Fitting the copCAR Regression Model for Discrete Areal Data
Coverage Probability Excursion (CoPE) Sets
Copula Based Bivariate Beta-Binomial Model for Diagnostic Test
Accuracy Studies
Estimation of Distribution Algorithms Based on Copulas
Estimation and Statistical Process Control Under Copula-Based
Time Series Models
Bivariate Copula Based Regression Models
Copula Mixed Effect Models for Bivariate and Trivariate
Meta-Analysis of Diagnostic Test Accuracy Studies
Computing Statistical Indices to Detect Answer Copying on
Multiple-Choice Tests
Baseline Correction for Copy Number Data from Cancer Samples
Collection of Rudimentary Bioinformatics Tools
Generate correlated count random variables
Community Estimation in G-Models via CORD
Classification, Regression and Feature Evaluation
Core Functionality for Simulating Quantities of Interest from
Generalised Linear Models
TDT for compound heterozygous and recessive models
The Clustering of Regression Models Method
Efficient Estimation of Covariance and (Partial) Correlation
Statistics and data sets for corpus frequency data
Implementation of 2D Correlation Analysis
Nonparametrics with Clustered Binary and Multinomial Data
Correct Overloaded Peaks from GC-APCI-MS Data
Linear Regression Based on Linear Structure Between Covariates
Functions and Methods for Correspondence Regression
A collection of functions for graphing correlation matrices
Estimate Correlations Between Repeatedly Measured Endpoints
(E.g., Reliability) Based on Linear Mixed-Effects Models
Modeling Correlational Magnitude Transformations in
Discretization Contexts
Tools for processing data after a Genome Wide Association Study
Tools for estimating and predicting the cosinor model
Functions for cosmological distances, times, luminosities, etc
Photometric redshift estimation using generalized linear models
Fit Regularized Nonparametric Regression Models Using COSSO
Penalty
Connect to and Work with CouchDB Databases
Flexible Univariate and Bivariate Count Process Probability
Mean and Variance Modeling of Count Data
Convert from UTC to Local Time for United States Counties
A Residue-Residue Contact Detecting Method
Local Polynomial Regression of State Dependent Covariates in
State-Space Models
Brownian Motion Processes for 'nlme'-Models
Latent Class Models with Covariate Effects on Underlying and
Measured Variables
A simultaneous regression model for the mean and covariance
Robust Covariance Estimation via Nearest Neighbor Cleaning
Model-Free Covariate Selection in High Dimensions
Tests for Determining if the Covariance Structure of
2-Dimensional Data is Separable
Computes covariance test for adaptive linear modelling
Streamlined Plot Theme and Plot Annotations for 'ggplot2'
Messages, Warnings, Strings with Ascii Animals
Cox models by likelihood based boosting for a single survival
endpoint or competing risks
Cox-Type Models for Interval-Censored Data
Cox Regression (Proportional Hazards Model) with Multiple Causes
and Mixed Effects
Confirmatory Path Analysis through the d-sep tests
Methods to perform Common Principal Component Analysis (CPCA)
Concordance Probability Estimates in Survival Analysis
Association Between Methylation and a Phenotype of Interest
Parallelized Genomic Prediction and GWAS
CpG Filtering Method Based on Intra-class Correlation
Coefficients
Find the maximum likelihood estimator of the shape constrained
hazard baseline and the effect parameters in the Cox
proportional hazards model
Sequential and Batch Change Detection Using Parametric and
Nonparametric Methods
Correction of the pvalue after multiple coding
Conditional probability function of a competing event
Quantile, Composite Quantile Regression and Regularized Versions
Conditional Maximum Likelihood for Quadratic Exponential Models
for Binary Panel Data
Power Calculation for Weighted Log-Rank Tests in Cure Rate
Models
Probabilistic damage tolerance analysis for fatigue cracking of
metallic aerospace structures
Multivariate nonparametric Cramer-Test for the
two-sample-problem
Download Logs from the 'RStudio' 'CRAN' Mirror
Fit Continuous-Time Correlated Random Walk Models to Animal
Movement Data
Categorical Randomized Block Data Analysis
Censored Regression with Conditional Heteroscedasticity
Functions for calculating the CreditMetrics risk model
Analyze Cricketers Based on ESPN Cricinfo Statsguru
Group-Based Modelling of Longitudinal Data
Statistical Methods for Crime Series Linkage
Continual Reassessment Method (CRM) for Phase I Clinical Trials
CCMN and other noRMalizatioN methods for metabolomics data
Object-Oriented Implementation of CRM Designs
Downloads and Builds datasets for Climate Reference Network
A Partial Clustering Algorithm with Automatic Estimation of the
Number of Clusters and Identification of Outliers
Analysis and Search of Crossover Designs
Confidence intervals for crossover points of two simple
regression lines
Cross-Recurrence Quantification Analysis for Categorical and
Continuous Time-Series
Penalized Variable Selection in Competing Risks Regression
Competing risks regression for Stratified and Clustered data
Stepwise Covariate Selection for the Fine & Gray Competing Risks
Regression Model
Nonlinear Regression Parameters Estimation by 'CRS4HC' and
'CRS4HCe'
Doubly Robust Inverse Probability Weighted Augmented GEE
Estimator
Sample Size Estimation Functions for Cluster Randomized Trials
Interface to Climatic Research Unit Time-Series Version 3.21
Data
Identifying cryptic relatedness in genetic association studies
Statistical Tests for Cryptographic Randomness
Functions for Conditional Simulation in Regression-Scale Models
Covariate-adjusted Skewed Functional Model (cSFM)
Correlates of State Policy Data Set in R
Methods to Test Hypotheses on the Distribution of Spatial Point
Processes
csSAM - cell-specific Significance Analysis of Microarrays
Substantive significance testing for regression estimates and
marginal effects
Import and Export CSV Data with a YAML Metadata Header
A Text Mining Toolkit for Chinese Document
Estimating the Parameters of a Continuous-Time Markov Chain from
Discrete-Time Data
Modeling Animal Movement with Continuous-Time Discrete-Space
Markov Chains
Censored and Truncated Quantile Regression
Continuous Time Structural Equation Modelling
A Class of Mixture Models for Ordinal Data
Rule- and Instance-Based Regression Modeling
CUDA Parallel Implementation of a Bayesian Multilevel Model for
fMRI Data Analysis
Data sets for the examples used in the package "cudaBayesreg"
Charles's Utility Function using Formula
Analyze Multivariate Phenotypes by Combining Univariate results
Extends ddply to allow calculation of cumulative quantities
Change point detection in genomic sequences
Tools to Transform 'cURL' Command-Line Calls to 'httr' Requests
The package will formally test two curves represented by
discrete data sets to be statistically equal or not when the
errors of the two curves were assumed either equal or not using
the tube formula to calculate the tail probabilities
Cusp-Catastrophe Model Fitting Using Maximum Likelihood
Customized Training for Lasso and Elastic-Net Regularized
Generalized Linear Models
Compute Decision Interval and Average Run Length for CUSUM
Charts
CUTOFF: A Spatio-temporal Imputation Method
An R package to perform LPUE standardization and stock
assessment of the English Channel cuttlefish stock using a
two-stage biomass model
Cross-Validated Area Under the ROC Curve Confidence Intervals
Estimation of the Calibration Equation with Error-in
Observations
Penalized Logistic Regression Model using Majorization
Minimization by Coordinate Descent (MMCD) Algorithm
Calculate the predictive squared correlation coefficient
Fast Cross-Validation via Sequential Testing
Cross-validation tools for regression models
Regularized Estimators of Covariance Matrices with CV Tuning
Miscellaneous Functions for Math, Plotting, Printing,
Statistics, Strings, and Tools
extend cxxfunction by saving the dynamic shared objects
Cyclic Coordinate Descent for Logistic, Poisson and Survival
Analysis
Query 'Team Cymru' 'IP' Address, Autonomous System Number
('ASN'), Border Gateway Protocol ('BGP'), Bogon and 'Malware'
Hash Data Services
Cycle and Phase Identification for mastication data
Agent-Based Model for Taenia_solium Transmission and Control
Predicting Causal Direction from Dependency Features
Interactive Heat Maps Using 'htmlwidgets' and 'D3.js'
Tools for creating D3 JavaScript network, tree, dendrogram, and
Sankey graphs from R
Data Analysis and Graphics Data and Functions
Data Sets and Functions, for Demonstrations with Expression
Arrays and Gene Sequences
Data Sets and Functions, supplementary to DAAG
Three-Way Data Analysis Through Densities
Functions Useful in the Design and ANOVA of Experiments
Design and Analysis of Experiments with R
Learning directed acyclic graphs (DAGs) through bootstrap
aggregating
Graphical Analysis of Structural Causal Models
Diagnostic accuracy of classification models
Dynamical Assembly of Islands by Speciation, Immigration and
Extinction
DALY Calculator - A GUI for stochastic DALY calculation in R
Dynamic Assembly Model of Colonization, Local Extinction and
Speciation
Dams in the United States from the National Inventory of Dams
(NID)
Dandelion Plot for R-Mode Exploratory Factor Analysis
Package for Deep Architectures and Restricted Boltzmann Machines
Statistical Tools to Analyze Your Darts Game
Interactive Data Visualization with D3.js
File-Based Access to Large Matrices Stored on HDD in Binary
Format
Tools for Easily Combining and Cleaning Data Sets
Divide and Recombine for Large, Complex Data
dataframes2xls writes data frames to xls files
Estimating Finite State Machine Models from Data
A system for mapping foreign objects to R variables and
environments
Easily Source Publicly Available Data on Derivatives
A Flexible Container to Transport and Manipulate Data and
Associated Resources
Performs variable level data quality checks and generates
summary statistics
Retrieval Functions for USGS and EPA Hydrologic and Water
Quality Data
An Implementation of a SAS-Style Data Step
General Purpose Hierarchical Data Structure
Support functions for packages VBmix, semisupKernelPCA, and
patchPlot
Data and Workspace Browser for Terminals
Deconvolution Analysis Tool for Dynamic Contrast Enhanced MRI
Functions for "Data Analysis in Vegetation Ecology"
Discriminant Analysis with Additional Information
Discrete Bayesian Additive Regression Trees Sampler
Provides a graphical user interface to connect with databases
that use MySQL
Goodness-of-fit and two sample comparison tests using sample
entropy
Detecting Breakpoints and Estimating Segments in Trend
methods of distance-based gene set functional enrichment
analysis
'DBHYDRO' Hydrologic and Water Quality Data
Discrete Beta Kernel Graduation of Mortality Data
Compute the NPMLE of distribution from doubly censored data
Distance-Based Measures of Spatial Structures
Density Based Clustering of Applications with Noise (DBSCAN) and
Related Algorithms
Analyzing Dichotomous Choice Contingent Valuation Data
A Package for Image Analysis of DCE-MRI (S4 Implementation)
Data Cloud Geometry (DCG): Using Random Walks to Find Community
Structure in Social Network Analysis
Differential Co-expression Analysis and Differential Regulation
Analysis of Gene Expression Microarray Data
Analysis of Ontologies and Protein Domain Annotations
Claims Reserving under the Double Chain Ladder Model
Data Cloning and MCMC Tools for Maximum Likelihood Methods
Functions for the Detection of Spatial Clusters of Diseases
Hierarchical Models Made Easy with Data Cloning
Attribute profile estimation using Diagnostic Classification
Models and MCMC
List Linear n-Peptide Constraints for Overlapping Protein
Regions
Distance Covariance and Correlation for Time Series Analysis
Conventional Cross-validation statistics for climate-growth
model
Depth-Based Classification and Calculation of Data Depth
Variance Stabilization by Data-Driven Haar-Fisz (for
Microarrays)
Analysis and Visualization of Droplet Digital PCR in R and on
the Web
Learning Bayesian Networks with Mixed Variables
Deconvolution density estimation with adaptive methods for a
variable prone to measurement error
DEComposition of Indirect and Direct Effects
Quantitative Support of Decision Making under Uncertainty
Differential Co-Expression and Differential Expression Analysis
Decode Coded Variables to Plain Text (and Vice Versa)
Deconvolution Estimation in Measurement Error Models
Identifies Signatures Present in a Tumor Sample
Additional dialogs and functions for Deducer
Deductive Correction, Deductive Imputation, and Deterministic
Correction
Data Correction and Imputation Using Deductive Methods
An Implementation of Deep Neural Network for Regression and
Classification
Dirichlet-multinomial Evolutionary Event Profile Randomization
(DEEPR) test
Integration of One-Dimensional Functions with Double Exponential
Formulas
Detection of differentially expressed genes
Models for Skewed Count Distributions Relevant to Networks
Statistical Functions for the Delaporte Distribution
Delaunay Triangulation and Dirichlet (Voronoi) Tessellation
Estimates Pseudotimes for Single Cell Expression Data
Estimation of Multivariate Densities Using Adaptive Partitions
Identification of dichotomous differential item functioning
(DIF) using Angoff's Delta Plot method
Functions to Calculate Relatedness on Diploid Genetic Data
Evaluating the genetic differentiation between populations based
on Gst and D values
Differential Expression from Multiple Indicators
Deming, Thiel-Sen and Passing-Bablock Regression
Forecasting mortality, fertility, migration and population data
Kernel Density Estimation for Demonstration Purposes
DEvelopment (of Multi-Linear QSPR/QSAR) MOdels VAlidated using
Test Set
Faster Dendrogram Manipulation using 'Rcpp'
Extra functions to cut, label and colour dendrogram clusters
Dendrogram seriation: ordering for visualisation
Modular Leaf Ordering Methods for Dendrogram Nodes
Parameter Estimates and Real-Time Prediction of a Single Dengue
Outbreak
Statistical Analyses of De Novo Genetic Variants
Visualization of Multivariate Functions, Sets, and Data
Clustering by Fast Search and Find of Density Peaks
Density.T.HoldOut: Non-combinatorial T-estimation Hold-Out for
density estimation
Dens-Based Method for Partial Correlation Estimation in Large
Scale Brain Networks
Density strips and other methods for compactly illustrating
distributions
Global Optimization by Differential Evolution
Differential Evolution Optimization in Pure R
Statistical Inference for Parametric and Semiparametric Models
Based on Dependently Truncated Data
Dependent Mixture Models - Hidden Markov Models of GLMs and
Other Distributions in S4
Depth functions tools for multivariate analysis
Statistical Depth Functions for Multivariate Analysis
Functions and R Code to Accompany Derivatives Markets
Seasonal Adjustment by Frequency Analysis
An Interface to the DescribeDisplay GGobi Plugin
Describe Data in R Using Common Descriptive Statistics
Optimal deseasonalization for geophysical time series using AR
fitting
Computational tool for designing genetical genomics experiments
Finding Optimal Block Designs for a Generalised Linear Mixed
Model
Construction of Optimally Matched Samples for Randomized
Experiments and Observational Studies that are Balanced and
Representative by Design
Desirability Functions for Ranking, Selecting, and Integrating
Data
Desirability Function Optimization and Ranking
Bagging with Distance-based Regression for Differential Gene
Expression Analyses
Solvers for Initial Value Problems of Differential Equations
(ODE, DAE, DDE)
Estimation of Diagonal Elements of Sparse Precision-Matrices
Plotting Field Plans for Agricultural Experiments
Analyzing Wildlife Data with Detection Error
Detect Data Containing Personally Identifiable Information
Implementation of the DetMCD Algorithm (Robust and Deterministic
Estimation of Location and Scatter)
Suite of Deterministic and Robust Algorithms for Linear
Regression
Start the detrendeR Graphical User Interface (GUI)
A computer program to detect markers responding to selection
Data sets from Devore's "Prob and Stat for Eng (7th ed)"
Tools to Make Developing R Packages Easier
Phase I/II Adaptive Dose-Finding Design for Combination Studies
Dose-finding by the continual reassessment method
Explore data.frames by plotting NA and classes of each variable
Differential Functioning of Items and Tests
Phase I/II Adaptive Dose-Finding Design for MTA
A Bayesian Dose-Finding Design using Pharmacokinetics(PK) for
Phase I Clinical Trials
Capture-Recapture Estimation using Bayesian Model Averaging
Differential Geometric LARS (dgLARS) method
Simulating Data for PLS Mode B Structural Models
Double Hierarchical Generalized Linear Models
Independence Testing via Hilbert Schmidt Independence Criterion
Block Diagonal Extraction or Replacement
Functions for visualising simple graphs (networks), plotting
flow diagrams
Create Graph Diagrams and Flowcharts Using R
Export DiagrammeR Graphviz Graphs as SVG
Diagnostic test summary measures for three ordinal groups
Calculate probabilities of various dice-rolling events
Construction and Evaluation of Metamodels
Kriging Methods for Computer Experiments
Kriging-Based Optimization for Computer Experiments
Plot methods for computer experiments design and surrogate
Dictionaries for reading microdata surveys from IBGE
A Simple Implementation and Demonstration of Gradient Boosting
Defines some physical constants and dielectric functions
commonly used in optics, plasmonics
R Interface to the ZEIT ONLINE Content API
Detection of Differential Item Functioning (DIF) in Rasch Models
by Boosting Techniques
Difference of Two Precision Matrices Estimation
Analyzing and Visualizing Differential Correlation Networks in
Biological Data
Calculates Confidence Intervals for two Dependent Proportions
Functions from the book Solving Differential Equations in R
Metrics of Difference for Comparing Pairs of Maps
Diffusion IRT Models for Response and Response Time Data
Display Differences Between Two Files using Codediff Library
Baseline identification and peak decomposition for x-ray
diffractograms
Inference and Analysis for Generalized Quadratic Diffusions
Inference and Analysis for Diffusion Processes via Data
Imputation and Method of Lines
Inference and Analysis for Jump Generalized Quadratic Diffusions
A Penalty Approach to Differential Item Functioning in Rasch
Models
Detection of Dichotomous Differential Item Functioning (DIF) by
Non-Linear Regression Function
Collection of Methods to Detect Dichotomous Differential Item
Functioning (DIF)
Item Focused Trees for the Identification of Items in
Differential Item Functioning
Create Compact Hash Digests of R Objects
An application programming interface for generating null models
of social contacts based on individuals' space use
Data-Informed Link Strength. Combine multiple-relationship
networks into a single weighted network. Impute (fill-in)
missing network links
DIME (Differential Identification using Mixture Ensemble)
DiNAMIC A Method To Analyze Recurrent DNA Copy Number
Aberrations in Tumors
Hartigan's Dip Test Statistic for Unimodality - Corrected
Bayesian Clustering of Multivariate Data Under the
Dirichlet-Process Prior
Direction Analysis for Pathways and Kinases
Discrete Laplace Mixture Inference using the EM Algorithm
DiscML: An R package for estimating evolutionary rates of
discrete characters using maximum likelihood
Coordinate-Descent Algorithm for Discrete Data
Multiple testing procedures for discrete test statistics
Create and Manipulate Discrete Random Variables
Discrete Weibull Distributions (Type 1 and 3)
Data preprocessing, discretization for classification
Discrimination of Alternative Reproductive Tactics (ARTs)
Tools of the Trade for Discriminant Analysis
Modelling Spatial Variation in Disease Risk for Areal Data
Calculate Dissimilarity Matrix for Dataset with Mixed Attributes
A Pipeline to Analyze Resistance and Tolerance from Drug Disk
Diffusion Assays
2D Hausdorff and Simplex Dispersion Orderings
Disparity Filter Algorithm for Weighted Networks
Create Disposable R Packages for Testing
Utilities for making pairwise comparisons of multivariate data
Distance Sampling Detection Function and Abundance Estimation
Calculates Study Size Required for Distance Sampling
DiSTATIS Three Way Metric Multidimensional Scaling
Computations over Distributed Data without Aggregation
Method Functions for Confidence Intervals and to Distill
Information from an Object
Object Oriented Implementation of Distributions
Documentation for 'distr' Family of R Packages
S4 classes for elliptically contoured distributions
Object Oriented Implementation of Probability Models
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'
Provides tools for quality checks of georeferenced plant species
accessions
Comparative Phylogenetic Analyses of Diversification
A Comprehensive, General Purpose Population Genetics Analysis
Package
Building Diversity Models from Multiple Species Occupancy Models
Functions for re-sampling a community matrix to compute
diversity indices at different sampling levels
Tools for Analysis of Diversity and Similarity in Biological
Systems
Nearest Neighbour Contingency Table Analysis
Distance Measure Based Judgment and Learning
Implementation of Differentiable Lasso Penalty in Linear Models
Bayesian and Likelihood Analysis of Dynamic Linear Models
Distributed-Lag Structural Equation Modelling with Second-Order
Polynomial Lag Shapes
Dynamic Modeling and Parameter Estimation in ODE Models
Delete or Merge Regressors for linear model selection
Functions and data for "Data Mining with R"
Tools for Analysing Forensic Genetic DNA Data
Integrative Analysis of Omics Data in Terms of Network,
Evolution and Ontology
Analysis of Discretely Observed Linear
Birth-and-Death(-and-Immigration) Markov Chains
Groupwise Statistics, LSmeans, Linear Contrasts, Utilities
Extract Data Tables and Comments from Microsoft Word Documents
Functions for Acceptance Sampling Ideas originated by H.F. Dodge
Full Factorials, Orthogonal Arrays and Base Utilities for DoE
Packages
Wrapper package for design of experiments functionality
Foreach Parallel Adaptor using the Future API of the 'future'
Package
ADI (Average Dominance Index), Social Network Graphs with Dual
Directions, and Music Notation Graph
R Console Bindings for the 'Domino Command-Line Client'
Foreach parallel adaptor for the Rmpi package
Foreach Parallel Adaptor for the 'parallel' Package
Foreach parallel adapter for the rredis package
Generic Reproducible Parallel Backend for foreach Loops
Planning and Analyzing Dose Finding Experiments
Foreach Parallel Adaptor for the 'snow' Package
Dot-and-Whisker Plots of Regression Results
Test against parametric regression function
Differential Exon Usage Test for RNA-Seq Data via Empirical
Bayes Shrinkage of the Dispersion Parameter
Local Linear Hazard Estimation with Do-Validated and
Cross-Validated Bandwidths
Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's
Book Measuring Market Risk
Dirichlet Process Mixture model simulation for clustering and
image segmentation
Data Pre-Processing and Visualization Functions for
Classification
Methods for Dimension Reduction for Regression
Data Representation: Bayesian Approach That's Sparse
Regularized Estimation of Dynamic Linear Regression in the
Presence of Autocorrelated Residuals (DREGAR)
Doubly Robust Generalized Estimating Equations
Discontinuous Regression and Image Processing
Regression and association models for repeated categorical data
Dual Empirical Likelihood Inference under Density Ratio Models
in the Presence of Multiple Samples
Analyze Drop Out of an Experiment or Survey
Dose-Response Modeling with Smoothing Splines
Implementation of a Machine Learning Framework for Predicting
Drugs Side Effects
Discretization-Based Direct Random Sample Generation
Bayesian subgroup analysis in clinical trials
Dynamic Systems Estimation (Time Series Package)
Density Surface Modelling of Distance Sampling Data
Spatial Modelling for Distance Sampling Data
Recursive Partitioning for Discrete-Time Survival Trees
Exploring Disease Similarity in Terms of Dysfunctional
Regulatory Mechanisms
A Wrapper of the JavaScript Library 'DataTables'
Simplifying Descriptive Frequencies and Statistics
Comparison of Binary Diagnostic Tests in a Paired Study Design
Analysis of Diffusion Weighted Imaging (DWI) Data
Dunnett-Tukey-Kramer Pairwise Multiple Comparison Test Adjusted
for Unequal Variances and Unequal Sample Sizes
Suite of functions related to discrete-time discrete-state
Markov Chains
Estimation and Comparison of Dynamic Treatment Regimes
Learning Algorithms for Dynamic Treatment Regimes
DTR Estimation and Inference via G-Estimation, Dynamic WOLS, and
Q-Learning
Time Series Clustering Along with Optimizations for the Dynamic
Time Warping Distance
Time-Weighted Dynamic Time Warping for Satellite Image Time
Series Analysis
Dual Scaling Analysis of Multiple Choice Data
Create dummy/indicator variables flexibly and efficiently
Automatic Creation of Dummies with Support for Predictive
Modeling
Software implementation of step-down and step-up Dunnett test
procedures
Dunn's Test of Multiple Comparisons Using Rank Sums
Bayesian inference from count data using discrete uniform priors
Discrete variations of a fractional Brownian motion
Analyze Dose-Volume Histograms and Check Constraints
Parametric Regression for Discrete Response
Interface to 'Dygraphs' Interactive Time Series Charting Library
Dynamically visualized probability distributions and their
moments
Methods for Detection of Clusters in Hierarchical Clustering
Dendrograms
Implementation of the Dynamic TOPMODEL Hydrological Model
Full Interactive GUI for Dynamic Biplot in R
Denoising and clustering for dynamical image sequence (2D or
3D)+T
Dynamic Nomograms for Linear, Generalized Linear and
Proportional Hazard Models
Companion Package to "Dynamic Prediction in Clinical Survival
Analysis"
Dynamic Simulations of Autoregressive Relationships
Methods for Estimating Dynamic Treatment Regimes
Misc Functions of the Department of Statistics, Probability
Theory Group (Formerly: E1071), TU Wien
Plots of the Empirical Attainment Function
Dynamic Web Analytics for the Energy Industry
Early Warning Signals Toolbox for Detecting Critical Transitions
in Timeseries
Efficient Approximate Bayesian Computation Sampling Schemes
Analysis of variance and other important complementary analyzes
Utility functions for working with mark-recapture data
Sample Size Estimation for Experimental Designs
Search and Retrieve Scientific Publication Records from Pubmed
Evaluation of stratified genome-wide association meta-analysis
results
Ensemble Forecast Verification for Large Data Sets
Entropy reweighting to create balanced samples
Empirical Bayes Thresholding and Related Methods
Empirical Bayes Estimation of Dynamic Bayesian Networks
Genotyping and SNP Detection using Next Generation Sequencing
Data
Empirical Bayesian Lasso and Elastic Net Methods for Generalized
Linear Models
Genotyping and SNP calling using single-sample next generation
sequencing data
Programmatic Access to the European Central Bank's Statistical
Data Warehouse (SDW)
Simulation from Endpoint-Conditioned Continuous Time Markov
Chains
Elliptic Distribution and Lambda Option Pricing Model
Functions for Spatial Point Pattern Analysis
Embedding Charts Generated with ECharts Library into Shiny
Applications
Efficient calculation of fine structure isotope patterns via
Fourier transforms of simplex-based elemental models
Dissimilarity-based functions for ecological analysis
Programmatic Interface to the API Serving UC Berkeley's Natural
History Data
Spatial Analysis of Phenotypic, Genotypic and Environmental Data
A community modeling foundation for Eco-Hydrology
"A practical guide to ecological modelling - using R as a
simulation platform"
General Analysis of Various Economics Demand Systems
Ecological Regression using Aggregate and Individual Data
Simulating Community Assembly and Ecological Diversification
Using Ecospace Frameworks
Procedures for Ecological Assessment of Surface Waters
Non-Parametric Multiple Change-Point Analysis of Multivariate
Data
Exploratory and Descriptive Event-Based Data Analysis
Read Data from European Data Format (EDF and EDF+) Files
More Powerful Unconditional Testing of Negative Binomial Means
for Digital Gene Expression Data
Network Reconstruction and Changepoint Detection
Simultaneous Edit-Imputation for Continuous Microdata
Parsing, Applying, and Manipulating Data Cleaning Rules
Estimation of the effective dimension reduction (EDR) space
Provides tools for dimension reduction methods
Exploring Election and Census Highly Informative Data Nationally
for Australia
Tools for analysis and classification of electroencephalography
(EEG) data
Read and Preprocess Fluorescence Excitation-Emission Matrix
(EEM) Data
Tools for Pre-Processing Emission-Excitation-Matrix (EEM)
Fluorescence Data
Convenience Functions for Education Data
Wavelet-Based Enhanced FDR for Signal Detection in Noisy Images
Effect Displays for Linear, Generalized Linear, and Other Models
Test changes of a grouped response relative to baseline
Visualization of Categorical Response Models
The Causal Effects for a Causal Loglinear Model
Hierarchical Modelling of Faecal Egg Counts
Tool for ego-centric measures in Social Network Analysis
Exploration and Graphics for RivEr Trends (EGRET)
Exploration and Graphics for RivEr Trends (EGRET) Confidence
Intervals
R Wrapper for the Energy Information Administration (EIA) API
Generates (dense) matrices that have a given set of eigenvalues
Semiparametric factor and regression models for symmetric
relational data
Computes confidence intervals for principal components
eiPack: Ecological Inference and Higher-Dimension Data
Management
An algorithm for reducing errors-in-variable bias in simple
linear regression
Ecological Inference with individual and aggregate data
Enhanced Least Absolute Shrinkage and Selection Operator
Regression Model
General Purpose Interface to 'Elasticsearch'
Elastic-Net for Sparse Estimation and Sparse PCA
Collection of functions for statistical election audits
Functions for election audits using stratified random samples
R Functions to Download and Clean Brazilian Electoral Data
Data Sets, Functions and Examples from the Book: "The Elements
of Statistical Learning, Data Mining, Inference, and
Prediction" by Trevor Hastie, Robert Tibshirani and Jerome
Friedman
Load Associated Press Election Results with Elex
Functions for drawing ellipses and ellipse-like confidence
regions
Implementation of ELM (Extreme Learning Machine ) algorithm for
SLFN ( Single Hidden Layer Feedforward Neural Networks )
Preference Rating for Visual Stimuli Based on Elo Ratings
Animal Dominance Hierarchies by Elo Rating
Empirical Likelihood Analysis for the Cox Model and
Yang-Prentice (2005) Model
Tools to Analyze the Thermal Reaction Norm of Embryo Growth
Evolutionary Monte Carlo (EMC) algorithm
EM Algorithm for Model-Based Clustering of Finite Mixture
Gaussian Distribution
Empirical Mode Decomposition and Hilbert Spectral Analysis
Support Functions and Data for "Ecological Models and Data"
Exponentially Modified Gaussian (EMG) Distribution
Evaluation of Modeling without Information Leakage
EM Algorithms for Estimating Item Response Theory Models
Estimation of Wastewater Emissions in Combined Sewer Systems
Contrasts in mixed effects for EMMIX model with random effects
The EM Algorithm and Skew Mixture Distribution
Fitting Unrestricted Multivariate Skew t Mixture Models
A Maximum Likelihood Approach to the Analysis of Modularity
Fitting Mixed Models with Known Covariance Structures
Eye Movement Analysis Package for Fixation and Saccade Detection
Expected Maximum Profit Classification Performance Measure
Routines for Performing Empirical Calibration of Observational
Study Estimates
Simulation-Based False Discovery Rate in RNA-Seq
Empirical Likelihood Ratio for Censored/Truncated Data
Empirical Likelihood Ratio Test for Two Samples with Censored
Data
Exact Multinomial Test: Goodness-of-Fit Test for Discrete
Multivariate data
Main Package of the EMU Speech Database Management System
Entropy Minimization over Variable Clusters (EMVC)
R Package for Fitting Multinomial Probit Models with Endogenous
Selection
R Package for Analyzing Endorsement Experiments
Data Published by the United States Federal Energy Regulatory
Commission
Data sets from "Introductory Statistics for Engineering
Experimentation"
English and European Soccer Results 1871-2016
Automated Runs and Evaluations of Ecological Niche Models
Ensemble Partial Least Squares Regression
An R Package for the Analysis of Multiple ChIP-Seq Data
Enrichment assessment of virtual screening approaches
Methods to Enrich R Objects with Extra Components
Extensible Package for Parallel, Batch Training of Base Learners
for Ensemble Modeling
Probabilistic Forecasting using Ensembles and Bayesian Model
Averaging
Extensible Package for Cross-Validation-Based Integration of
Base Learners
Extensible Package for Principal-Component-Regression-Based
Heterogeneous Ensemble Meta-Learning
Extensible Classes and Methods for Penalized-Regression-based
Integration of Base Learners
Entropy Partitioning to Measure Diversity
Estimation of Entropy, Mutual Information and Related Quantities
Estimation of Entropy and Related Quantities
Tools for Exploring Differential Shannon Entropy, Differential
Coefficient of Variation and Differential Expression
Isotope Pattern, Profile and Centroid Calculation for Mass
Spectrometry
Peak Picking for High Resolution Mass Spectrometry Data
Statistical Analysis of Environmental Space-Time Processes
Package for Environmental Statistics, Including US EPA Guidance
Statistical Functions for the Censored and Uncensored
Epanechnikov Distribution
Gaussian Approximation of Bayesian Binary Regression Models
A Package for Statistical Analysis in Epidemiology
Elementary Epidemiological Functions for Epidemiology and
Biostatistics
Implements Hierarchical Bayesian Models for Epidemiological
Applications
Epidemiological Tool for Contact Tracing
EpiEstim: a package to estimate time varying reproduction
numbers from epidemic curves
Flexible Modelling Functions for Epidemiological Data Analysis
Mathematical Modeling of Infectious Disease
Tools for the Analysis of Epidemiological Data
Basic Sensitivity Analysis of Epidemiological Results
Density Estimation with Soft Information by Exponential
Epi-splines
Conversion Between Epidemiological Weeks and Calendar Dates
EPoC (Endogenous Perturbation analysis of Cancer)
EQS Output Conversion to lavaan Functions
Tools for analyzing eQTL experiments: A complementary to Karl
Broman's 'qtl' package for genome-wide analysis
Direct, Chain and Average Equating Coefficients with Standard
Errors Using IRT Methods
Provides Tests and Graphics for Assessing Tests of Equivalence
Automated Spectral Deconvolution, Alignment, and Metabolite
Identification in GC/MS-Based Untargeted Metabolomics
Nonparametric Multiple Expectile Regression via ER-Boost
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
ERG Modeling Based on Graphlet Properties
Local Health Department network data set
Fit, Simulate and Diagnose Exponential-Family Models for
Rank-Order Relational Data
User-specified terms for the statnet suite of packages
Significance Analysis of Event-Related Potentials Data
Event-Related Potential (ERP) Data Exploration Made Easy
Event-related potentials (ERP) analysis, graphics and utility
functions
Estimate Number of Latent Factors and Factor Matrix for Factor
Analysis
Effect Size Computation for Meta Analysis
ESEA: Discovering the Dysregulated Pathways based on Edge Set
Enrichment Analysis
Toolkit for the simulation of financial assets and interest
rates models
Ensemble of Subset of K-Nearest Neighbours Classifiers for
Classification and Class Membership Probability Estimation
Calibrating Parameters for the Samejima's Continuous IRT Model
Estimation of Heritability in High Dimensional Sparse Linear
Mixed Models using Variable Selection
Tools for Assessing Estimability of Linear Predictions
Modeling Earthquake Data Using ETAS Model
Mixed FLP and ML Estimation of ETAS Space-Time Point Processes
Extract-Transform-Load Framework for Medium Data
Utility Functions to Execute Standard Extract/Transform/Load
Operations (using Package 'ff') on Large Data
Computes Moments of Univariate Truncated t Distribution
eulerian: A package to find eulerian paths from graphs
R Interface to the Europe PubMed Central RESTful Web Service
Bayesian Single Arm Sample Size Calculation Software
Extreme Value Analysis with Goodness-of-Fit Testing
Parsing and Evaluation Tools that Provide More Details than the
Default
Collection of Model Evaluation Measure Functions
Modelling Actual, Potential and Reference Crop
Evapotranspiration
Functions for Extreme Value Distributions
Bayesian Analysis in Extreme Value Theory
A Powerful Tool to Quickly Compare Huge Lists and Draw Venn
Diagrams
Extreme Value Mixture Modelling, Threshold Estimation and
Boundary Corrected Kernel Density Estimation
Comparative and Population Genetic Analyses
Tools for Evolutionary Quantitative Genetics
Evolutionary Parameter Estimation for 'Repast Simphony' Models
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
Exact Conditional 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
Monte Carlo Exact Tests for Log-linear models
Exact solution paths for regularized LASSO regressions with L_1
penalty
Exact Distributions for Rank and Permutation Tests
Confidence regions for exceedance sets and contour lines
Convenient Data Exchange with Microsoft Excel
Excursion Sets and Contour Credibility Regions for Random Fields
Calls Copy Number Variants from Targeted Sequence Data
Expanding Ploidy and Allele-Frequency on Nested Subpopulations
Modular Differential Evolution for Experimenting with Operators
experiment: R package for designing and analyzing randomized
experiments
Modeling without data using expert opinion
Explanation of Predictions for Classification and Regression
Models
Interactive Interfaces for Results Exploration
Exploratory analysis with the singular value decomposition
Calculate density dependent likelihood of a phylogenetic tree
Spatial analysis of extra-pair paternity
Data Sets from "Forecasting with Exponential Smoothing"
Some Useful Functions from Spreadsheets and 'SPSS' Statistics
Fast, Reliable and Elegant Reproducible Research
Convenience Functions for Botanists to Create Specimens Indices
Extending the Range of Functions for Probability Distributions
Maximum penalized likelihood estimation with extended lasso
penalty
Extra-binomial approach for pooled sequencing data
Categorical Data Analysis and Visualization
Additional Univariate and Multivariate Distributions
Extremely Randomized Trees (ExtraTrees) Method for
Classification and Regression
Estimation of Extreme Conditional Quantiles and Probabilities
Extreme Value Statistics and Quantile Estimation
Estimation of Extreme Value Dependence for Time Series Data
Estimate Lower Extreme Quantile with the Censored Weibull MLE
and Censored Weibull Mixture
Easy Analysis and Visualization of Factorial Experiments
Easy Interface to Effective Concentration Calculations
selects significant non-additive interaction between two
variables using fast GLM implementation
Avoid the Typical Working Directory Pain When Using 'knitr'
provide an easy to use framework to conduct simulation
Fast Covariance Estimation for Sparse Functional Data
Bayesian Sparse Factor Analysis model for the inference of
pathways responsive to drug treatment
Combination of Factorial Methods and Cluster Analysis
Extract and Visualize the Results of Multivariate Data Analyses
Multivariate Exploratory Data Analysis and Data Mining
Graphical Presentation of Simple Contrasts
Bayesian quantile regression factor models
Perform Factorial Analysis from 'FactoMineR' with a Shiny
Application
Scores the FACT and FACIT Family of Patient-Reported Outcome
Measures
thin wrapper for the Factual.com server API
Variable Selection for Supervised Classification in High
Dimension
Distributions that are Sometimes Used in Hydrology
Data from the Book "Multivariate Statistical Modelling Based on
Generalized Linear Models", First Edition, by Ludwig Fahrmeir
and Gerhard Tutz
Faisal Conjoint Model: A New Approach to Conjoint Analysis
Simulates Data from a Data Frame of Different Variable Types
Finding Allele-Specific Copy Number in Next-Generation
Sequencing Data
Finding Allele-Specific Copy Number in Whole-Exome Sequencing
Data
Simulation of Time-to-Event Family Data and Penetrance
Estimation
Probabilities for Pedigrees Given DNA Data
A Convex Formulation for Modeling Interactions with Strong
Heredity
Maximum Likelihood and Bayesian Estimation of Univariate
Probability Distributions
Factor Analysis for Multiple Testing (FAMT) : simultaneous tests
under dependence in high-dimensional data
Penalized Likelihood Factor Analysis via Nonconvex Penalty
Building Kriging Models from FANOVA Graphs
Visualisation of Sequential Probability Distributions Using Fan
Charts
Download Data from the FAOSTAT Database of the Food and
Agricultural Organization (FAO) of the United Nations
Influential Case Detection Methods for Factor Analysis and
Structural Equation Models
Modelization for Functional AutoRegressive Processes
Functions and Datasets for Books by Julian Faraway
Rmetrics - Analysing and Modelling Financial Assets
Implementation of the Fourier Amplitude Sensitivity Test (FAST)
Fast Estimation of a Covariance Matrix by Banding the Cholesky
Factor
A Fast Solver for Parameterized LP Problems, Constrained L1
Minimization Approach to Sparse Precision Matrix Estimation and
Dantzig Selector
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, Low Memory-Footprint Digests of R Objects
Raster Image Processing and Vector Recognition
Fast Rcpp implementation of Gauss-Hermite quadrature
Efficiently Using Gaussian Processes with Rcpp and RcppEigen
Fast Drawing and Shading of Graphs of Statistical Distributions
Robust Algorithm for Principal Component Analysis
Hierarchical Independent Component Analysis: a Multi-Scale
Sparse Non-Orthogonal Data-Driven Basis
FastICA Algorithms to perform ICA and Projection Pursuit
Learn from Training Data then Quickly Fill in Missing Data
A Fast Multiple-Kernel Method Based on a Low-Rank Approximation
Fast Computation of Multivariate M-estimators
FastPCS Robust Fit of Multivariate Location and Scatter
Foundations and Applications of Statistics Using R
Fits the FastRCS Robust Multivariable Linear Regression Model
Fast Interactive Framework for Web Scripting Using R
Fast Utility Function for Time Parsing and Conversion
Two-Locus Family-Based Association Test with Polytomic Outcome
Kiener Distributions and Fat Tails in Finance
Functions and Datasets for "Forest Analytics with R"
Gene by Environment Interaction and Conditional Gene Tests for
Nuclear Families
Algorithm for searching the space of Gaussian directed acyclic
graphical models through moment fractional Bayes factors
FISH Based Normalization and Copy Number inference of SNP
microarray data
Analyzing and Managing Facebook Ads from R
Association Football (Soccer) Ranking via Poisson Regression
Fast Algorithms to Bootstrap Receiver Operating Characteristics
Curves
Basics of Certificates and Structured Products Valuation
Rmetrics - Bivariate Dependence Structures with Copulae
A Method to Search for Differentially Expressed Genes and to
Detect Recurrent Chromosomal Copy Number Aberrations
Measuring functional diversity (FD) from multiple traits, and
other tools for functional ecology
Functional Data Analysis: K-Mean Alignment
Functional data analysis in a mixed model framework
Functional Data Analysis and Empirical Dynamics
Functional Data Analysis and Partial Differential Equations;
Statistical Analysis of Functional and Spatial Data, Based on
Regression with Partial Differential Regularizations
Interval Testing Procedure for Functional Data
Functional Data Analysis and Utilities for Statistical Computing
Multivariate Dependence with FDG Copulas
Permutation-based FDR Point and Confidence Interval Estimation
False Discovery Rate Procedure Under Discrete Null Distributions
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
Local Inferential Feature Significance for Multivariate Kernel
Density Estimation
Creates a Model Matrix via Feature Hashing with a Formula
Interface
Feature Extraction for Discretely-Sampled Functional Data
Fechnerian Scaling of Discrete Object Sets
Functions to Automate Downloading Geospatial Data Available from
Several Federated Data Sources
Client Package for the U.S. Federal Register API
Fixed Effects Nonlinear Maximum Likelihood Models
fExpressCertificates - Structured Products Valuation for
ExpressCertificates/Autocallables
Rmetrics - Extreme Financial Market Data
memory-efficient storage of large data on disk and fast access
functions
Basic Statistical Functions for Package 'ff'
Force field simulation for a set of points
Generate, Visualise, and Compare Fast and Frugal Decision Trees
Wrapper for FFTW3: Includes 1-D, Univariate and Multivariate,
and 2-D Transform
Rmetrics - Autoregressive Conditional Heteroskedastic Modelling
Fractional Gaussian Noise and power law decay time series model
fitting
Feature Grouping and Selection Over an Undirected Graph
Tests for Right and Interval-Censored Survival Data Based on the
Fleming-Harrington Class
Provide functions for forest inventory calculations
Classical, Reloaded and Adaptive FastICA Algorithms
A Lightweight and Flexible Web Framework
File-Backed Matrix Class with Convenient Read and Write Access
Effective File Navigation from the R Console
Rmetrics - Economic and Financial Data Import
Financial Instrument Model Infrastructure for R
Classifies implicit trading activity from market quotes and
computes the probability of informed trading
Time Value of Money, Time Series Analysis and Computational
Finance
Covariance Matrix Estimation and Regularization for Finance
Find all root(s) of the equation and Find root(s) of the
equation by dichotomy
Python tools to find an acceptable python binary
Functions to operate on binary fingerprint data
Computation of the probability of ruin within a finite time
horizon
Financial Data from U.S. Securities and Exchange Commission
Companion to Tsay (2005) Analysis of Financial Time Series
Fisheye and Hyperbolic-space-alike Interactive Visualization
Tools in R
Iterative FISH-based Calibration of Hi-C Data
Fits Poisson-sum-of-Gammas GLMs, Tweedie GLMs, and delta
log-normal mdoels
Transcriptomic Dynamics Models in Field Conditions
FitARMA: Fit ARMA or ARIMA using fast MLE algorithm
Help to Fit of a Parametric Distribution to Non-Censored or
Censored Data
FITS (Flexible Image Transport System) utilities
fitTetra is an R package for assigning tetraploid genotype
scores
Feature-Based Landscape Analysis of Continuous and Constraint
Optimization Problems
Fits Piecewise Constant Models with Data-Adaptive Knots
Implementation of optimal hierarchical clustering
R Markdown Format for Flexible Dashboards
Flexible Parametric Models for Censored and Truncated Data
Flexible Parametric Survival and Multi-State Models
Tools for Interacting with the Brazilian Flora 2020
Cytometric Diversity Indices from 'FlowJo' Workspaces
Tools for characterizing flowering traits
Forecasts future values of a univariate time series
Streamlining Design and Deployment of Complex Workflows
Daily Streamflow Trend and Change Point Screening
Path algorithm for the general Fused Lasso Signal Approximator
Multithreaded Fixed Size Subset Sum with Bounded Error in
Multidimensional Real Domain
Flux rate calculation from dynamic closed chamber measurements
Data Sets from "Forecasting: Methods and Applications" by
Makridakis, Wheelwright & Hyndman (1998)
A Flexible Modelling Environment for Inverse Modelling,
Sensitivity, Identifiability, Monte Carlo Analysis
Filtered Monotonic Polynomial IRT Models
Variable Selection in Finite Mixture of AFT Regression and FMR
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 - Analysing and Modeling Multivariate Financial Return
Distributions
Fast Nearest Neighbor Search Algorithms and Applications
Nonlinear and Chaotic Time Series Modelling
visualisation and analysis of food web networks
Rmetrics - Pricing and Evaluating Basic Options
Foraminifera and Community Ecology Analyses
Provides Foreach Looping Construct for R
Forecasting Functions for Time Series and Linear Models
Convenient Functions for Ensemble Time Series Forecasts
Floating-Point Genetic Algorithms with Statistical Forecast
Based Inheritance Operator
Read Data Stored by Minitab, S, SAS, SPSS, Stata, Systat, Weka,
dBase, ...
Statistical Methods in Forensic Genetics
Statistical tools for the interpretation of forensic DNA
mixtures
Visualizes Random Forests with Feature Contributions
Design-Based Global and Small-Area Estimations for Multiphase
Forest Inventories
Advanced Forest Plot Using 'grid' Graphics
Imputation of Missing Values Through a Forward Imputation
Algorithm
Functions from the 2nd Italian Forest Inventory (INFC)
Elementary arithemtic in formal series rings
Utilities for Formulas, Expressions, Calls and Other Objects
Palaeoecological and Palaeogeographical Analysis Tools
Bayesian 4 Parameter Item Response Model
Restricted MLE for Functional Principal Components Analysis
Reliable Comparison of Floating Point Numbers
Rmetrics - Portfolio Selection and Optimization
Computing the noncentrality parameter of the noncentral F
distribution
Data for "Forecasting: principles and practice"
Approximation of First-Passage-Time Densities for Diffusion
Processes
Fractionally differenced ARIMA aka ARFIMA(p,d,q) models
Fraction Proliferation via a Quiescent Growth Model
Fractal Time Series Modeling and Analysis
Estimation of Parameters p and q for Randomized Sierpinski
Carpet for [p-p-p-q]-Model
Generate fractal time series with non-normal returns
distribution
General Frailty Models: Shared, Joint and Nested Frailty Models
with Prediction
General Semiparametric Shared Frailty Model
Financial Risk Modelling and Portfolio Optimisation with R
Fuzzy Rule-Based Systems for Classification and Regression Tasks
Fast Regularized Canonical Correlation Analysis
Statistical algorithms used in common data mining course
Rmetrics - Regression Based Decision and Prediction
FREQ: Estimate population size from capture frequencies
Frequency Domain Analysis for Multivariate Time Series
Frequency Moving Average Plots (MAP) of Multinomial Data by a
Continuous Covariate
Frequency Profiles Computing and Plotting
Feature Selection Algorithms for Computer Aided Diagnosis
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
Regression Analysis of Fractional Responses
Regression Analysis of Fractional Responses Under Unobserved
Heterogeneity
Regression Analysis of Panel Fractional Responses
The Generalized Hyperbolic Distribution, Related Distributions
and Their Applications in Finance
Simple Fisheries Stock Assessment Methods
Data to Support Fish Stock Assessment (FSA) Package
Automated Feature Selection from 'caret'
Import and Analysis of OMR Data from FormScanner
Wrapper Functions for FSL (FMRIB Software Library) from
Functional MRI of the Brain (FMRIB)
Social Relations Analyses with Roles ("Family SRM")
Programs for Analyzing Fourier Transform-Ion Cyclotron Resonance
Mass Spectrometry Data
Features and Strings for Nonparametric Regression
R interface to tslib (a time series library in c++)
Spectral Density Estimation and Comparison for Functional Time
Series
FUzzy GEnetic, a machine learning algorithm to construct
prediction model based on fuzzy logic
Full Text of 'Scholarly' Articles Across Many Data Sources
Chi-Square and Exact Tests for Non-Parametric Functional
Dependencies
Functional Profiling of Microarray Expression Data
A package for functional data clustering
An algorithm for gene and gene set network inference
Clustering in the Discriminative Functional Subspace
Fungible Coefficients and Monte Carlo Functions
Model-based clustering in group-specific functional subspaces
Title: Learn Data Science Through the "Data Science Live Book"
Simple Utility Providing Terminal Access to all R Functions
funreg (Functional Regression for Irregularly Timed Data)
Community Detection via Fused Principal Component Analysis
A Tiny Utility Providing Polymorphic Operations
Random Matrix Generation and Manipulation
A framework for working in a functional programming paradigm in
R
Find, Characterize, and Explore Heat Waves in Climate
Projections
Exact calculation of fuzzy decision rules for multiple testing
Join Tables Together on Inexact Matching
Fuzzy Rank Tests and Confidence Intervals
Fuzzy Stationary Probabilities from a Sequence of Observations
of an Unknown Markov Chain
Forward search for Mokken scale analysis
Selecting Variables in Regression Models
Fire Weather Index System and Fire Behaviour Prediction System
Calculations
A package performing Dynamic Bayesian Network inference
Grain-Size Statistics and Description of Sediment
A genetic algorithm approach to determine stratum boundaries and
sample sizes of each stratum in stratified sampling
Abbreviating Items Measures using Genetic Algorithms
Framework for Generalized Subspace Pattern Mining
GAD: Analysis of variance from general principles
First Passage Time Simulation for Gaussian Diffusion Processes
Graphical Extension with Accuracy in Parameter Estimation
(GAIPE)
Genetic algorithms and C-steps based LTS (Least Trimmed Squares)
estimation
Fit the GamBin Model to Species Abundance Distributions
Generalized linear and additive models by likelihood based
boosting
Estimating multistate models using gamboost()
Functions and Data for a Course on Modern Regression and
Classification
Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for
Binary Classification
Statistical Estimation of Game-Theoretic Models
Tools for Calculating Allocations in Game Theory
Generalised Additive Models for Location Scale and Shape
Fitting an Interval Response Variable Using `gamlss.family'
Distributions
Distributions to be Used for GAMLSS Modelling
Fitting Mixture Distributions with GAMLSS
Fitting non linear parametric GAMLSS models
Generating and Fitting Truncated `gamlss.family' Distributions
Generalized additive mixed models using mgcv and lme4
classic gamma regression: joint modeling of mean and shape
parameters
Generalized additive mixed model analysis via slice sampling
Fit Regularization Path for Generalized Additive Models
Gene Association Network-based Pathway Analysis
Genetic Algorithm optimization for real-based and
permutation-based problems
Functions for Drawing Gapped Cluster Heatmap with ggplot2
Authorize and Request Google Analytics Data
Genetic Algorithm (GA) for Variable Selection from
High-Dimensional Data
Genetic Data Manipulation (Quality Control, GRM and LD
Computations, PCA), Linear and Logistic Mixed Models (AIREML
Algorithm), Association Testing
Difference measures for multivariate Gaussian probability
density functions
The Greatest Mathematician Since Antiquity
Collection of functions for Gaussian quadrature
Generalize Lambda Distribution and Generalized Bootstrapping
Generalized Beta Distribution of the Second Kind: Properties,
Likelihood, Estimation
Utilities for processing Rd objects and files
Simulation of Real and Complex Numbers and Small Programming
Utilities
Guided Correction Approach for Inherited bias (GCAI.bias)
Graph-based two-sample tests for categorical data
GPU/CPU Benchmarking in Debian-based systems
LASSO and (adaptive) Elastic-Net penalized least squares,
logistic regression, HHSVM and squared hinge loss SVM using a
fast GCD algorithm
Concord method for Graphical Model Selection
Datasets for the Book Graphical Data Analysis with R
Wrappers for the Geospatial Data Abstraction Library (GDAL)
Utilities
Various R Programming Tools for Data Manipulation
A toolbox for the analysis of categorical data in social
sciences, and especially Geometric Data Analysis
Download, slice, and normalize GDELT data
Generalized Diffusion Magnetic Resonance Imaging
Distances and Routes on Geographical Grids
Functions for Generalized Dissimilarity Modeling
Adaptive Association Tests for Multiple Phenotypes using
Generalized Estimating Equations (GEE)
Modified Variance Estimators for Generalized Estimating
Equations
Calculate Generalized Eigenvalues, the Generalized Schur
Decomposition and the Generalized Singular Value Decomposition
of a Matrix Pair with Lapack
File Conversion for 'Gem Infrasound Logger'
Network Meta-Analysis Using Bayesian Methods
Package contains data which is used by GenABEL example and test
functions
Global ENvironmental ASsessment Information System (GENASIS)
computational tools
Clopper-Pearson Confidence Interval and Generalized Binomial
Distribution
Predict Gender from Names Using Historical Data
Identification of Periodically Expressed Genes
Bayesian calculation of gene-specific FST from genomic SNP data
Detection of structure from multilocus genetic data
Profiling a gene list into GOslim or KEGG function pie
Belief Propagation in Genotype-Phenotype Networks
Genetic Epidemiology Design and Inference
Generalized Correlations and Initial Causal Path
Goodness of Fit Tests for Logistic Regression Models
Blinder-Oaxaca Decomposition for Generalized Linear Model
Generate Data Containing Fake Personally Identifiable
Information
Construct time delay gene regulatory network
Genome-Wide Association Study with SLOPE
Identify Favorable Subsets of Germplasm Collections
Collection of Genetic Data Analysis Tools
Spatial Graph-Theoretic Genetic Gravity Modelling
The Forward Imputation: A Sequential Distance-Based Approach for
Imputing Missing Data
A New, Fast, and Outlier Resistant Hierarchical Clustering
Algorithm
Functions for generating and manipulating binned kernel density
estimates
Path algorithm for generalized lasso problems
Functions for the Bayesian Analysis of GWAS Data
Application of MOSS algorithm to genome-wide association study
(GWAS)
'Plot genome wide values for all chromosomes'
Circular Genomic Permutation using Gwas p-Values of Association
Collection of Tools for Genomic Data Analysis
Plot Publication-Grade Gene and Genome Maps
Simulation of Discrete Random Variables with Given Correlation
Matrix and Marginal Distributions
Generalized PATHMOX Algorithm for PLS-PM, LS and LAD Regression
Generalized Ridge Trace Plots for Ridge Regression
R Functions for Generalized Simulated Annealing
Spline Based Window Boundaries for Genomic Analyses
Draw and Annotate Maps, Especially Charts of the North Atlantic
Analysis of Geostatistical Data using Bayes and Empirical Bayes
Methods
Analysis and Modeling for Geostatistical Count Data
A geometrical Approach to Differential expression and gene-set
enrichment
3D-Visualization of Geoelectric Resistivity Measurement Profiles
Spatial Prediction for Function Value Data
Quantification of the effect of geographic versus environmental
isolation on genetic differentiation
Tools for Geohash Creation and Manipulation
Convert Data from and to 'geoJSON' or 'topoJSON'
Web-Processing of Large Gridded Datasets
Data for topographic and Geologic Mapping
Network Visualization in the 'ggplot2' Framework
Geometric Morphometric Analyses of 2D/3D Landmark Data
Interface to www.geonames.org web service
Interface to the Geoparser.io API for Identifying and
Disambiguating Places Mentioned in Text
Geophysics, Continuum Mechanics, Mogi Models, Gravity
A Package for Generalised Linear Spatial Models
Robust Geostatistical Analysis of Spatial Data
Facilitate Generating of Distance Matrices Used in Package
'spacom' and Plotting Data on Maps
Geostatistical Analysis and Design of Optimal Spatial Sampling
Networks
Spatio-Temporal; Inverse Distance Weighting and Radial Basis
Functions with Distance-Based Regression
Geostatistical Modelling with Likelihood and Bayes
An R Plug-in for the Distributed Hydrological Model GEOtop
Interactive exploratory spatial data analysis
Google Encoded Polyline Algorithm Format
Estimation and Fit Diagnostics for Generalized Exponential
Random Graph Models
Generalized Structured Component Analysis (GSCA)
Download and Aggregate High Frequency Trading Data from Bovespa
Get Landsat 8 Data from Amazon Public Data Sets
Get Meteorological Data for Hydrologic Models
Parsing Command-Line Arguments and Variable Interpolation
GetR: Calculate Guttman error trees in R
General-to-Specific (GETS) Modelling and Indicator Saturation
Methods
Get Data for Brazilian Bonds (Tesouro Direto)
Learning Optimization and Machine Learning for Statistics
GEV Conditional Density Estimation Network
ARMA-GARCH/APARCH Models with GEV and Stable Distributions
A visual, intuitive, easy to use software giving access to a new
type of information buried into your microarray data
Tools for Working with Hansen et al. Global Forest Change
Dataset
Extra Coordinate Systems, Geoms and Statistical Transformations
for 'ggplot2'
Categorical Scatter (Violin Point) Plots
Visualization of a Correlation Matrix using 'ggplot2'
Create Dendrograms and Tree Diagrams Using 'ggplot2'
Visualization Tools for Genealogical Data
Add Marginal Histograms to 'ggplot2', and More 'ggplot2'
Enhancements
Data Visualization Tools for Statistical Analysis Results
Capture the Spirit of Your 'ggplot2' Calls
Make 'ggplot2' Graphics Interactive Using 'htmlwidgets'
Group Lasso Penalized Learning Using A Unified BMD Algorithm
Tools for Analyzing MCMC Simulations from Bayesian Inference
Gaussian Graphical Models Using Ridge Penalty Followed by
Thresholding and Reestimation
Geometries to Plot Networks with 'ggplot2'
Variations of Parallel Coordinate Plots for Categorical Data
An Implementation of the Grammar of Graphics
Polygons with Holes for the Grammar of Graphics
Allows Interactive Visualization of Data Through a Web Browser
GUI
Repulsive Text and Label Geoms for 'ggplot2'
Scientific Journal and Sci-Fi Themed Color Palettes for
'ggplot2'
'stats' for Seasonal Adjustment on the Fly with 'ggplot2'
North Symbols and Scale Bars for Maps Created with 'ggplot2' or
'ggmap'
Extensions to 'ggplot2' for Radiation Spectra
Offers Various Swiss Maps as ggplot2 Objects
An Extension to 'ggplot2', for the Creation of Ternary Diagrams
Extra Themes, Scales and Geoms for 'ggplot2'
A Package on Generalized Hyperbolic Distribution and Its Special
Cases
Gene Set Uncertainty in Enrichment Analysis
Gibbs Sampler for One-Way Mixed-Effects ANOVA and ANCOVA Models
Naive Gibbs Sampling with Metropolis Steps
Random Variate Generator for the GIG Distribution
Gillespie's Stochastic Simulation Algorithm (SSA)
Group Iterative Multiple Model Estimation
Computing the Gini-Based Coefficients for Weighted and Negative
Attributes
Generalized Iterative Proportional Fitting for Relational Models
The giRaph package for graph representation in R
A Helpful Way to Install R Packages Hosted on GitHub
Quantification of Pinned Microbial Cultures
Constructing panels of population pyramid plots based on lattice
Gaines and Kuklinski (2011) Estimators for Hybrid Experiments
Penalization in Large Scale Generalized Linear Array Models
Generalized Linear Autoregressive Moving Average Models
Graphical lasso- estimation of Gaussian graphical models
General Linear Ballistic Accumulator Models
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
(RS and FMKL) using Various Methods
An Asymmetry-Steepness Parameterization of the Generalized
Lambda Distribution
Fit GLD Regression Model and GLD Quantile Regression Model to
Empirical Data
Learning Interactions via Hierarchical Group-Lasso
Regularization
All Hierarchical or Graphical Models for Generalized Linear
Model
Bayesian Fractional Polynomials for GLMs
Fitting Generalized Linear Models Subject to Constraints
Distributed 'glm' for Big Data using 'ddR' API
Graph-Constrained Regularization for Sparse Generalized Linear
Models
Fit GLM with LEP-based penalized maximum likelihood
Generalized Linear Mixed Models via Monte Carlo Likelihood
Approximation
Generalised Linear Mixed Models and Spatial Models with WinBUGS,
BRugs, or OpenBUGS
Gauss-Seidel Generalized Linear Mixed Model solver
Variable Selection for Generalized Linear Mixed Models by
L1-Penalized Estimation
Generalized linear models with clustering
Generalized Linear Mixed Model (GLMM) for Binary Randomized
Response Data
Lasso and Elastic-Net Regularized Generalized Linear Models
Fit a penalized constrained continuation ratio model for
predicting an ordinal response
L1 Regularization Path for Generalized Linear Models and Cox
Proportional Hazards Model
Fit a penalized continuation ratio model for predicting an
ordinal response
Model selection and multimodel inference made easy
Variable Selection Deviation Measures and Instability Tests for
High-Dimensional Generalized Linear Models
Testing the additional predictive value of high-dimensional data
Bi-Level Optimization of Metabolic Network Models
Global Gene-Set Analysis for Association Studies
Generate Functions to Get or Set Global Options
Objective functions for benchmarking the performance of global
optimization algorithms
Identify Global Objects in R Expressions
Plot 2D and 3D Views of the Earth, Including Major Coastline
Fitting and Testing Generalized Logistic Distributions
Generalized Logrank Tests for Interval-censored Failure Time
Data
Generalized Least Squares with Measurement Error
Distance and Travel Time Between Two Points from Google Maps
Fast Estimation of Gaussian Mixture Copula Models
Graph Based Multiple Comparison Procedures
Generalized Minimum Distance of distributions
Accessing a Geometallurgical Database with R
Short Term Forecasting via GMDH-Type Neural Network Algorithms
Geometric Median, k-Median Clustering and Robust Median PCA
Meta-Analysis via a Unified Framework of Confidence Distribution
Descriptive Statistics, Transition Plots, and More
Generalized Method of Moments and Generalized Empirical
Likelihood
Multinomial Logit Models with Random Parameters
Various R Programming Tools for Model Fitting
Interface between GMT Map-Making Software and R
Computation of Generalized Nash Equilibria
Generalized Non-negative Matrix Factorization Based on Renyi
Divergence
Read Data from Files Readable by Gnumeric
Weighted and lexicographical goal programming and optimization
Functions for Community Data and Ordinations
Model-diagnostics based on cumulative residuals
Testing Goodness-of-Fit with the Kernel Density Estimator
Khmaladze Martingale Transformation Goodness-of-Fit Test
Tests of Fit for some Probability Distributions
Classical Goodness-of-Fit Tests for Univariate Distributions
Generalized Orthogonal GARCH (GO-GARCH) models
Association Analysis for Categorical Variables
Easy Authentication with Google OAuth2 API
Collect Data Programmatically by POST Methods to Google Forms
Working with Google Public Data Explorer DSPL Metadata Files
Visualization of Functional Analysis Data
Fit Generalized Odds Rate Mixture Cure Model with Interval
Censored Data
functions to get public survey data in Japan
Gaussian Processes for Pareto Front Estimation and Optimization
Batch Effect Detection via Guided Principal Components Analysis
GPCSIV, Generalized Principal Component of Symbolic Interval
variables
General Profiling Method for Delay Differential Equation
Bootstrap goodness-of-fit test for the generalized Pareto
distribution
Apply Gaussian Process in Functional data analysis
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
A Minimalistic package to apply Gaussian Process in R
gpseq: Using the generalized Poisson distribution to model
sequence read counts from high throughput sequencing
experiments
Maximum Likelihood Estimation of Multiple Membership Mixed
Models Used in Value-Added Modeling
Graph-Constrained Estimation and Hypothesis Tests
Species distribution modelling using latent Gaussian random
fields
Graphical Representation and Modeling of Metagenomic Reads
Creating Continuously Integrated Package Repositories from
Manifests
Graphical Analysis of Variance Using ggplot2
Efficient selection of undirected graphical models for
high-dimensional datasets
A Multi-Platform GUI for Drawing Customizable Graphs in R
Graphical VAR for Experience Sampling Data
Cluster Detection with Hypothesis Free Scan Statistic
Inference in Graphical Gaussian Models with Edge and Vertex
Symmetries
Gene ID Mapping for Genotype-Tissue Expression (GTEx) Data
Fit a Grey-Zone Model with Survival Data
Miscellaneous Functions for "Grid" Graphics
Redraw Base Graphics Using 'grid' Graphics
Uses Grieg-Smith method on 2 dimentional spatial data
Generalized Regression on Orthogonal Components
The package was developed to fit fit many growth curves obtained
under different conditions
Gromov-Hausdorff Type Distances for Labeled Metric Spaces
Regression Analysis of Grouped and Coarse Data
Regularized Multivariate Regression for Identifying Master
Predictors Using the GroupRemMap Penalty
A GUI-Based Program to Compute Probabilities Regarding Group
Sequential Designs
Multiple Testing Procedure for Grouped Hypotheses
Bayesian Semi and Nonparametric Growth Curve Models that
Additionally Include Multiple Membership Random Effects
Bayesian Non-Parametric Dependent Models for Time-Indexed
Functional Data
Simple Metrics to Summarize Growth Curves
Bayesian reconstruction of growth velocity
Estimate Growth Rates from Experimental Data
Fitting user specified models with Group Lasso penalty
Concave 1-norm and 2-norm group penalty in linear and logistic
regression
Regularization Paths for Regression Models with Grouped
Covariates
Penalized Regression Models with Overlapping Grouped Covariates
Alternative Implementations of Base R Functions
Tools for the Analysis of Gutenberg-Richter Distributions of
Earthquake Magnitudes
Gene Set Analysis using the Gamma Method
Two functions for Generalized SARIMA time series simulation
Robust Estimation in the Presence of Cellwise and Casewise
Contamination and Missing Data
Semi-Supervised Generalized Structural Equation Modeling
Group Sequential Design in Equivalence Studies
Download Google Sheets Using Just the URL
Download, Clean and Generate New Variables from GSOD Data
Genome Structure Rearrangement Calling in Genomes with High
Synteny
Copula Density and 2-D Hazard Estimation using Smoothing Splines
Spatial and Spatio-Temporal Geostatistical Modelling, Prediction
and Simulation
Utilities for strings and function arguments
Estimation of the Generalized Symmetry Point, an Optimal
Cutpoint in Continuous Diagnostic Tests
Calculate efficiencies of group testing algorithms with
correlated responses
Game-Theoretically OPtimal (GTOP) Reconciliation Method
R Functions to Perform and Display Google Trends Queries
Maps, data and methods related to Guerry (1833) "Moral
Statistics of France"
Adjust Estimates of Learning for Guessing
Implementation of Sampling Formulas for the Unified Neutral
Model of Biodiversity and Biogeography, with or without Guild
Structure
Statistical Analysis of Monthly Background Checks of Gun
Purchases
Download and Process Public Domain Works from Project Gutenberg
Fast Calculation of the Likelihood of a Stochastic Survival
Model
Regularized Categorical Effects/Categorical Effect
Modifiers/Continuous/Smooth Effects in GLMs
Global Validation of Linear Models Assumptions
Genome-Wide Association/Interaction Analysis and Rare Variant
Analysis with Family Data
Exact Hardy-Weinburg testing for Genome Wide Association Studies
A Shiny App to Aid Interpretation of Geometrically-Weighted
Degree Estimates in Exponential Random Graph Models
Controlling the genome-wide type I error rate in association
mapping experiments
Calculation of probabilities for inadequate and excessive
gestational weight gain
gWidgets API for building toolkit-independent, interactive GUIs
Rewrite of gWidgets API for Simplified GUI Construction
Implementation of gWidgets2 for the RGtk2 Package
Toolkit Implementation of gWidgets2 for tcltk
Toolkit implementation of gWidgets for RGtk2
Toolkit implementation of gWidgets for tcltk package
Geographically Weighted Logistic Elastic Net Regression
Generalized Waring Regression Model for Count Data
Fits geographically weighted regression models with diagnostic
tools
Estimating Genome-Wide Significance for Whole Genome Sequencing
Studies, Either Single SNP Tests or Region-Based Tests
Maximum Likelihood Estimation for Gene-by-Measured Environment
Interaction Models
Software to perform Haar Fisz transforms
Estimation, Simulation and Visualization of Hierarchical
Archimedean Copulae (HAC)
Utilities for using R scripts in Hadoop streaming
Hierarchical Optimal Matching and Machine Learning Toolbox
Univariate non-parametric two-sample test based on empirical
Hankel transforms
Inference of Trait Associations with SNP Haplotypes and Other
Attributes using the EM Algorithm
Analyzing Case-Parent Triad and/or Case-Control Data with SNP
Haplotypes
Estimate Haplotype Relative Risks in Case-Control Data
Statistical Analysis of Haplotypes with Traits and Covariates
when Linkage Phase is Ambiguous
Tool for Clustering Genotypes in Haplotypes
Haplotype Inference and Statistical Analysis of Genetic
Variation
Statistical Tests and Graphics for Hardy-Weinberg Equilibrium
Harmonic Regression to One or more Time Series
Full feature implementation of hash/associated
arrays/dictionaries
A collection of non-cryptographic hash functions
Generate Short Unique YouTube-Like IDs (Hashes) from Integers
Hawkes process simulation and calibration toolkit
Damage functions from FEMA's HAZUS software for use in modeling
financial losses from natural disasters
Hierarchical Bayesian Modeling of Decision-Making Tasks
Hierarchical Bayesian Regression for GLMs
Hill/Bliss Independence Model for Combination Vaccines
Hierarchical Bayesian Analysis of Recognition Memory
Hierarchical Bayesian Small Area Estimation
Hierarchical Bayesian Space-Time models for Gaussian space-time
data
Interval estimation for the parameters of linear models with
heteroskedasticity (Wild Bootstrap)
Change Point Estimation for Regression with Heteroscedastic Data
High Dimensional Supervised Classification and Clustering
Sample Size Calculation for High Dimensional Classification
Study
Use known groups in high-dimensional data to derive scores for
plots
Hierarchical DECOmposition of Entropy for Categorical Map
Comparisons
Tests for High Dimensional Generalized Linear Models
Statistical Analysis Tools for High Dimension Molecular Data
(HDMD)
Nomograms for High-Dimensional Cox Models
Leland Wilkinson's Algorithm for Detecting Multidimensional
Outliers
Principal Component Analysis in High-Dimensional Data
Interface to the UNDR Human Development Report API
Highest density regions and conditional density estimation
The Lasso for the Tweedie's Compound Poisson Model Using an
IRLS-BMD Algorithm
Health Effects of Air Pollution and Temperature (HEAT)
Heat exchange calculations during physical activity
Fit Statistic for Binary Dependent Variable Models
Robust Estimation Using Heavy-Tailed Distributions
Providing 'stringsAsFactors=FALSE' Variants of 'data.frame()'
and 'as.data.frame()'
Visualizing Hypothesis Tests in Multivariate Linear Models
Hierarchical Exponential-Family Random Graph Models
Marker-Based Estimation of Heritability Using Individual Plant
or Plot Data
Heuristics Including Take the Best and Unit-Weight Linear
Holonomic Gradient Method and Gradient Descent
Handy Functions for Working With HGNC Gene Symbols and
Affymetrix Probeset Identifiers
Statistical Analysis and Data Display: Heiberger and Holland
Heller-Heller-Gorfine Tests of Independence and Equality of
Distributions
The Hilbert-Huang Transform: Tools and Methods
Simulation from distributions supported by nested hyperplanes
Bindings for the HaveIBeenPwned.com Data Breach API
Multiple Logistic Regression for 3D Chromatin Domain Border
Analysis
The All-Configurations, Maximum-Interaction F-Test for Hidden
Additivity
Inference on High Dimensional Max-Stable Distributions
Functions For Performing Hierarchical Analysis of Distance
Sampling Data
Set Data Visualization Using Hierarchies
Hierarchical Multiplicative Partitioning of Complex Phenotypes
Analysis of Dynamics Hierarchy Formation
Estimation and Tests of Hierarchical F-Statistics
A graphical user interface for calculating power and sample size
for hierarchical data
Convex Hierarchical Testing of Interactions
Two-Sample Tests for Equality of Means in High Dimension
Outlier Detection Algorithms for High-Dimensional Data
Two-Sample Tests for High-Dimensional Mean Vectors
Determining and Evaluating High-Risk Zones
High Throughput Screening for Plate Based Essays
Simultaneous Critical Values for t-Tests in Very High Dimensions
Estimation of Heritability in Linear Mixed Models
H-Index Calculator using Data from a Web of Science (WoS)
Citation Report
Tools for hypothesis testing based on Hypergeometric
Intersection distributions
Hierarchical Semiparametric Regression of Test Statistics
Data Sets from the History of Statistics and Data Visualization
Construction of regular and irregular histograms with different
options for automatic choice of bins
"Hit and Run" and "Shake and Bake" for Sampling Uniformly from
Convex Shapes
HIV calibrated model life tables for countries with generalized
HIV epidemics
Conversion Tools for HK80 Geographical Coordinate System
Spatial Extreme Value Analysis with the Hierarchical Model of
Reich and Shaby (2012)
API to Retrieve Data from Hong Kong Stock Exchange
Diagnostic Tools for Hierarchical (Multilevel) Linear Models
Hierarchical Latent Space Network Model (HLSM)
The H-measure and other scalar classification performance
metrics
Hidden Markov Model for Continuous Observations Processes
Hidden Markov Models with Discrete Non-Parametric Observation
Distributions
Analysing accelerometer data using hidden Markov models
Hypothesis Testing and Power Calculations for Comparing
Metagenomic Samples from HMP
Statistical Object Oriented Data Analysis of RDP-Based Taxonomic
Trees from Human Microbiome Data
Flux Estimation with Static Chamber Data
Group Association Test using a Hidden Markov Model
Half-Normal Plots with Simulation Envelopes
Information Retrieval for Genetic Datasets
Holiday and Half-Day Data, for Use with the 'TimeWarp' Package
Theoretical Model to Simulate Radical Polymerization
Homogeneity tests for Regional Frequency Analysis
Transmissions and Receptions in a Hop by Hop Network
Horn's (1965) Test to Determine the Number of Components/Factors
Hot Deck Imputation Methods for Missing Data
A lower bound for the number of correct rejections
Heligman Pollard mortality model parameter estimation using
Bayesian Melding with Incremental Mixture Importance Sampling
High Performance Cluster Models Based on Kiefer-Wolfowitz
Recursion
Miscellaneous convenience functions and dataset
Regularization Paths for Lasso or Elastic-Net Penalized Huber
Loss Regression and Quantile Regression
Hierarchical Spatial Autoregressive Model (HSAR)
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)
Manage, Analyse and Simulate Hyperspectral Data
hierarchical Bayesian species distribution models
Canonical Correlation Analysis based on Kernel Independence
Measures
A Path-Based BCD for Proximal Function of Latent Group Lasso
Phasing, Pedigree Reconstruction, Sire Imputation and
Recombination Events Identification of Half-sib Families Using
SNP Data
Meta-Analysis of Diagnostic Test Accuracy when Reference Test is
Imperfect
Facilitates Automated HTML Report Creation
Clustering High-Throughput Transcriptome Sequencing (HTS) Data
compute HUM value and visualize ROC curves
Simplify Analysis and Annotation of Human Microarray Datasets
An R Package for Calculating Water Vapor Measures from
Temperature and Relative Humidity
Morphological Analysis and Spell Checker for R
Models and Tests for Departure from Hardy-Weinberg Equilibrium
and Independence Between Loci
Bayesian investigation of Hardy-Weinberg Equilibrium via
estimation and testing
Objective Bayesian Testing for the Hardy-Weinberg Equilibrium
Problem
Testing Hardy-Weinberg Equilibrium for Multiallelic Genes
HTML Writer - Outputs R objects in HTML format
hwriterPlus: Extending the hwriter Package
Exact Tests for Hardy-Weinberg Proportions
Build, Deploy and Evaluate Hybrid Ensembles
Implementation of the Hybrid Monte Carlo and Multipoint Hybrid
Monte Carlo sampling techniques
Stochastic Hybrid Models in Dynamic Networks
Hybrid Bayesian Networks Using R and JAGS
Tools and models for hydrological applications
Groundwater Data Presentation and Interpretation
Goodness-of-fit functions for comparison of simulated and
observed hydrological time series
R codes for estimating water retention and infiltration model
parameters using experimental data
Particle Swarm Optimisation, with focus on Environmental Models
Hydrologic Indices for Daily Time Series Data
Time series management, analysis and interpolation for
hydrological modelling
A generalization of the Dirichlet distribution
Generic N-Dimensional Hyperplane Fitting with Heteroscedastic
Covariant Errors and Intrinsic Scatter
Hyper-Ensemble Smote Undersampled Random Forests
Work with Hyperspectral Data, i.e. Spectra + Meta Information
(Spatial, Time, Concentration, ...)
High-Dimensional Kernel Density Estimation and Geometry
Operations
Tools to Hyphenate Strings Using the 'Hunspell' Hyphenation
Library
Macroevolutionary phylogentic analysis of species trees and gene
trees
Confidence Intervals and Tests of Statistical Hypotheses
Wrapper for the 'Hypothes.is' Web Annotation Service
Tools for Modeling Rate-Dependent Hysteretic Processes and
Ellipses
Synthesizing Information Across Collaborating Research
Model Selection for Index of Asymmetry Distribution
Cleaning and Visualizing Implicit Association Test (IAT) Data
Implicit Association Test Scores Using Robust Statistics
Integrative Bayesian Analysis of Transcriptomic and CGH Data
Functions for the Analysis of IBD Haplo Output
Convert Between Different IBD-State Labelling Schemes
Regression Methods for IBD Linkage With Covariates
Simulation of Chromosomal Regions Shared by Family Members
Irregular-lattice based ensemble empirical mode decomposition
Toolkits to Develop Individual-Based Models in Infectious
Disease
Iboot: iterated bootstrap tests and confidence sets
R API to Interactive Brokers Trader Workstation
An Interface to WinBUGS/OpenBUGS/JAGS by gWidgets
A Copy Number and Expression-Based Classifier for Breast Tumours
Inequality and Concentration Indices and Curves
Standardized high-throughput evaluation of cell-based compound
screens
Independent Components Analysis (ICA) based artifact correction
Imperialist Competitive Algorithm for Optimal Designs
Calibrates and Reweights Units in Samples
Bayesian Semiparametric Models for Interval-Censored Data
Facilitating Estimation of the Intraclass Correlation
Coefficient
Multilevel model intraclass correlation for slope heterogeneity
Calculation of Sample Size and Power for ICC
Tools for Working with ICD-9 and ICD-10 Codes, and Finding
Comorbidities
Tools for Working with ICD-9 Codes, and Finding Comorbidities
EM by the Method of Weights for Incomplete Categorical Data in
Generlized Linear Models
Individual Conditional Expectation Plot Toolbox
Incremental Cost-Effectiveness (ICE) Statistical Inference from
Two Unbiased Samples
Regression Models for Interval Censored Data
Study Design and Data Analysis in the Presence of Error-Prone
Diagnostic Tests and Self-Reported Outcomes
Stock Assessment Graphs Database Web Services
Estimation of number of clusters and identification of atypical
units
Fit Generalized Odds Rate Hazards Model with Interval Censored
Data
Inequality constrained inference in linear normal situations
A Button-Based GUI for Financial and Economic Data Analysis
Integrative clustering of multiple genomic data types
Reproducible Data Retrieval from the ICPSR Archive
A Modified Random Survival Forest Algorithm
Tools for Exploring Multivariate Data via ICS/ICA
A package for semiparametric regression analysis of
interval-censored data
R Interface to the US Census Bureau International Data Base API
Inference in Randomized Controlled Trials with Death and
Missingness
Jacquard Condensed Coefficients of Identity
Integrated Discovery of Oncogenic Signatures
Utilities of Institute of Data Analyses and Process Design
(www.idp.zhaw.ch)
Imprecise Dirichlet Process for Survival Analysis
Estimate Global Clustering in Infectious Disease
Identify Turtles by their Plastral Biometries
R Analysis package for iDynoMiCS Simulation Results
Irucka Embry's Miscellaneous USGS Functions
Irucka Embry's Miscellaneous USGS Data Collection
Functions to set and get the IEEE rounding mode
Irucka Embry's Miscellaneous Data Collection
Irucka Embry's Miscellaneous Text Collection
An integrative factor analysis model for drug-pathway
association inference
Toolkit for Item Factor Analysis with OpenMx
Italian Fiscal Code ('Codice Fiscale') Utilities
Statistical Tests and Utilities for Genetic Association
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
Instagram 2014 Vancouver Top Colour Dataset
Consistency, Homogeneity and Summary Statistics of
Climatological Data
Improved Laplace Approximation for Integrals of Unimodal
Functions
Lee-Carter Mortality Models using Iterative Fitting Algorithms
Aids in Processing and Plotting Data from a Lemna-Tec
Scananalyzer
R Interface for International Monetary Fund(IMF) Data API
Download Data from the International Monetary Fund's Data API
Item Response Models for Multiple Ratings
Identifying Causal Effect for Multi-Component Intervention Using
Instrumental Variable Method
Imprecise Inferential Framework for Poisson Sampling Model
Minimum distance estimation in an imprecise probability model
A collection of methods for left-censored missing data
imputation
The Multifactor Dimensionality Reduction (MDR) Analysis for
Incomplete Data
Impute Missing Values in a Predictive Context
Imputation Methods for Multivariate Multinomial Data
Impute Missing Data in Time Series Data with PSF Based Method
Test Bench for Missing Data Imputing Models/Methods Comparison
Imputing the Last Largest Censored Observation(s) Under Weighted
Least Squares
Mixture models for longitudinal count data
Analysing Inbreeding Based on Genetic Markers
Dose Response Curves from Incucyte Proliferation Assays
Insertion Deletion Analysis While Accounting for Possible
Missing Data
Nonparametric tests of independence between random vectors
Relationship Between Species and Groups of Sites
Tests of Independence Between Point Processes in Time
Integrate INEGI’s (Mexican Stats Office) API with R
Measuring Inequality, Concentration, and Poverty
Interpolation and Extrapolation for Species Diversity
Infine-dimensional model (IDM) to analyse phenotypic variation
in growth trajectories
Functions to extract inferential values of a fitted model object
Inference about the standardized mortality ratio when evaluating
the effect of a screening program on survival
Methods for Causal Inference with Interference
Tools for Detecting Influential Data in Mixed Effects Models
Software Tools to Quantify Structural Importance of Nodes in a
Network
Case Influence in Structural Equation Models
Information Decomposition of Two-phase Experiments
Data Exploration with Information Theory (Weight-of-Evidence and
Information Value)
Performance Analysis and Companion Functions for Binary
Classification Models
Multiple Imputation for Informative Censoring
Sequence Statistics for Relational Event Models
Functions to Inline C, C++, Fortran Function Calls from R
Convert inline comments to documentation
Analyse Text Documents Using Ecological Tools
insideRODE includes buildin functions with deSolve solver and
C/FORTRAN interfaces to nlme, together with compiled codes
Probabilistic Verbal Autopsy Coding with 'InSilicoVA' Algorithm
High-Dimensional Changepoint Estimation via Sparse Projection
Check, Install and Load CRAN & USGS GRAN Packages
Using R to Install Stuff (Such As: R, Rtools, RStudio, Git, and
More!)
A Collection of Insurance Datasets Useful in Risk Classification
in Non-life Insurance
procedures for automated interpolation - methods only to be used
interactively, not included in intamap package
Joint Modelling of the Gene-Expression and Bioassay Data, Taking
Care of the Effect Due to a Fingerprint Feature
Integrated Prediction using Univariate and Multivariate Random
Forests
Tests for marginal interactions in a 2 class response model
Calculates Critical Test Statistics to Control False Discovery
and Familywise Error Rates in Marginal Effects Plots
interactive network analysis and visualization
Compute Chi-Square Measures with Corrections
Cure Rate Estimators for Interval Censored Data
Exact Confidence Intervals in the Presence of Interference
Coercion Routines for Network Data Objects
Plot the Effects of Variables in Interaction Terms
Hourly interpolation of multiple temperature daily series
Binary Classifier and Regression Model Interpretation Functions
Simulation of Inter-Related Genomic Datasets
Weighted Logrank Tests and NPMLE for interval censored data
Tools for Working with Points and Intervals
Interventional Inference for Dynamic Bayesian Networks
Numerical Integration for Integrated Likelihood
Integrative Clustering of Multiple Genomic Dataset
linear programming solver by the interior point method and
graphically (two dimensions)
methods for analyzing introgression between divergent lineages
Interface to Popular R Functions for Data Science Pipelines
Threshold regression that fits the (randomized drift) inverse
Gaussian distribution to survival data
A Unified Framework for Input-Output Operations in R
Calling Copy Number Alterations in Amplicon Sequencing Data
Calculate the Number of Required Flows for Semiconductor
Sequencing
Functions for smoothing with infinite order flat-top kernels
Tools for subgroup analyses with multiple trial data using
aggregate statistics
Spatial Interpolation by Inverse Path Distance Weighting
Fast Implementation of the Iterative Proportional Fitting
Procedure in C
Builds and analyses Integral Projection Models (IPMs)
Interfaces to Phylogenetic Software in R
Introduction to Probability and Statistics Using R
Convert IP Addresses to Country Names or Full Location with
Geoplotting
Manipulate, Validate and Resolve 'IP' Addresses
Generate Chemical Strings (SMILES) with the Inverse QSPR Model
Integrative Random Forest for Gene Regulatory Network Inference
Regression Methods for Interval-Valued Variables
Classes and Methods for Seismic Data Analysis
Fast Truncated SVD, PCA and Symmetric Eigendecomposition for
Large Dense and Sparse Matrices
Various Coefficients of Interrater Reliability and Agreement
Simple interface to the estimation and plotting of IRT models
Estimating IRT Parameters using the IRT Methodology
Utilities and Probability Distributions Related to
Multidimensional Person Item Response Models
Estimation of Tree-Based Item Response Models
Iterative Selection of Blocks of Features - ISBF
Provides datasets for Introduction to Statistical Data Analysis
for the Life Sciences
Fitting Ising models using the eLasso method
Sampling Methods and Distribution Functions for the Ising Model
Stochastic Island Biogeography Theory Made Easy
Data for An Introduction to Statistical Learning with
Applications in R
An Introduction to Statistical Modeling of Extreme Values
Functions to Perform Isotonic Regression
Confidence intervals for current status data based on
transformations and bootstrap
Order-Restricted Inference for Microarray Experiments
Calculation of isotopic pattern for a given molecular formula
Statistical Toolbox for Radiometric Geochronology
Active Set and Generalized PAVA for Isotone Optimization
Penalized Isotonic Regression in one and two dimensions
Week of the year and weekday according to ISO 8601
Approximate probability densities by iterated Laplace
Approximations
Efficient Iterator for Permutations and Combinations
itertools2: Functions creating iterators for efficient looping
Tools for classification and regression trees, with an emphasis
on interpretability
Interpreting Time Series and Autocorrelated Data Using GAMMs
Time series analysis package for students
Incorporating Uncertainties in Propensity Scores
Bayesian Instrumental Variable Estimation and Model
Determination via Conditional Bayes Factors
Instrumental fixed effect panel data model
Uses heteroscedasticity to estimate mismeasured and endogenous
regressor models
Statistical Inference and Sensitivity Analysis for Instrumental
Variables Model
Improved methods for causal inference and missing data problems
Simulation-Based Maximum Likelihood Parameter Estimation
Jackknife Estimates of Kaplan-Meier Estimators or Integrals
Statistical Inference of Variables Driving Systematic Variation
Jaccard Index for Population Structure Identification
Blind Source Separation Methods Based on Joint Diagonalization
and Some BSS Performance Criteria
A Wrapper Around 'rjags' to Streamline 'JAGS' Analyses
Joint Analysis of Genotype and Group-Specific Variability Using
a Novel Score Test Approach to Map Expression Quantitative
Trait Loci (eQTL)
Analysis Tools for the 'JAMES' Framework
R modules for JASPAR databases: a collection of transcription
factor DNA-binding preferences, modeled as matrices
Misc Small Tools and Helper Functions for Other Code of J.
Buttlar
One-to-One Gene-Probeset Mapping for Affymetrix Human
Microarrays
Joint Generalized Estimating Equation Solver
Performs the Joint Graphical Lasso for sparse inverse covariance
estimation on multiple classes
Chinese Text Segmentation Data for jiebaR Package
Joint Modeling of Longitudinal and Survival Data
Joint Modeling of Longitudinal and Time-to-Event Data under a
Bayesian Approach
Joint Mean-Covariance Models using 'Armadillo' and S4
Joint Modeling of Longitudinal and Survival Data - Power
Calculation
Time Series Analysis Toolkit Based on Symbolic Aggregate
Dicretization, i.e. SAX
Permutation Tests for Nonparametric Statistics
Joint modelling of repeated measurements and time-to-event data
Penalized Likelihood Estimation and Dynamic Prediction under the
Joint Frailty-Copula Models Between Tumour Progression and
Death for Meta-Analysis
Joint Approximate Diagonalization of a set of square matrices
Semiparametric Joint Models for Longitudinal and Counting
Processes
Risk estimation using the joint probability method
Joint Modelling of Mixed Correlated Binary and Continuous
Responses : A Latent Variable Approach
Multilevel Joint Modelling Multiple Imputation
Functions for some Unit-Level Small Area Estimators and their
Variances
Javascript Object Signing and Encryption
Covariance and Inverse Covariance Matrix Estimation Using Joint
Penalty
Methods for population-based cancer survival analysis
Joint Random Forest (JRF) for the Simultaneous Estimation of
Multiple Related Networks
Jack-Knife Support for Evolutionary Distinctiveness Indices I
and W
Basic Finance; NPV/IRR/Annuities/Bond-Pricing; Black Scholes
A Robust, High Performance JSON Parser and Generator for R
Package to identify and sort genes overexpressed
Kantorovich Distance Between Probability Measures
Non-Additive Measure and Integral Manipulation Functions
Sample Size Estimation Functions for Studies of Interobserver
Agreement
Calculates "vectorial Kappa", an index of congruence between
patchy mosaics
K-Adaptive Partitioning for Survival data
Kinetic analysis and visualization of DCE-MRI data
Kernel Smoothing for Bivariate Copula Densities
Nonparametric method for identifying discordant phylogenetic
trees
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
Nonparametric kernel estimation of the distribution function.
Bandwidth selection and estimation of related functions
Expectile Regression in Reproducing Kernel Hilbert Space
Distance Weighted Discrimination (DWD) and Kernel Methods
Kernel Factory: An Ensemble of Kernel Machines
Kernel Density Estimation for Heaped and Rounded Data
Kernel Machine Score Test for Semi-Competing Risks
Functions for Kernel Smoothing Supporting Wand & Jones (1995)
Kalman Filter and Smoother for Exponential Family State Space
Models
Integrated Code Chunk Anchoring and Referencing for R Markdown
Documents
Kalman Filter, Smoother and Disturbance Smoother
Framework for the Analysis of Kinetic Visual Field Data
Routines for Fitting Kinetic Models to Chemical Degradation Data
An Implementation of 'kinn' Algorithm, a Graph Based Regression
Model
a Keep It Simple Species Migration Model
Spectral response of water wells to harmonic strain and pressure
Linear equations with Kronecker structure
Kaplan-Meier Estimator with Constraints for Right Censored Data
-- a Recursive Computational Algorithm
Confidence intervals for the Kaplan-Meier estimator
Kaplan-Meier Simultaneous Confidence Band for the Survivor
Function
Distributed k-Means for Big Data using 'ddR' API
Kaplan-Meier multiple imputation for the analysis of cumulative
incidence functions in the competing risks setting
Clustering longitudinal data using the likelihood as a metric of
distance
K-Means for Longitudinal Data using Shape-Respecting Distance
K-Means with Simultaneous Outlier Detection
Data sets from Klein and Moeschberger (1997), Survival Analysis
A General-Purpose Package for Dynamic Report Generation in R
Nearest-neighbor Classification with Categorical Variables
Knockoff Filter for Controlling the False Discovery Rate
Tools for the provision of scientific fisheries management
advice
Knowledge discovery by accuracy maximization
A Genetic Algorithm for Fixed-Size Subset Selection
Functional Summary and Meta-Analysis of Gene Expression Data
Supervised and Unsupervised Self-Organising Maps
An Improved Evaluation of Kolmogorov's Distribution
Koul's Minimum Distance Estimation in Linear Regression and
Autoregression Model
Cubic Spline Fitting with Knot Selection
Method for Clustering Partially Observed Data
Kriging-based Inversion for Deterministic and Noisy Computer
Experiments
Kernel-based Regularized Least squares (KRLS)
K-Sample Rank Tests and their Combinations
Goodness-of-Fit Tests using Kernelized Stein Discrepancy
Identify Kinase Substrate Relationships Using Dynamic Data
Configurable function for solving families of nonlinear
equations
k-Top Scoring Pairs for Microarray Classification
Datasets and functions from the (now non-existing) Faculty of
Life Sciences, University of Copenhagen
Calculation of Groundwater Mounding Beneath an Infiltration
Basin
Utility Functions by Youyi, Krisz and Others
Multi-Scale Motions Separation with Kolmogorov-Zurbenko
Periodogram Signals
Kolmogorov-Zurbenko Fourier Transform and Applications
Kolmogorov-Zurbenko Spatial Smoothing and Applications
Sparse Generalized Linear Model with L0 Approximation for
Feature Selection
l2boost - Friedman's boosting algorithm for regularized linear
regression
Ordination and Multivariate Analysis for Ecology
Relabelling MCMC Outputs of Mixture Models
Convert labels or tables to a dendrogram
Libreria Del Laboratorio Di Statistica Con R
Data Sets for the Book "Experimental Design for Laboratory
Biologists"
Estimation of indicators on social exclusion and poverty
Duncan test, Tukey test and Scott-Knott test
Local Approximate Gaussian Process Regression
Tools for the Analysis of Ecosystem Metabolism
Lake Temperatures Collected by Situ and Satellite Methods from
1985-2009
Collection of Internal Consistency Reliability Coefficients
Modeling Data with Functional Programming
Tools for Modeling Data with Functional Programming
Probabilistic Models to Analyze and Gaussianize Heavy-Tailed,
Skewed Data
Liquid Association for Network Dynamics Detection
Landmark Estimation of Survival and Treatment Effect
Landmark Prediction of a Survival Outcome
Radiometric and topographic correction of satellite imagery
Landsat 8 Imagery Rescaled to Reflectance, Radiance and/or
Temperature
Langevin Analysis in One and Two Dimensions
Data sets and functions with "Analyzing Linguistic Data: A
practical introduction to statistics"
Laplace Deconvolution with Noisy Discrete Non-Equally Spaced
Observations on a Finite Time Interval
Complete Environment for Bayesian Inference
Local Average Response Functions for Instrumental Variable
Estimation of Treatment Effects
Serialization Interface for Large List Objects
Least Angle Regression, Lasso and Forward Stagewise
Likelihood Analysis of Speciation/Extinction Rates from
Phylogenies
Modelling Interactions in High-Dimensional Data with
Backtracking
High-Dimensional Inference with the Penalized Score Test
L1 regularized regression (Lasso) solver using the Cyclic
Coordinate Descent algorithm aka Lasso Shooting
Draws Diagrams Useful for Checking Latent Scales
Latent Position and Cluster Models for Statistical Networks
Functions to Calculate Common Laterality Statistics in
Primatology
Density estimation and nonparametric regression on irregular
regions
Extra Graphical Utilities Based on Lattice
Multiresolution Kriging Based on Markov Random Fields
Complex Survey Structural Equation Modeling (SEM)
Client for 'Turfjs' for 'Geospatial' Analysis
Tools for Biostatistics, Public Policy, and Law
Latent Budget Analysis for Compositional Data
Limited Memory BFGS Minimizer with Bounds on Parameters
Length-biased correction to survival curve estimation
Latent Class Analysis (LCA) with familial dependence in extended
pedigrees
Data sets for package ``LMERConvenienceFunctions''
Extended Mixed Models Using Latent Classes and Latent Processes
Local Correlation, Spatial Inequalities, Geographically Weighted
Regression and Other Tools
Collapsed Gibbs Sampling Methods for Topic Models
Selection of Statistically Similar Research Groups
Interactive Visualization of Topic Models
Lan-DeMets Method for Group Sequential Boundaries
Linkage disequilibrium corrected by the structure and the
relatedness
Graphical display of pairwise linkage disequilibria between SNPs
LD LASSO Regression for SNP Association Study
Finding Locally D-optimal optimal designs for some nonlinear and
generalized linear models
Methods for likelihood-based dimension reduction in regression
Linear Dependence Statistics for High-Dimensional Data
Exact tests for Linkage Disequilibrium and Hardy-Weinberg
Equilibrium
Analysis and Visualization of Plant Leaf Angle Distributions
Rapid Digital Image Analysis of Leaf Area
Create Interactive Web Maps with the JavaScript 'Leaflet'
Library
Interactive Web-Maps Based on the Leaflet JavaScript Library
Constructing Gene Co-Expression Networks for Single-Cell
RNA-Sequencing Data Using Pseudotime Ordering
Likelihood Estimation of Admixture in Parents From Offspring
Genotypes
latent effect adjustment after primary projection
Functions for Learning Bayesian Inference
An Implementation of Crawford's and Wright's Learning Curve
Production Functions
Data and functions to accompany the book "Learning R"
An Interactive Environment for Learning Statistics
Phylogenetic and Functional Analyses for Ecology
Functions and datasets to accompany the book "Le logiciel R:
Maitriser le langage, Effectuer des analyses statistiques"
(french)
Tools for Data Handling and Analysis in Macroecology
Utilities for Formatting Strings with Consistent Capitalization,
Word Breaks and White Space
Plot Lexis Diagrams for Demographic Purposes
Extractive Summarization of Text with the LexRank Algorithm
Estimation of the Local False Discovery Rates by Type II Maximum
Likelihood Estimation
Calculation of Low Flow Statistics for Daily Stream Flow Data
Tools for linear grouping analysis (LGA)
Simulation and Estimation of Log-GARCH Models
Tests for Genetic Association/Gene-Environment Interaction in
Longitudinal Gene-Environment-Wide Interaction Studies
Set-Based Tests for Genetic Association in Longitudinal Studies
A set of methods for longitudinal data objects
Computational Routines for Proton and Ion Radiotherapy
Linear Predictive Models Based on the LIBLINEAR C/C++ Library
Linear Classification with Online Adaptation of Coordinate
Frequencies
Linearized Bregman Algorithms for Generalized Linear Models
Light Cone Reconstruction of States - Predictive State
Estimation From Spatio-Temporal Data
Sensitivity Analysis for Case Weight in Normal Linear Regression
Financial and Actuarial Mathematics for Life Contingencies
Two-Parameter HMD Model Life Table System
Compute the Top Decile Lift and Plot the Lift Curve
Tools for Communication with Lightning-Viz Server
Implementation of the 'Lights Out' Puzzle Game
Methods for Maximum Likelihood Estimation
Functions to Analyze and Visualize Likert Type Items
Linear Inverse Model examples and solution methods
Jitter/CI Plot with Ordered Points Below the Limit of Detection
Binning and Plotting of Linearly Referenced Data
Static Univariate Frequentist and Bayesian Linear Calibration
Functions to Explore L-Systems (Lindenmayer Systems)
The Lindley Distribution and Its Modifications
Minimum Distance Estimation in Linear Regression Model
Manipulate Formulas and Evaluate Marginal Effects
Tools for Generating, Visualizing, and Analysing Link
Communities in Networks
Linkage information based genotype imputation method
Interactive Interpretation of Linear Regression Models
Manipulation of Linear Systems of (in)Equalities
Implements Queue, PriorityQueue and Stack Classes
Fitting lasso penalised additive isotone models
Statistical Methods for the Item Count Technique and List
Experiment
Tests of independence based on the Longest Increasing
Subsequence
'htmlwidget' for Interactive Views of R Lists
Leveraging Learning to Automatically Manage Algorithms
Local Log-linear Models for Capture-Recapture
Add Standardized Regression Coefficients to lm-Objects
Linear Mixed-Effects Models using 'Eigen' and S4
Linear Mixed-Effects Models with Censored Responses
Linear Mixed Effects Models for Genome-Wide Association Studies
Linear Mixed Effects Models for QTL Mapping for Multienvironment
and Multitrait Analysis
Compute the Personalized Activity Index Based on a Negative
Binomial Model
Compute the Personalized Activity Index Based on a Flexible
Bayesian Negative Binomial Model
Linear Mixed Effects Models with Non-Stationary Stochastic
Processes
Model Selection and Post-hoc Analysis for (G)LMER Models
Bootstrap Methods for Nested Linear Mixed-Effects Models
Add smoothing spline modelling capability to nlme
Latent Markov Models with and without Covariates
Testing for a subset of variance components in linear mixed
models
Functions for estimation and inference of selection in
age-structured populations
Linear Mixed Effect Model Splines for Modelling and Analysis of
Time Course Data
L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments,
and Many Distributions
Regional frequency analysis using L-moments
Predicting Modulator and Functional/Survival Analysis
Identifying the Pathways Regulated by LncRNA Sets of Interest
Prioritizing Candidate LncRNAs Based on a Composite Multi-Level
Network
Functions for Performing Local FDR Estimation when Null and
Alternative are Poisson
Local Regression, Likelihood and Density Estimation
Test of Stationarity and Localized Autocovariance
Datasets for "Statistics: UnLocking the Power of Data"
Datasets for 'Statistics: Unlocking the Power of Data'
Genome-Wide Association Analysis of a Biomarker Accounting for
Limit of Detection
A simple logging system for R, based on log4j
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
Compute MLE of Log-Concave Density on R with Fixed Mode, and
Perform Inference for the Mode
Estimate a Log-Concave Probability Mass Function from Discrete
i.i.d. Observations
CoxPH Model with Log Concave Baseline Distribution
LOGICOIL: multi-state prediction of coiled-coil oligomeric
state
Firth's bias reduced logistic regression
Diagnostic Tests for Models with a Binomial Response
Functions, Data and Code for Binary and Binomial Data
Fitting l2-regularized logit choice models via generalized
gradient descent
Infer network based on binary arrays using regularized logistic
regression
Functions for the logitnormal distribution
Double log normal distribution functions
Log-Multiplicative Models, Including Association Models
Logrank Test for Aggregated Survival Data
Kernel Regression Smoothing with Local or Global Plug-in
Bandwidth
Package for Plotting Categorical Longitudinal and Time-Series
Data
Model-Based Clustering and Classification for Longitudinal Data
Statistics for Long-Memory Processes (Jan Beran) -- Data and
Functions
Sample Size Calculations for Longitudinal Data
Expand Short URLs Using the 'LongURL' API
Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian
Models
loop decomposition of weighted directed graphs for life cycle
analysis, providing flexbile network plotting methods, and
analyzing food chain properties in ecology
A Collection of Tools to Conduct Levins' Loop Analysis
Uses an Archive to Amend Previous Stages of a Pipe using Current
Output
Logistic Ordinal Regression Differential Item Functioning using
IRT
LOw Rand and sparsE Covariance matrix estimation
Missing Morphometric Data Simulation and Estimation
Runs Lotka's Law which is One of the Special Applications of
Zipf's Law
Lassoed principal components for testing significance of
features
Local polynomial estimators of intensity function or its
derivatives
Linear Parametric Models Applied to Hydrological Series
Local Polynomial Estimator in Measurement Error Models
Merging linkage maps by linear programming
Modeler for linear programs (LP) and mixed integer linear
programs (MILP)
Linear Predictor Score, for Binary Inference from Multiple
Continuous Variables
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
LP Nonparametric Approach to Non-Gaussian Non-Linear Time Series
Modelling
Dose Response Signal Detection under Model Uncertainty
Sources an R "Module" with Caching & Encapsulation, Returning
Exported Vars
Different Types of Estimators to Deal with Multicollinearity
A Likelihood Ratio Test Accounting for Genetic Heterogeneity
Locally stationary two-dimensional wavelet process estimation
scheme
A Multiscale Test of Spatial Stationarity for LS2W processes
Applied Latent Semantic Analysis (LSA) Functions
Least-Squares Bilinear Clustering for Three-Way Data
Local Statistical Complexity - Automatic Pattern Discovery in
Spatio-Temporal Data
Solving Least Squares Problems under Equality/Inequality
Constraints
American options pricing with Least Squares Monte Carlo method
Lysate and Secretome Peptide Feature Plotter
Companion to "Learning Statistics with R"
the accelerated failure time model to right censored data based
on least-squares principle
Simulation-Based Bayesian Inference for Latent Traits of Item
Response Models
Longitudinal Targeted Maximum Likelihood Estimation
LTPD and AOQL Plans for Acceptance Sampling Inspection by
Variables
Survival Trees to Fit Left-Truncated and Right-Censored Survival
Data
Ridge and Liu Estimates based on LTS (Least Trimmed Squares)
Method
Likelihood inference from case-control data Under Covariate
Assumptions (LUCA)
Printing Floating Point Numbers in a Human-Friendly Format
Comprehensive Luminescence Dating Data Analysis
Lunar Phase & Distance, Seasons and Other Environmental Factors
A Latent Variable Model for Mixed Continuous and Ordinal
Responses
An Automated Approach to Evaluating Dose-Effect Experiments
Following Litchfield and Wilcoxon (1949)
Accurate Estimation of Clonal Coincidences and Abundances from
Biological Replicates
Data from the M4 Time Series Forecasting Competition
Binary and Multiclass Boosting Algorithms
Machina Time Series Generation and Backtesting
Retrieve Data from MacLeish Field Station
Class prediction based on microarray data and clinical
parameters
Automatic Differentiation of Multivariate Operations
A Flexible Microarray Data Simulation Model
Data Class and Tools for Handling Spatial-Temporal Data
Pretty Scientific Plotting with Minor-Tick and Log Minor-Tick
Support
Magnetic Laplacian Matrix and Magnetic Eigenmap Visualization
A Graphical User Interface for Microarray Data Analysis
Creates an empty package framework for the LCFD format
Quantitative Analysis of Mass Spectrometry Data
A wrapper around the Java machine learning tool MALLET
Calculation of Minimum Averaged Mean Squared Error (MAMSE)
weights
Matrix Analysis and Normalization by Concordant Information
Enhancement
Interactive Q-Q and Manhattan Plots Using 'plotly.js'
Access and Process Data and Documents of the Manifesto Project
Manly Mixture Modeling and Model-Based Clustering
Analysis of Multivariate Data and Repeated Measures Designs
Multiple testing procedures of Cox (2011) and Wang and Cox
(2007)
Mapping Markers to the Nearest Genomic Feature
Mapping Smoothed Effect Estimates from Individual-Level Data
Geographic Display of Survey Data Statistics
Tools for Reading and Handling Spatial Objects
Mapping, pruning, and graphing tree models
Interactive Viewing of Spatial Objects in R
Multivariate Autoregressive Modeling for Analysis of Community
Time-Series Data
Multiplicative AR(1) with Seasonal Processes
Estimation of Meiotic Recombination Rates Using Marey Maps
Approximate marginal inference for regression-scale models
Mark-Recapture Analysis for Survival and Abundance Estimation
Markov Chain Models for Phylogenetic Trees
Easy Handling Discrete Time Markov Chains
Statistical Significance of the Markowitz Portfolio
Multivariate Analysis Based on Relative Likelihoods
Import, Plot and Analyze Bathymetric and Topographic Data
An algorithm for least-squares curve fitting
Mandallaz' Model-Assisted Small Area Estimators
Build Data Structures for Common Statistical Analysis
Support Functions and Datasets for Venables and Ripley's MASS
Body Mass Estimation Equations for Vertebrates
ML and MCMC Methods for Pedigree Reconstruction and Analysis
Model-Averaged Tail Area Wald (MATA-Wald) Confidence Interval
Multivariate and Propensity Score Matching with Balance
Optimization
Computation of the Balance - Sample Size Frontier in Matching
Methods for Causal Inference
MatchIt: Nonparametric Preprocessing for Parametric Casual
Inference
Combining Matching and Linear Regression for Causal Inference
Optimal Multilevel Matching using a Network Algorithm
A Code Converter from the Matlab/Octave Language to R
Tools to Assess Mating Potential in Space and Time
Measuring Association and Testing Independence Efficiently
An Interface for MATLAB using System Calls
Matrix Functions for Teaching and Learning Linear Algebra and
Multivariate Statistics
Sparse and Dense Matrix Classes and Methods
Collection of functions for matrix calculations
Matrix eQTL: Ultra fast eQTL analysis via large matrix
operations
Normalized Laplacian Matrix and Laplacian Map
Modelling with Sparse And Dense Matrices
Matrix-Based Partial Least Squares Estimation
Functions that Apply to Rows and Columns of Matrices (and to
Vectors)
Data.frame-Like Operations on Sparse and Dense Matrix Objects
Modern Calibration Functions for the Modern Analog Technique
(MAT)
Three methods to identify differentially expressed gene sets,
ordinary least square test, Multivariate Analysis Of Variance
test with n contrasts and Random forest
Exact max-type Cochran-Armitage trend test(CATT)
Low-memory Multinomial Logistic Regression with Support for Text
Classification
Selecting the Best Set of Relevant Environmental Variables along
with the Optimal Regularization Multiplier for Maxent Niche
Modeling
Maximum Likelihood Estimation and Related Tools
Model species distributions by estimating the probability of
occurrence using presence-only data
Orthogonal Data Projections with Maximal Skewness
Mazama Science Spatial Data Download and Utility Functions
Maxwell Boltzmann Bose Einstein Fermi Dirac Distribution and
Destruction Rate Modelling
Moment-Based Estimation for Hierarchical Models
Nucleic Acid Melting Curve Analysis on Microbead Surfaces with R
Model Based Multifactor Dimensionality Reduction
Access Data from the Massachusetts Bay Transit Authority (MBTA)
Web API
Multivariate Bayesian Variable Selection Method Exploiting
Dependence among Outcomes
Tools for Two-Dimensional Monte-Carlo Simulations
Translates information from netcdf files with MC2 output into
inter-PVT transitions
Matrix Computation Based Identification Of Prime Implicants
Functions to Support the Multicriteria Decision Aiding Process
Maximum Likelihood Estimation for Generalized Linear Mixed
Models
Machine Coded Genetic Algorithms for Real-Valued Optimization
Problems
Warnes and Raftery's MCGibbsit MCMC diagnostic
Multivariate Covariance Generalized Linear Models
Global optimization using Monte Carlo and Quasi Monte Carlo
simulation
Monte Carlo hypothesis tests with Sequential Stopping
Multiplicative Competitive Interaction (MCI) Model
IRT models for multiple choice items (mcIRT)
Estimating Conditional Auto-Regression (CAR) Models using Monte
Carlo Likelihood Methods
Gaussian Mixture Modelling for Model-Based Clustering,
Classification, and Density Estimation
Posterior Distribution of Extreme Value Models in R
Bayesian Analysis of Multivariate Counts Data in DNA
Metabarcoding and Ecology
Multiple Criteria Optimization Algorithms and Related Functions
Conjoint Analysis through Averaging of Multiple Analyses
Estimating Preferential Attachment from a Single Network
Snapshot by Markov Chain Monte Carlo
Multiple Comparisons Using Normal Approximation
A Simplified Interface for Running Commands on Parallel
Processes
A Monte Carlo permutation method for multiple test correlation
Design and Analysis of Dose-Finding Studies (see also
DoseFinding package)
Functions for Monte Carlo Methods with R
Selecting Bandwidth for Kernel Density Estimator with Minimum
Distance Method
Mixture and Flexible Discriminant Analysis
Multivariate Data Analysis for Chemometrics
Measuring the Difference Between Two Empirical Distributions
Multivariate Double Hierarchical Generalized Linear Models
Multi-Dimensional MA Normalization for Plate Effect
Detect gene-gene interactions using multifactor dimensionality
reduction
Improved Score Tests for Generalized Linear Models
Functions for Analysis of Data with General Recognition Theory
Detection and Control of Tree-Ring Widths on Scanned Image
Sections
Maximum Entropy Bootstrap for Time Series
Bayesian Methods for Identifying the Most Harmful Medication
Errors
Flexible Mediation Analysis Using Natural Effect Models
Medical Risk and Comorbidity Tools for ICD-9-CM Data
A max-margin supervised Sparse Topical Coding Model
Multivariate Data Handling in Ecology and Biogeography
Multivariate Data Handling with S4 Classes and Sparse Matrices
Multiscale Clustering of Geometrical Network
Interactive model exploration using GGobi
Spatial pattern detection in genetic distance data using Moran's
Eigenvector Maps
Tools for Management of Survey Data and the Presentation of
Analysis Results
Data sets from Mixed-effects Models in S
Tools for Analyzing Mixed Effect Regression Models
Meta-Analysis for Diagnostic Test Studies
An Interactive Visualisation of Meta-Analysis as a Physical
Weighing Machine
Meta-analysis of genome-wide SNP association results
Probabilistic latent variable models for metabolomic data
Analysis of the 'Elements of Metacommunity Structure'
Evaluate Periodicity in Large Scale Data
MetaDE: Microarray meta-analysis for differentially expressed
gene detection
Metapopulation simulations for conserving salmon through
portfolio optimization
Fused Lasso Approach in Regression Coefficient Clustering
Comprehensive Research Synthesis Tools for Systematic Reviews
and Meta-Analysis
Inference in Meta Analysis and Meta Regression
Metaheuristic Optimization Framework for Preprocessing
Combinations
MetaIntegrator- Meta-Analysis of Gene Expression Data
Landscape and Range Expansion Simulation
Likelihood Inference in Meta-Analysis and Meta-Regression Models
Diagnostic and prognostic meta analysis (metamisc)
Bayesian Mixture Analysis for Metagenomic Community Profiling
Meta-Analysis of Studies with Non Statistically-Significant
Unreported Effects
Perform the Meta-Analysis for Pathway Enrichment Analysis (MAPE)
MetaPCA: Meta-analysis in the Dimension Reduction of Genomic
data
Creates CrossHairs Plots for Meta-Analyses
MetaQC: Objective Quality Control and Inclusion/Exclusion
Criteria for Genomic Meta-Analysis
Meta-Analysis using Structural Equation Modeling
Advanced Statistical Methods to Model and Adjust for Bias in
Meta-Analysis
Meta Analysis for SNP-Set (Sequence) Kernel Association Test
Meta-analysis for Classification Data and Correction to
Imperfect Reference
Spatio-Temporal Analysis and Mapping of Meteorological
Observations
Fitting and Plotting Tools for the Maximum Entropy Theory of
Ecology (METE)
Meth27QC: sample quality analysis, and sample control analysis
Functions for Analysis of Agreement in Method Comparison Studies
Full Bayesian Partition Model for Identifying Differentially
Methylated Loci
Detection of Differentially Methylated Regions using
MethylCap-Seq Data
Statistical Methods for Normalizing Metabolomics Data
Separate Metabolites into Likely Measurement Artifacts and True
Metabolites
Create Interactive Charts with the JavaScript 'MetricsGraphics'
Library
Test Metric and Null Model Statistical Performance
GUI Tool for Estimating Sample Sizes for Metabolomic Experiments
A Fixed Memeory Moving Expanding Window Average
Multivariate Functional Principal Component Analysis for Data
Observed on Different Dimensional Domains
Marginal Effects, Odds Ratios and Incidence Rate Ratios for GLMs
Simulating, Estimating and Diagnosing MGARCH (BEKK and mGJR)
Processes
Mixed GAM Computation Vehicle with GCV/AIC/REML Smoothness
Estimation
Structural Pursuit Over Multiple Undirected Graphs
Multivariate Response Generalized Linear Models
Model Averaging for Multivariate GLM with Null Models
Estimating Time-Varying Mixed Graphical Models
mgpd: Functions for multivariate generalized Pareto distribution
(MGPD of Type II)
Graphing map attributes and non-map variables in R
API Client for the MG-RAST Server of the US DOE KBase
Gene set analysis based on GSZ-scoring function and asymptotic
p-value
General Markov Chain Monte Carlo for Bayesian Inference using
adaptive Metropolis-Hastings sampling
Minimum Hellinger Distance Test for Normality
Inference for Hidden Markov and Semi-Markov Models
Multiple Hypothesis Testing for Variable Selection in
High-Dimensional Linear Models
Bayesian Model Selection in Logistic Regression for the
Detection of Adverse Drug Reactions
Missing Data Imputation and Model Checking
Multivariate Imputation by Chained Equations
Some Additional Multiple Imputation Functions, Especially for
'mice'
Demand Analysis with the Almost Ideal Demand System (AIDS)
Analysis with the Constant Elasticity of Substitution (CES)
function
Symmetric Normalized Quadratic Profit Function
Multivariate Independent Comparison of Observations
Promotion Time Cure Model with Mis-Measured Covariates
Methods for Taxonomic Classification of Prokaryotes
Utilities for Official Spanish Microdata
Use R Graphics Files as Microplots (Sparklines) in Tables in
LaTeX or HTML Files, and Output Data.frames to Org-Mode
Multiple Imputation by Distance Aided Donor Selection
Multiple Comparisons Procedures Based on Studentized Midrange
and Range Distributions
Implementing dispersal into species distribution models
Methods for the Indirect Estimation of Bilateral Migration
Graphical User Interface to the 'mi' Package
Multiple Imputation for Interval Censored Data
Model Implied Instrumental Variable (MIIV) Estimation of
Structural Equation Models
MIcrosimulation Lung Cancer (MILC) model
Multiple Imputation for Multivariate Binary Outcome
Multiple-Instance Logistic Regression with LASSO Penalty
Mixture summary method for multiple imputation
Data sets included in Utts and Heckard's Mind on Statistics
Maximal Information-Based Nonparametric Exploration R Package
for Variable Analysis
Implementation of the Well-Known Game to Clear Bombs from a
Given Field (Matrix)
Create a Mini Version of CRAN Containing Only Selected Packages
R Interface to the Levenberg-Marquardt Nonlinear Least-Squares
Algorithm Found in MINPACK, Plus Support for Bounds
Gene region-level testing procedure for SNP data, using the min
P test resampling approach
Derivative-free optimization algorithms by quadratic
approximation
An R Package for Linear Mixed Model Analyses
MINimal VALidation for Stoichiometric Reactions
Multidimensional Iterative Proportional Fitting and Alternative
Models
Mutant Identification through Probabilistic High throughput
Enabled NOrmalization
Computerized Adaptive Testing with Multidimensional Item
Response Theory
Miscellaneous Useful Functions Including LaTeX Tables, Kalman
Filtering and Development Tools
Miscellaneous Functions for the Correlation Coefficient
Microbiome Based Sum of Powered Score (MiSPU) Tests
'Correctly Analyse Disease Recurrence with Missing at Risk
Information using Population Mortality'
Nonparametric Missing Value Imputation using Random Forest
Handling Missing Values with Multivariate Data Analysis
Testing Homoscedasticity, Multivariate Normality, and Missing
Completely at Random
Mixed effects Score Test for continuous outcomes
Data Sets, Functions and Examples from the Book: "Modern
Industrial Statistics" by Kenett, Zacks and Amberti
Methods in Structural Reliability Analysis
Mixture of Student t Distributions using Importance Sampling and
Expectation Maximization
Tools for Multiple Imputation in Multilevel Modeling
Tools for multiple imputation of missing data
Estimation/Multiple Imputation for Mixed Categorical and
Continuous Data
Multivariate Normal Mixture Models and Mixtures of Generalized
Linear Mixed Models Including Model Based Clustering
Mixed effects cumulative link and logistic regression models
Missing Data Imputation for Continuous and Categorical Data
using Nonparametric Bayesian Joint Models
Tools for Discrete Multivariate Mixed Membership Models
Estimation Methods for Stochastic Differential Mixed Effects
Models
Design and Analysis of Mixture Experiments
Evaluation of the FIM in NLMEMs using MCMC
Model Based Clustering, Classification and Discriminant Analysis
Using the Mixture of Generalized Hyperbolic Distributions
Mixed Model ANOVA and Statistics for Education
Functions to fit mixtures of regressions
A Random-Forest-Based Approach for Imputing Clustered Incomplete
Data
Forensic Genetics DNA Mixture Separation
Simulating Data to Study Performance of Clustering Algorithms
Fitting Finite Mixture of Scale Mixture of Skew-Normal
Distributions
DE Analysis of RNA-Seq Data by Mixtures of NB
Tools for Analyzing Finite Mixture Models
Curve Fitting and Mixture Toxicity Assessment
Mixture Models for Clustering and Classification
Multi-species sIZE spectrum modelling in R
2D and 3D movement-based kernel density estimates (MKDEs)
Kinetic Evaluation of Chemical Degradation Data
Efficient multi-level k-circulant supersaturated designs
Latent Class Item Response Theory (LC-IRT) Models under
Within-Item Multidimensionality
Machine Learning-based Differential Network Analysis of
Transcriptome Data
Exploratory Data Analysis and Manipulation of Multi-Label Data
Sets
R Ultimate Multilabel Dataset Repository
Machine learning algorithms with unified interface and confusion
matrices
Computation of the MLE for bivariate (interval) censored data
Maximum Likelihood Estimates of Gaussian Processes
Independent Component Analysis using Maximum Likelihood
ML estimation under multivariate linear mixed models with
missing values
Examples from Multilevel Modelling Software Review
Bayesian Model Averaging for Multinomial Logit Models
Multi-Label Prediction Using Gibbs Sampling (and Classifier
Chains)
A package for Multilinear Regression Model Population Analysis
Use the MLS Junk Generator Algorithm to Generate a Stream of
Pseudo-Random Numbers
Most Likely Transformations: Documentation and Regression Tests
Single-Sample Classifier of Medulloblastoma Subtypes for
Medulloblastoma Patient Samples, Mouse Models, and Cell Lines
Gene Expression Datasets for the 'MM2S' Package
Mathematical Morphology in Any Number of Dimensions
Estimation of Multinormal Mixture Distribution
an R package for analyzing multivariate longitudinal data with
multivariate marginal models
Multivariate marginal models with shared regression parameters
Multi-Marker Molecular Signature for Treatment-specific Subgroup
Identification
Modern Measures of Population Differentiation
Various Similarity and Distance Metrics for Marked Point
Processes
Markov Modulated Poisson Process for Unsupervised Event
Detection in Time Series of Counts
Model-Based Clustering and Classification with Mixtures of
Modified t Factor Analyzers
Convert Dates to MMWR Day, Week, and Year
Multivariate Nonparametric Methods. An Approach Based on Spatial
Signs and Ranks
Multivariate Normal Distributions with Power Integrand
The Multivariate Normal and t Distributions
R Package for Fitting the Multinomial Probit Model
Multi-objective optimization for collecting cluster alternatives
Extraction of Bands from MODIS Surface Reflectance Product MOD09
NRT
Multiscale Analysis for Density Functions
Model-free estimation of a psychometric function
A Collection of Useful Custom Tools for D&A and Modelling
Modeling and Map Production using Random Forest and Stochastic
Gradient Boosting
A Model Object Framework for Regression Analysis
Tools and Classes for Statistical Models
Find the Modes and Assess the Modality of Complex and Mixture
Distributions, Especially with Big Datasets
R tools for processing Level 2 Cloud Mask products from MODIS
Community Structure Detection via Modularity Maximization
Modelling temperature effects using time series data
Multiobjective Genetic Algorithm for Variable Selection in
Regression
Dental Surface Complexity Measurement Tools
Moment-Matching Methods for Weighted Sums of Chi-Squared Random
Variables
Moments, cumulants, skewness, kurtosis and related tests
A Simple Graphical Representation of the Relative Occurrence and
Co-Occurrence of Events
Monotone Multi-Layer Perceptron Neural Network
Geometric Morphometric Analysis of Monogenean Anchors
Estimation for Multivariate Normal and Student-t Data with
Monotone Missingness
Allows to Explore Monophyly (or Lack of it) of Taxonomic Groups
in a Phylogeny
Functions and Datasets for the Book by Keon-Woong Moon
MOPSOCD: Multi-objective Particle Swarm Optimization with
Crowding Distance
Check Time Homogeneity and Markov Chain Order
Color schemes compatible with red-green color perception
difficulties
Calculations and Visualisations Related to Geometric
Morphometrics
MOdelling Tools for Reproduction and Survival Data in
Ecotoxicology
Simple raw data generator based on user-specified summary
statistics
Smoothing and Forecasting Poisson Counts with P-Splines
Project MOSAIC Statistics and Mathematics Teaching Utilities
Learning Hybrid Bayesian Networks using Mixtures of Truncated
Basis Functions
Mountain Plots, Folded Empirical Cumulative Distribution Plots
Mouse-Tracking Measures from Trajectory Data
Visualizing and Analyzing Animal Track Data
Animal Movement Modelling using Hidden Markov Models
Mixtures of von Mises-Fisher Distributions
Multi-Patient Analysis of Genomic Markers
Multinomial Probit Bayesian Additive Regression Trees
Multivariate Process Capability Indices (MPCI)
Data sets and scripts for Modeling Psychophysical Data in R
The package can implement the network-based metabolite pathway
identification of pathways
Modified Profile Likelihood Estimation for Weibull Shape and
Regression Parameters
Graphical Model Stability and Variable Selection Procedures
Automating Mplus Model Estimation and Interpretation
Symbolic Computation and More with Multivariate Polynomials
Mposterior: R package for Robust and Scalable Bayes via a Median
of Subset Posterior Measures
Statistics for analysing multiple simultaneous point processes
on the real line
Modeling Phylogenetic Signals using Eigenvector Maps
Analyze Multinomial Processing Tree Models
Data Sets from Montgomery, Peck and Vining's Book
Metabolomic Quantitative Trait Locus Mapping
Inferences for ratios of coefficients in the general linear
model
Methods for Analyzing Multiple Response Categorical Variables
(MRCVs)
Fits regression models when the outcome is partially missing
Marine Regions Data from 'Marineregions.org'
Multi-Resolution Estimation of the Hazard Rate
Modified Rand Index (1 and 2.1 and 2.2) and Modified Adjusted
Rand Index (1 and 2.1 and 2.2)
An R package for conditional maximum likelihood estimation in
mixed Rasch models
Multilocus Random Mixed Linear Model for Genome-Wide Association
Study and Linkage Analysis
Multivariate Regression Models for Reserving
R package for parallelized mRMR ensemble feature selection
Minimal Clinically Important Difference and Response Shift
Effect for Health-Related Quality of Life
Multi-Resolution Scanning for Cross-Sample Differences
Multinomial Response Models with Structured Penalties
A multiplicative-regression model for relative survival
Multiresolution time warping for functional data
Statistical analysis for Methylation-sensitive Amplification
Polymorphism data
Draw Diagrams (mis)Representing the Results of Mass Spec
Experiments
Multiscale Bernstein Polynomials for Densities
Markov-Switching, Bayesian, Vector Autoregression Models
Multivariate Synthetic Control Method Using Time Series
Combine Data from Positive and Negative Ionization Mode Finding
Common Entities
R Client for the Microsoft Cognitive Services Text Analytics
REST API
R Client for the Microsoft Cognitive Services Web Language Model
REST API
Metabolite set enrichment analysis for factor loading in
principal component analysis
Preprocessing of Gas Chromatography-Mass Spectrometry (GC-MS)
data
Data and Functions for the Book Modern Statistical Graphics
High Dimensional Multiclass Classification Using Sparse Group
Lasso
A library to serialize or unserialize data in MessagePack format
Degrees of freedom of elastic net, adaptive lasso and
generalized elastic net
Assess Tumor Microsatellite Instability with a Decision Tree
Classifier from Exome Somatic Mutations
Improved Techniques to Estimate Trend, Velocity and Acceleration
from Sea Level Records
Multi-State Markov and Hidden Markov Models in Continuous Time
Functions and Datasets for "Methods of Statistical Model
Estimation"
Building Augmented Data to Run Multi-State Models with 'msm'
Package
Datasets and Functions used in Multivariate Statistics: Old
School by John Marden
Morse-Smale Approximation, Regression and Visualization
Package for Calculation of ARMSS, Local MSSS and Global MSSS
Nonparametric Estimation for Multistate Models
Data Preparation, Estimation and Prediction in Multi-State
Models
Read Data from Delimited 'MTConnect' Data Files and Perform some
Analysis
All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS)
and Estimating Multivariate Volatility Models
Multivariate time series data imputation
Munich Franz-Josef-Strauss Airport Pattern Analysis
Data on Freedom of Information Act Requests
Hazard Function Estimation in Survival Analysis
Exploring Data with Tree Data Structures
Optimal Allocation in Stratified Sampling
Simultaneous Inference in General Parametric Models
Multiple Equivalence Tests and Simultaneous Confidence Intervals
GEE Solver for Correlated Nominal or Ordinal Multinomial
Responses
Finite Difference Method for Multi-Asset Option Valuation
Quantitative Linkage Analysis Tools using the Variance
Components Approach
Multiple Copy Number Variation Detection
Permutations of Multisets in Cool-Lex Order
Multivariate Analysis and Visualization for Biological Data
Read Fixed Width Format Files Containing Lines of Different Type
Multidimensional Latent Class Item Response Theory Models
Capture-Mark-Recapture Analysis using Multiple Non-Invasive
Marks
Meta-analysis of Multivariate Genome Wide Association Studies
Regression analysis of overdispersed correlated count data
Simultaneous confidence intervals for multinomial proportions
according to the method by Sison and Glaz
Robust Estimation of Overdispersed Multinomial Regression Models
Generation of Multivariate Ordinal Variates
Infrastructure to Assemble Multi-Panel Figures (from Grobs)
A Package to Test for Pleiotropic Effects
Variable Importance Analysis with Population Intervention Models
Weighted Cox-Regression for Nested Case-Control Data
Algebraic Tools for the Analysis of Multiple Social Networks
Data Manipulation with Parallelism and Shared Memory Matrices
Calculate Multivariate Richness via UTC and sUTC
Bias, Precision, and Power for Multi-Level Random Regressions
Clustering a Dataset using Multi-SOM Algorithm
MultiSV: an R package for identification of structural
variations in multiple populations based on whole genome
resequencing
Multivariate Random Forest for Linearly Related Output Features
Estimation of Multivariate Long-Memory Models Parameters
Common Multiple Testing Procedures and Gatekeeping Procedures
Metabolomics Univariate and Multivariate Analysis
Interpolate Munsell Renotation Data from Hue/Chroma to CIE/sRGB
Murphy Diagrams for Forecast Comparisons
Conversion of Nuclear Magnetic Resonance spectrum in audio file
A Graphical User Interface for the MuToss Project
MultiClass Visualizable Classification using Combination of
Projections
An Introduction to Applied Multivariate Analysis with R
Statistical Methods for Analysing Multivariate Abundance Data
Modelling Multivariate Binary Data with Blocks of Specific
One-Factor Distribution
Workspace organization, code and documentation editing, package
prep and editing, etc
Multivariate Variance Components Tests for Multilevel Data
Wavelet analysis of multiple time series
Multivariate Generalized Linear Mixed Models for Ranking Sports
Teams
Influence Measures and Diagnostic Plots for Multivariate Linear
Models
Multivariate Linear Model with Analytic p-Values
Multivariate Meshes and Histograms in Arbitrary Dimensions
Multivariate and Univariate Meta-Analysis and Meta-Regression
Multivariate Comparative Tools for Fitting Evolutionary Models
to Morphometric Data
Nelson-Aalen estimator of the cumulative hazard in multistate
models
Moving Grid Adjustment in Plant Breeding Field Trials
ML estimation for multivariate normal data with missing values
Normality test for multivariate variables
Generate New Multivariate Normal Samples from Permutations
Goodness of Fit Tests for Multivariate Normality
Multivariate outlier detection based on robust methods
Multivariate Peaks-over-Threshold Modelling for Spatial Extreme
Events
Orthant Probability of the Multivariate Normal Distribution
Mean and Variance of Truncated Normal Distribution
Generalized Shapiro-Wilk test for multivariate normality
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
Causal Inference in Spatiotemporal Event Data
Multichannel Wavelet Deconvolution with Additive Long Memory
Noise
Penalized Moving-Window Lasso Method for Genome-Wide Association
Studies
Efficient mixed-level k-circulant supersaturated designs
Integrative immunoinformatics for Mycobacterial diseases in R
platform
Automatic Correlation and Regression Test in a Data Frame
Interface to Myrrix. Myrrix is a complete, real-time, scalable
clustering and recommender system, evolved from Apache Mahout
External jars required for package Myrrix
Regression Models for Monozygotic Twin Data
Wraps 'libnabo', a Fast K Nearest Neighbour Library for Low
Dimensions
Nondetects And Data Analysis for environmental data
Provide namespace managment functions not (yet) present in base
R
Tools for Nanoparticle Simulation and Calculation of PDF and
Total Scattering Structure Function
Normalize NanoString miRNA and mRNA Data
Performs the Processing and Normalisation of Nanostring miRNA
and mRNA Data
Collection of datasets from the ASA 2006 data expo
NeuroAnatomy Toolbox for Analysis of 3D Image Data
NeuroAnatomy Toolbox ('nat') Extension for Assessing Neuron
Similarity and Clustering
NeuroAnatomy Toolbox ('nat') Extension for Handling Template
Brains
File System Utility Functions for 'NeuroAnatomy Toolbox'
Maximum Likelihood method in estimating effective population
size from genetic data
Bayes Classifier for Verbal Autopsy Data
Determining the Best Number of Clusters in a Data Set
Vignette Engine Wrapping IPython Notebooks
NBD-Dirichlet Model of Consumer Buying Behavior for Marketing
Research
Functions for Optimal Non-Bipartite Matching
Negative Binomial Models for RNA-Sequencing Data
NCA Calculation and Population PK Model Diagnosis
Interface to Unidata netCDF (Version 4 or Earlier) Format Data
Files
Helper functions for use with the ncdf4 package
Miscellaneous Functions for Creating Adaptive Functions and
Scripts
Regularization Paths for SCAD and MCP Penalized Regression
Models
Efficient Network Enrichment Analysis Test
Calculating Effective Sizes Based on Known Demographic
Parameters of a Population
Estimating the Number of Essential Genes in a Genome
Access to the Neotoma Paleoecological Database Through R
Network Assisted Algorithm for Epigenetic Studies Using Mean and
Variance Combined Signals
Survival Analysis for Cohorts with Missing Covariate Information
Mann-Whitney-Wilcoxon Test for Nested Ranks
Inference of Species Associations from Co-Occurrence Data
netClass: An R Package for Network-Based Biomarker Discovery
Statistical Modeling with Network Cohesion
Network Analysis for Diffusion of Innovations
Network Generator for Combinatorial Graph Problems
Estimating network indices, including trophic structure of
foodwebs in R
Network Meta-Analysis using Frequentist Methods
Origin Estimation for Propagation Processes on Complex Networks
Permutation Testing Network Module Preservation Across Datasets
Network Strengths and Weaknesses Analysis
Tools for using Network Reporting Estimators
Simulate Bipartite Graphs with Fixed Marginals Through
Sequential Importance Sampling
Visualization and Analysis Tools for Neural Networks
Data Structures and Handling for Neuroimaging Data
Functions to Generate fMRI Data Including Activated Data, Noise
Data and Resting State Data
Computes Pdf, Cdf, Quantile and Random Numbers, Measures of
Inference for 19 General Families of Distributions
Parallel Analysis and Non Graphical Solutions to the Cattell
Scree Test
Numerical Formal Concept Analysis for Systematic Clustering
A Simple General Purpose N-Gram Tokenizer
Fitting the Centered Autologistic and Sparse Spatial Generalized
Linear Mixed Models for Areal Data
Data from the US National Health and Nutrition Examination Study
Non-hierarchical evolutionary multi-objective tree learner to
perform cost-sensitive classification
Compiling the NHL Real Time Scoring System Database for easy use
in R
Bayesian NHMM Modeling (Multiple Time Series)
Non-Homogeneous Markov Switching Autoregressive Models
Modelling and Validation of Non Homogeneous Poisson Processes
(Niche) (R)egion and Niche (Over)lap Metrics for
Multidimensional Ecological Niches
Fast and Accurate Trisomy Prediction in Non-Invasive Prenatal
Testing
Nonlinear least squares examples from NIST
Fundamental Physical Constants and Unit Conversions from NIST
Noninferiority Tests with Variable Margins
Solve Nonlinear Optimization with Nonlinear Constraints
Linear and Nonlinear Mixed Effects Models
Non-linear mixed-effects modelling in nlme using differential
equations
Datasets and utility functions enhancing functionality of nlme
package
Functions for Nonlinear Least Squares Solutions
Nonlinear Network Reconstruction and Clustering Based on DCOL
(Distance Based on Conditional Ordered List)
Higher Order Inference for Nonlinear Heteroscedastic Models
Non-Linear Relative Risk Estimation and Plotting
Fitting Structural Equation Mixture Models
Non-Linear Shrinkage Estimation of Population Eigenvalues and
Covariance Matrices
Nonlinear regression in predictive microbiology
Fitting nonlinear models with scale mixture of skew-normal
distributions
Utilities and Kinship Information for Research with the NLSY
A nondecimated lifting transform for signal denoising
Wald Test of Nonlinear Restrictions and Nonlinear CI
Algorithms and Framework for Nonnegative Matrix Factorization
(NMF)
Non-Negative Matrix Factorization (NMF) using CUDA
Normalized Mutual Information of Community Structure in Network
Numerical Methods and Optimization in Finance
Feed-Forward Neural Networks and Multinomial Log-Linear Models
Prediction Intervals of Multi-Layer Neural Networks
Non-Negative Lasso and Elastic Net Penalized Generalized Linear
Models
Fast and Versatile Non-Negative Matrix Factorization
The Lawson-Hanson algorithm for non-negative least squares
(NNLS)
Calculate Design Parameters for Biomarker Validation Studies
Node Harvest for Regression and Classification
Compares the Distribution of Sister Clades Through a Phylogeny
Implementation of the Natural and Orthogonal InterAction (NOIA)
model
Estimation of Intrinsic and Extrinsic Noise from Single-Cell
Data
Label Noise Filters for Data Preprocessing in Classification
Biplot representations of categorical data
U.S. Census Regional and Demographic Data
Causal Inference in the Presence of Treatment Noncompliance
Under the Binary Instrumental Variable Model
Loading NONMEM Output Files and Simulate with Parameter
Uncertainty
Nonparametric Methods for Measuring Efficiency and Productivity
Model Checking and Variable Selection in Nonparametric
Regression
Stratification and matching by the propensity score
Detecting Isotope, Adduct and Homologue Relations in LC-MS Data
Quantized simulation data of isotope pattern centroids
Normal (1-d) Mixture Models (S3 Classes and Methods)
Dataset for Climate Analysis with Data from the Nordic Region
Analysis of multivariate normal datasets with missing values
Analysis of Incomplete Multivariate Data under a Normal Model
Routines for Exponential Power Distribution
Evaluates complex erf, erfc, Faddeeva, and density of sum of
Gaussian and Student's t
Generation of Multivariate Data with Arbitrary Marginals
Neyman Smooth Tests of Normality for the Errors of ARMA Models
Send push notifications to your smartphone via pushover.net
(ACCOUNT REQUIRED!)
NOVEL Integration of the Sample and Thresholded (NOVELIST)
Correlation and Covariance Estimators
Nonparametric kernel smoothing methods for mixed data types
Non-Parametric Measures of Actigraphy Data
Multiple Comparisons and Simultaneous Confidence Intervals
Nonparametric Analysis of Longitudinal Data in Factorial
Experiments
Non-Parametric Bayesian Multiple Imputation for Categorical Data
Nonparametric Combination of Hypothesis Tests
Nonparametric Methods for Cognitive Diagnosis
Some Nonparametric Tests for Change-Point Detection in Possibly
Multivariate Observations
Normalised prediction distribution errors for nonlinear
mixed-effect models
Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry
Data
Sample Size Calculation for the Proportional Hazards Mixture
Cure Model
Nonparametric Interaction Tests for Factorial Designs with
Repeated Measures
Plotting linkage and association results
Type-Specific Failure Rate and Hazard Rate on Competing Risks
Data
Nonparametric maximum likelihood estimation for random effect
models
tertiary probabilistic model in predictive microbiology for use
in food manufacture
Nonparametric Comparison of Multivariate Samples
Nonparametric Partially-Balanced Incomplete Block Design
Analysis
Nonparametric Estimation of Regression Models with
Factor-by-Curve Interactions
Kernel-Based Nonparametric ROC Regression Modelling
Convenience Functions and Tests for Working With the Net
Promoter Score (NPS)
Nonparametric and Stochastic Efficiency and Productivity
Analysis
Nonparametric Smoothing for contaminated data using
Simulation-Extrapolation
Package for Nonparametric Statistical Methods using R
Generalization of Hewitt's Seasonality Test
Post-normalization of total copy numbers
Simulation and Estimation of the Neyman-Scott Type Spatial
Cluster Models
Elitist Non-dominated Sorting Genetic Algorithm based on R
Functions and Datasets to Accompany Hollander, Wolfe, and
Chicken - Nonparametric Statistical Methods, Third Edition
NUtrient Cycling and COMpetition Model Undisturbed Open Bog
Ecosystems in a Temperate to Sub-Boreal Climate
Numeric Routines for Optically Stimulated Luminescence Dating
Audioscrobbler data for "R in a Nutshell"
R functions for NetWorkSpaces and Sleigh
General Purpose 'Oai-PMH' Services Client
Multiple Sclerosis Lesion Segmentation using Magnetic Resonance
Imaging (MRI)
Outright Tool for the Analysis of Spatial Inequalities and
Segregation
Oblique Random Forests from Recursive Linear Model Splits
An R package to assess agreement between observers
Objective Bayesian Model Discrimination in Follow-Up Designs
Sensitivity analysis for Observational studies
Visualisation of Oceanographic Data and Model Output
Regression for Rank-Indexed Compositional Data
Open Document Databases (.odb) management
Support for odfWeave on the survey package
Estimation of Ordered Generalized Linear Models
Survival analysis supplement to OpenIntro guide
Multivariate Methods Based on the Oja Median and Related
Concepts
OkCupid Profile Data for Introductory Statistics and Data
Science Courses
Retrieve Oklahoma Mesonet climatological data
filter the molecular descriptors for QSAR
Maximum likelihood tree models for oncogenesis
Planing, Monitoring and Evaluating Oncological Phase 2 Studies
Software for constructing genetic maps in experimental crosses:
full-sib, RILs, F2 and backcrosses
One Rule Machine Learning Classification Algorithm with
Enhancements
Efficient Authenticated Interaction with the O*NET API
Detect Changepoints in Multivariate Time Series
Functions for Visualising Sets of Ontological Terms
Functions for Calculating Ontological Similarities
Opasnet Modelling Environment Utility Functions
Option Pricing and Estimation of Financial Models in R
Client to Access 'Openaddresses.io' Data
Tools for the Analysis of Air Pollution Data
Embedded Scientific Computing and Reproducible Research with R
OpenIntro data sets and supplemental functions
Control number of OpenMP threads dynamically
Apache OpenNLP Jars and Basic English Language Models
Toolkit for Encryption, Signatures and Certificates Based on
OpenSSL
Tools for Creating and Analysing Air Trajectory Data
Utilities for Working with R's Operators
Optimal Combinations of Diagnostic Tests Based on AUC
Estimation of optimal number of biomarkers for two-group
microarray based classifications at a given error tolerance
level for various classification rules
Determine Optimal Clustering Algorithm and Number of Clusters
Optimal Designs for Estimating the Slope Divided by the
Intercept
Tools to Support Optimization Possibly with Bounds and Masks
Near-Optimal and Balanced Group-Sequential Designs for Clinical
Trials with Continuous Outcomes
Estimation of value and hedging strategy of call and put
options
Computing optimal cutpoints in diagnostic tests
A Replacement and Extension of the 'optim' Function
R port of the Scilab optimsimplex module
A Replacement and Extension of the optim() Function
Optimal Two and Three Stage Designs for Single-Arm and Two-Arm
Randomized Controlled Trials with a Long-Term Binary Endpoint
Option Pricing with Efficient Simulation Algorithms
Simplifies and Automates Analyzing and Reporting OptiQuant's log
Data
Optimum Contribution Selection and Pedigree Analysis
Optimal Mixture Weights in Multiple Importance Sampling
Optimal Partitioning of Similarity Relations
Optimization Toolbox for solving linear systems
Convenient Tools for Working with Oracle Databases
Computation of Graphlet Orbit Counts in Sparse Graphs
Several confidence intervals for the odds ratio
Order Restricted Clustering for Microarray Experiments
Estimate procedure in case of first order autocorrelation
Modelling comparison data with ordinal response
Estimate parent distributions with data of several order
statistics
Ordered Lasso and Time-lag Sparse Regression
Least Squares, Logistic, and Cox-Regression with Ordered
Predictors
Ordinal Regression Analysis for Continuous Scales
Ordinal Regression for High-dimensional Data
Biplot representations of ordinal variables
Compute least squares estimates of one bounded or two ordered
isotonic regression curves
Concurrent Generation of Ordinal and Normal Data with Given
Correlation Matrix and Marginal Distributions
Selection and/or Smoothing of Ordinal Predictors
An R Interface to the Oniguruma Regular Expression Library
Connector to the Objective Revision Evaluation Service (ORES)
Analyse Text Files Created by Emacs' Org mode
Order-restricted Information Criterion-based Clustering
Algorithm
Fast Spatial Ancestry via Flexible Allele Frequency Surfaces
The package deals with Operations Research LOCational Analysis
models
Rigorous - NIfTI + ANALYZE + AFNI : Input / Output
Order Restricted Assessment Of Microarray Titration Experiments
Southern Ocean Frontal Distributions (Orsi)
Converting Odds Ratio to Relative Risk in Cohort Studies with
Partial Data Information
Dynamic Panel Models with Orthogonal Reparameterization of Fixed
Effects
Collection of functions for orthogonal and orthonormal
polynomials
Orthogonal Signal Deconvolution for Spectra Deconvolution in
GC-MS and GCxGC-MS Data
Design and analysis of observational studies
Customisable Images of OpenStreetMap Data
Add a Scale Bar to 'OpenStreetMap' Plots
Interface Between R and the OpenStreetMap-Based Routing Service
OSRM
Optimal Trees Ensembles for Regression, Classification and Class
Membership Probability Estimation
Variable Selection for Optimal Treatment Decision
North Temperate Lakes - Microbial Observatory 16S Time Series
Data and Functions
Ornstein-Uhlenbeck Models for Phylogenetic Comparative
Hypotheses
Bayesian Reconstruction of Disease Outbreaks by Combining
Epidemiologic and Genomic Data
Basic Tools for the Analysis of Disease Outbreaks
Outlier Detection using quantile regression for Censored Data
Outlier Detection for Multi-replicated High-throughput Data
Functions for Solving Multiple-criteria Decision-making Problems
Analysis of Evolutionary Rates in an OU Framework
Estimates of Coefficient of Overlapping for Animal Activity
Patterns
Estimation of Overlapping in Empirical Distributions
Processing of Oxy-Bisulfite Microarray Data
Plot the Australian Coastline and States
Posterior Predictive Checks of Coalescent Models
Performance Attribution for Equity Portfolios
Summarize Daily Physical Activity from 'activPAL' Accelerometer
Data
Pabon Lasso Graphs and Comparing Situations of a Unit in Two
Different Times
PAC-Bayesian Estimation and Prediction in Sparse Additive
Models
Track R Package Downloads from RStudio's CRAN Mirror
A few Useful Functions for Statisticians
A Dependency Management System for Projects and their R Package
Dependencies
Procrustes Application to Cophylogenetic Analysis
Variational Bayes (VB) Approximation of Gibbs Posteriors with
Hinge Losses
Attributable Fraction Function for Censored Survival Data
Nonparametric Estimation of Preferential Attachment and Node
Fitness in Temporal Complex Networks
An API Client for Wikimedia Traffic Data
The package can identify the dysregulated KEGG pathways based on
global influence from the internal effect of pathways and
crosstalk between pathways
Pathway Analysis Methods for Genomewide Association Data
Confidence intervals for the ratio of locations and for the
ratio of scales of two paired samples
Visualization using Eulerian tours and Hamiltonian
decompositions
Rasch Model Parameters by Pairwise Algorithm
Confidence Intervals for Two Sample Comparisons
Significance Tests for Palaeoenvironmental Reconstructions
Download and Process Data from the Paleobiology Database
Analysis of Charcoal Records from the Global Charcoal Database
Geometric Morphometric Tools for Paleobiology
Paleontological and Phylogenetic Analyses of Evolution
Principal Axes Methods for Contingency Tables with Partition
Structures on Rows and Columns
Power Analysis for Random Effects in Mixed Models
Implementation of the Panel Data Approach Method for Program
Evaluation
Pam: prediction analysis for microarrays
Multiple Imputation for Multivariate Panel or Clustered Data
Benchmarking and Rescaling R2 using Noise Percentile Analysis
Preferential Attachment Based Common Neighbor Distribution
Derived Functional Associations
Estimation of Linear AR(1) Panel Data Models with
Cross-Sectional Heteroskedasticity and/or Correlation
Random Effects and/or Sample Selection Models for Panel Count
Data
A Semi-Parametric Test for Specifying Functional Form
View Medical Research Images using the Papaya JavaScript Library
A Toolbox for Writing Pretty Papers and Reports
Random Forest Classification with Parallel Computing
Automate parallelization of function calls by means of dynamic
code analysis
Unified Interface to Parallelization Back-Ends
Methods for combining independent subset Markov chain Monte
Carlo (MCMC) posterior samples to estimate a posterior density
given the full data set
A Parallel-Voting Algorithm for many Classifiers
Paralellised Versions of Constraint Based Causal Discovery
Algorithms
A Parallel-Voting Version of the Support-Vector-Machine
Algorithm
A Shiny GUI for some Parameter Estimation Examples
Helpers for Parameters in Black-Box Optimization, Tuning and
Machine Learning
Horn's Test of Principal Components/Factors
Regularized estimation of partial correlation matrices
Parallel implementation of the "segment" function of package
"DNAcopy"
Conduct the Parent-Offspring Test Using Monomorphic SNP Markers
Computing, Fitting and Validating the PPS Distribution
Parallelized functions for palaeoecological and
palaeogeographical analysis
Portfolio Allocation and Risk Management Applications
Parallel Mutual Information estimation for Gene Network
reconstruction
Model-Based Clustering with Regularization Methods for
High-Dimensional Data
Recognize and Parse Dates in Various Formats, Including All ISO
8601 Formats
Partitioning Using Deletion, Substitution, and Addition Moves
Compute a distance metric between two partitions of a set
Periodic Autoregressive Time Series Models
Preprocessing of Aligned Sequences from HTS Analyses
Prediction and Stability Selection of Tuning Parameters
Package for Analysis of Space-Time Ecological Series
Phylogenetic Assembly with Soft Taxonomic Inferences
Probability and Statistics with R, Second Edition
Communication Between Editor and Viewer for Literate Programs
A Tool for Identification of Differentially Expressed Pathways
using Multi-Statistic Comparison
Classification using biological pathways as prior knowledge
Basic functions for drawing path diagrams
Pathmox Approach of Segmentation Trees in Partial Least Squares
Path Modeling
Backwards Variable Selection for Paths using M Plus
Class-focused pattern metric comparisons using simulation
Bayesian Experimental Design for Systems Biology
Perceptual Analysis, Visualization and Organization of Spectral
Color Data in R
Adding Progress Bar to '*apply' Functions
Protracted Birth-Death Model of Diversification
Programming with Big Data -- Base Wrappers for Distributed
Matrices
Programming with Big Data -- Demonstrations and Examples Using
'pbdR' Packages
Programming with Big Data -- Distributed Matrix Methods
Programming with Big Data -- Interface to MPI
Programming with Big Data -- Interface to Parallel Unidata
NetCDF4 Format Data Files
Programming with Big Data --- MPI Profiling Tools
Programming with Big Data -- Scalable Linear Algebra Packages
Programming with Big Data -- Interface to ZeroMQ
A Set of Datasets Used in My Classes or in the Book 'Modele
Liniowe i Mieszane w R, Wraz z Przykladami w Analizie Danych'
Parametric Bootstrap and Kenward Roger Based Methods for Mixed
Model Comparison
Tracking the Progress of Mc*pply with Progress Bar
Mapping Fisheries Data and Spatial Analysis Tools
GUI Tools Made Easy: Interact with Models and Explore Data
Segmenting Multiple Time Series by Contemporaneous Linear
Transformation
Create 2D Principal Component Plots with Bootstrapping
Fast Principal Component Analysis for Outlier Detection
Methods for Graphical Models and Causal Inference
Semiparametric regression analysis of panel count data using
monotone splines
Principal Component of Explained Variance
Preconditioned Conjugate Gradient Algorithm for solving Ax=b
Piecewise Constant Hazards Models for Censored and Truncated
Data
Implementation of POSIXct work-alike for 365 and 360 day
calendars
IRT Models for Polytomous and Continuous Item Responses
Partial Correlation Coefficient with Information Theory
Principal Coordinates of Phylogenetic Structure
Calculate the probability of correct selection (PCS)
Panel-Corrected Standard Error Estimation in R
Cluster analysis via nonparametric density estimation
Fetch Economic and Financial Time Series Data from Public
Sources
Extract Text and Data from PDF Documents
Proximal/distal modeling framework for Pavlovian conditioning
phenomena
Panel Dynamic OLS Estimation of Cointegrating Vectors
PDQ Functions via Gram Charlier, Edgeworth, and Cornish Fisher
Approximations
Threshold Model and Unit Root Tests in Panel Data
Positive definite sparse covariance estimators
Two and Three Dimensional Kolmogorov-Smirnov Two-Sample Tests
Periodogram Peaks in Correlated Time Series
Peak Picking Methods Inspired by Biological Data
Monitor the Total and Peak RAM Used by an Expression or Function
Package for Periodic Autoregression Analysis
Maximum Likelihood Inference for the Pearson VII Distribution
with Shape Parameter 3/2
Independent component analysis using score functions from the
Pearson system
Prediction Error Curves for Risk Prediction Models in Survival
Analysis
Functions to facilitate power and sensitivity analyses for
genetic studies of natural populations
An implementation for association analysis with CNV data
Population and Evolutionary Genetics Analysis System
Geophysical Inverse Theory and Optimization
A Penalized EM algorithm incorporating missing-data mechanism
Portable Emissions (and Other Mobile) Measurement System
Utilities
L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation
in GLMs and in the Cox Model
Penalized Classification using Fisher's Linear Discriminant
Feature Selection SVM using penalty functions
Flexible Copula Density Estimation with Penalized Hierarchical
B-Splines
Density Estimation with a Penalized Mixture Approach
Flexible Pair-Copula Estimation in D-Vines using Bivariate
Penalized Splines
Estimating Regularized Multi-state Models Using L1 Penalties
Simulation of high-dimensional data and parallelized repeated
penalized regression
Parallelised Estimation of Prediction Error
Insilico peptide mutation, digestion and homologous comparison
Evaluation of Diversity in Nucleotide Libraries
Calculate Indices and Theoretical Properties of Protein
Sequences
Using Percolation and Conductance to Find Information Flow
Certainty in a Direct Network
Implementing Double Bootstrap Linear Regression Confidence
Intervals Using the 'perc-cal' Method
PerfMeas: Performance Measures for ranking and classification
tasks
Econometric tools for performance and risk analysis
An Infra-Structure for Performance Estimation of Predictive
Models
Permutational Algorithm to Simulate Survival Data
Permutation Based Gene Expression Pathway Analysis
A Permutation Based Test for Biomarker Discovery in Microbiome
Data
Functions for Generating Restricted Permutations of Data
Resampling-based prediction error estimation for regression
models
Pictographic Representation of Treatment Effects
Permutation of Species During Turnover Events
Analysis of single serving and composite pesticide residue
measurements
Simulation and Reconstruction of PET Images
Building, Visualizing, Exporting and Replaying Petri Nets
Reproducible Retrieval of Pew Research Center Datasets
Phylogenetics for the Environmental Sciences
Estimates False Discovery Proportion Under Arbitrary Covariance
Dependence
Penalized Generalized Estimating Equations in High-Dimension
Generalized Least Square in comparative Phylogenetics
Recursive method for construction of nested resolvable designs
and uniform designs associated
Estimating Multiple Gaussian Graphical Models (GGM) in Penalized
Gaussian Mixture Models (GMM)
Build Dependency Graphs using Projection
Discover Probable Duplicates in Plant Genetic Resources
Collections
Phase II Clinical Trial Design Using Bayesian Methods
Phase II Clinical Trial Design for Multinomial Endpoints
Analysis of Large-Scale Pharmacogenomic Data
Pharmacometric Power calculations for mixed study designs
Phase Plane Analysis of One and Two Dimensional Autonomous ODE
Systems
Auxiliary Functions for Phenological Data Analysis
Auxiliary functions for phenological data processing, modelling
and result handling
Auxiliary functions for phenological data analysis
High-Throughput Generation of Genetic Markers and Maps from
Molecular Phenotypes for Crosses Between Inbred Strains
Tools to Manage a Parametric Function that Describes Phenology
Evaluation of the Proportional Hazards Assumption with a
Standardized Score Process
Proportional Hazards Mixed-effects Model (PHMM)
Convert Letters to Numbers and Back as on a Telephone Keypad
Tools for Phonetic and Acoustic Analyses
Plant 'Photobiology' Related Functions and Data
Waveband Definitions for 'UV', 'VIS', and 'IR' Radiation
R Interface to Geochemical Modeling Software
Panel Data Analysis with Heterogeneous Time Trends
PhViD: an R package for PharmacoVigilance signal Detection
Run Phoenix NLME and Perform Post-Processing
Marks periods of sleep in Actigraph accelerometer data
Analysis of Outbreaks with Sequence Data
An Extension (for Package 'SigTree') of Some of the Classes in
Package 'phylobase'
Base Package for Phylogenetic Structures and Comparative Data
Integrating Phylogenetics and Climatic Niche Modeling
Phylogenetic Comparative Methods for High-Dimensional Traits
Functions for Phylogenetically Based Statistical Analyses
Modelling Competitive Exclusion and Limited Dispersal in a
Statistical Phylogeographic Framework
Fast and Exact Algorithms for Computing Phylogenetic
Biodiversity Measures
Estimating Statistical Errors of Phylogenetic Metrics
Exploring the Phylogenetic Signal in Continuous Traits
Calculating Topological Properties of Phylogenies
Implements the Phylogenetic Regression of Grafen (1989)
Marks Periods of 'Bedrest' in Actigraph Accelerometer Data
Process Physical Activity Accelerometer Data
Calculate Physiological Characteristics of Adults and Children
A Fast, Flexible Tool for Sorting Phylogenetic Trees
Phylogenetic Tools for Comparative Biology (and Other Things)
Estimating the Proportion of True Null Hypotheses for FDR
R tools for integrating phylogenies and ecology
Pathwise Calibrated Sparse Shooting Algorithm
Self contained gene set analysis for gene- and
pathway-environment interaction analysis
Sequence ("Fasta"), Annotation ("Gff") and Variants ("Vcf") for
17 Samples of "P. Infestans" and 1 "P. Mirabilis"
Dual-Agent Dose Escalation for Phase I Trials using the PIPE
Design
Tools for Harnessing 'MLBAM' 'Gameday' Data and Visualizing
'pitchfx'
A Fast, Easy-to-use Tool for Manipulating Tables in Databases
and A Wrapper of MADlib
Tables so Beautifully Fine-Tuned You Will Believe It's Magic
Copy Local R Packages to Another Environment
Create Simple Packages Which Do not Upset R Package Checks
Model diagnostics for population pharmacokinetic models
Public Key Infrastucture for R Based on the X.509 Standard
A reporting pipeline for checking population pharmacokinetic
model assumption
A Pairwise Likelihood Augmented Cox Estimator for Left-Truncated
Data
Modelling and Analysis of Leaf Gas Exchange Data
Partially Linear Additive Quantile Regression
Dynamic Updating Methods for Player Ratings Estimation
Pleiotropy Test for Multiple Traits on a Genetic Marker
A GUI to View, Design and Export Various Graphs of Data
Multiplicity control using Pooled LIS statistic
Additive partially linear models for differential gene
expression analysis
Polytomous logit-normit (graded logistic) model estimation
Multivariate Ordered Probit Model via Pairwise Likelihood
Plotting Multi-Dimensional Data - Using 'rgl'
Various Functions to Facilitate Visualization of Data and
Analysis
Plot Spatial or Spatio-Temporal Data Over Google Maps
Visualization of Spatial and Spatio-Temporal Objects in Google
Earth
Create Interactive Web Graphics via 'plotly.js'
Plot Marginal Effects from Linear Models
Plot Principal Component Histograms Around a Scatter Plot
Useful Networking Tools for Project Management
Creates an envelope that surrounds a set of points plotted in a
two dimensional space
Generate Useful ROC Curve Charts for Print and Interactive Use
Graphing Nonlinear Relations Among Latent Variables from
Structural Equation Mixture Models
Log Linear by Linear Association models and Rasch family models
by pseudolikelihood estimation
Statistical inference in partial linear regression models
Partial Least Squares and Principal Component Regression
Partial Least Squares (PLS) Data Analysis Methods
Degrees of Freedom and Statistical Inference for Partial Least
Squares Regression
Tools for Partial Least Squares Path Modeling (PLS-PM)
Sensitivity Indexes from Polynomial Chaos Expansions and PLS
Partial Least Squares Regression for Beta Regression Models
Partial Least Squares Regression for Cox Models and Related
Techniques
Partial Least Squares Regression for Generalized Linear Models
Variable Selection in Partial Least Squares
Tools for Splitting, Applying and Combining Data
Parallel Model-Based Clustering using
Expectation-Gathering-Maximization Algorithm for Finite Mixture
Gaussian Model
Calculate Pairwise Multiple Comparisons of Mean Rank Sums
Minimal Working Examples for Particle Metropolis-Hastings
Transforms Input Data from a PMML Perspective
Probit-Normal Marginalized Transition Random Effects Models
Dose Finding in Drug Combination Phase I Trials Using PO-CRM
Principal Orthogonal ComplEment Thresholding (POET) Method
Bayesian Variable Selection for a Poisson-Logistic Model
PogromcyDanych / DataCrunchers is the Masive Online Open Course
that Brings R and Statistics to the People
Classification and clustering of sequencing data based on a
Poisson model
Poisson lognormal and bivariate Poisson lognormal distribution
Analyzing Pointer Years and Components of Resilience
Data Generation with Poisson, Binary and Continuous Components
Data Generation with Poisson, Binary and Ordinal Components
Generation of Up to Four Different Types of Variables
Data Generation with Poisson, Binary, Ordinal and Normal
Components
Confidence Intervals with Poisson Double Sampling
Simultaneous Generation of Count and Continuous Data
Simultaneous Generation of Multivariate Data with Poisson and
Normal Marginals
Simulating Homogenous & Non-Homogenous Poisson Processes
Fit high dimensional mixtures of Poisson GLMs
Significance analysis of sequencing data based on a Poisson log
linear model
Polytomous variable Latent Class Analysis
Implementation of the Polya-Aeppli distribution
Sensitivity Indexes Calculated from Polynomial Chaos Expansions
Bayesian Population Genomics in Autopolyploids
A Collection of Functions to Implement a Class for Univariate
Polynomial Manipulations
Paternity Exclusion in Autopolyploid Species
Tools for Polyploid Microsatellite Analysis
Simulate and test marker dosage for dominant markers in
autopolyploids
Bayesian mixture models for marker dosage in autopolyploids
Bootstrapped Basis Regression with Oracle Model Selection
Pattern Oriented Modelling Information Criterion
Statistical Inference for Partially Observed Markov Processes
A Flexible Syntax for Population Dynamic Modelling
Construction and Analysis of Matrix Population Models
Demographic Modelling Using Projection Matrices
Population (and Individual) Optimal Experimental Design
Functions for Epidemiological Analysis using Population Data
Useful functions for (batch) file conversion and data resampling
in microsatellite datasets
An Efficient Swiss Army Knife for Population Genomic Analyses
A Simple Framework to Analyse Population Genetic Data
This is an R package that constructs and manipulates population
graphs
For interval estimation of mean of selected populations
Tools for Simplifying the Population and Querying of SQLite
Databases
Genetic Analysis of Populations with Mixed Reproduction
popRange: A spatially and temporally explicit forward genetic
simulator
Reconstruct Human Populations of the Recent Past
Functions for Constructing and Evaluating Self-Organizing Maps
Genomic Breeding Tools: Genetic Variance Prediction and
Cross-Validation
Portmanteau Tests for Univariate and Multivariate Time Series
Models
Portfolio Analysis, Including Numerical Methods for Optimization
of Portfolios
High Frequency Price Estimators by PortfolioEffect
High Frequency Portfolio Analytics by PortfolioEffect
Framework for simulating equity portfolio strategies
Tools for Interacting with 'PostgreSQL' / 'PostGIS' Databases
Markov Chain Monte Carlo for Potts Models
Computation of Power and Level Tables for Hypothesis Tests
Power and Sample-Size Distribution of 2-Stage Bioequivalence
Studies
Power Calculations for GxE and GxG Interactions for GWAS
Power/Sample Size Calculation for Mediation Analysis
Power analyses for the affected sib pair and the TDT design
Power and Sample Size Calculation for Survival Analysis of
Epidemiological Studies
Power and Sample Size Based on Two One-Sided t-Tests (TOST) for
(Bio)Equivalence Studies
Partial and Semi-Partial (Part) Correlation
Predict Protein-Protein Interactions Based on Functional and
Topological Similarities
Point Process Models with LASSO Penalties
Projection Pursuit Classification Tree Visualization
web tool for estimating under-five deaths caused by poor-quality
antimalarials in sub-Saharan Africa
Functions for Clustering of Presence-Absence, Abundance and
Multilocus Genetic Data
Tools for Designing and Weighting Survey Samples
Provides a pragma / directive / keyword syntax for R
Prais-Winsten Estimation Procedure for AR(1) Serial Correlation
Kvantitatiivsete meetodite praktikumi asjad / Functions used in
the course "Quantitative methods in behavioural sciences"
(SHPH.00.004), University of Tartu
Testing Workbench for Precision-Recall Curves
Precipitation Intensity, Concentration and Anomaly Analysis
Calculate Accurate Precision-Recall and Receiver Operator
Characteristics Curves
Prediction Interval Functions for Assessing Replication Study
Results
Prediction Intervals for Three Basic Statistical Models
Calculate Predicted Means for Linear Models
Test Bench for Comparison of Data Prediction Models
Classification rule based on Bayesian mixture models with
feature selection bias corrected
Utilities to Fit Paired Comparison Models for Preferences
Pre-Knitting Processing and Post HTML-Rendering Processing
Dirichlet Process Bayesian Clustering, Profile Regression
Preparing Experimental Data for Statistical Analysis
Lightweight Data Quality Simulation for Classification
Tools for Visualization of Interdependent Data Quality Issues
R Markdown Template to Preregister Scientific Studies
Probability-Scale Residuals and Residual Correlations
Creating Pretty Documents from R Markdown
Scale Bar, North Arrow, and Pretty Margins in R
Pretty, Human Readable Formatting of Quantities
Geostatistical Modelling of Spatially Referenced Prevalence Data
Estimating Regional Trends of a Prevalence from a DHS
Permutation Significance for Random Forests
Use Prime Factorization for Computations
Functions and data for A Primer of Ecology with R
Visually Assessing the Specificity and Informativeness of Primer
Pairs
Fits a Principal Curve in Arbitrary Dimension
Finding and plotting simple basis vectors for multivariate data
Access Data from the Oregon State Prism Climate Project
Protocol Inspection and State Machine Analysis
Differentially Private Regularized Logistic Regression
Estimation of Prevalence Ratios using Logistic Models
Point-Process Response Model for Optogenetics
Elementary Probability on Finite Sample Spaces
Statistical Tools for Probing Moderation Effects
Probabilistic weather forecast using the GOP method
Probit with Spatial Dependence, SAR and SEM Models
probsvm: Class probability estimation for Support Vector
Machines
Inference for the Stress-Strength Model R = P(Y<X)
Extraction of Bands from MODIS Calibrated Radiances MOD02 NRT
Product Density Estimation for ICA using tilted Gaussian density
estimates
Product-Limit Estimation for Censored Event History Analysis
The package can prioritize candidate disease metabolites based
on global functional relationships between metabolites in the
context of metabolic pathways
Profile Likelihood for a Parameter in Commonly Used Statistical
Models
Tools for profiling inference functions for various model
classes
Profile Analysis of Multivariate Data in R
An alternative display for profiling information
An Alternative Display Profiling Data as Tree Structure
Interactive Visualizations for Profiling R Code
Finding the Optimal Cluster Number Using Progeny Clustering
support package for "Programming Graphical User Interfaces in R"
Prognostic ROC curves for evaluating the predictive capacity of
a binary test
A simple interface to the PROJ.4 cartographic projections
library
Automates the Creation of New Statistical Analysis Projects
Biological Network Construction, Visualization and Analyses
Various confidence interval methods for proportions
Analyzing Combination of Proportions and Relative Risk
Parse Java Properties Files for R Service Bus Applications
Inference on Single Binomial Proportion and Bayesian
Computations
Feature (gene) selection based on the Proportional Overlapping
Scores
Calculating Proportionality Between Vectors of Compositional
Data
Propensity score methods for assigning treatment in randomized
trials
Miscellaneous functions for processing and sample selection of
vis-NIR diffuse reflectance data
Generates Various Protein Descriptors for Machine Learning
Algorithms
Optimization of a multi-stage proteomic study
Statistical Analysis of High Throughput Proteomics Data
Protein (identification and) quantification based on peptide
evidence
Fast and Simple Object Serialization to Protocol Buffers
Inference on Prototypes from Clusters of Features
Generating Various Numerical Representation Schemes of Protein
Sequence
Manipulate and Play 'ProTracker' Modules
Visualizing and Analyzing Mass Spectrometry Related Data in
Proteomics
Statistical Toolbox for Sedimentary Provenance Analysis
Minimal Protein Set Explaining Peptide Spectrum Matches
Precision-Recall and ROC Curves for Weighted and Unweighted Data
Test of Periodicity using Response Surface Regression
Bootstrapping for Propensity Score Analysis
Penalized Parametric and Semiparametric Bayesian Survival Models
with Shrinkage and Grouping Priors
Analysis of Parent-Specific DNA Copy Numbers
Political Science Computational Laboratory, Stanford University
Standardizing Physiological Composite Risk Endpoints
Adaptive, Sine-Multitaper Power Spectral Density Estimation
Download Regularly Maintained Political Science Data Sets
Parameter Space Exploration with Latin Hypercubes
Methods for Evaluating Principal Surrogates of Treatment
Response
Forecasting of Univariate Time Series Using the Pattern
Sequence-Based Forecasting (PSF) Algorithm
Projected Spatial Gaussian Process (psgp) methods
Build Panel Data Sets from PSID Raw Data
Several Local False Discovery Rate Estimators
Non-Linear Mixed-Effects modelling using Stochastic Differential
Equations
Piecewise Exponential Model for Time to Progression and Time
from Progression to Death
Probabilistic Suffix Trees and Variable Length Markov Chains
Simulations of grouped responses relative to baseline
Procedures for Psychological, Psychometric, and Personality
Research
Recursive Partitioning Based on Psychometric Models
Functions for analyzing psychophysical data in R
Produce Well-Formatted Tables for Psychological Research
Bayesian Variable Selection with Hierarchical Priors
Performs simulation study to look for publication bias, using a
technique described by Ioannidis and Trikalinos; Clin Trials.
2007;4(3):245-53
Printing Results of Statistical Computing in a Publishable Way
Parallel Utilities for Lambda Selection along a Regularization
Path
Bayesian Estimation of Tumor Purity and Clonality
Population Viability Analysis with Data Cloning
Calculation and Application of p-Variation
Hierarchical Clustering with P-Values via Multiscale Bootstrap
Resampling
An R package to interact with the Project Vote Smart API for
scientific research
Time Series Regression Using the Power Weighted Densities (PWD)
Approach
Statistical Power Simulation for Testing the Rasch Model
Penn World Table (Versions 5.6, 6.x, 7.x)
Heuristics for the Quadratic Assignment Problem (QAP)
Yet Another Package for Qualitative Comparative Analysis
Tests for Type I Error in Qualitative Comparative Analysis (QCA)
Modern Functions for Qualitative Comparative Analysis
Professional Functionality for Performing and Evaluating
Qualitative Comparative Analysis
Fast & Easy Quality Control of EWAS Results Files
Quality Control of Genome Wide Association Study results
Robust Estimation of Gaussian Mixture Models
Sure Independence Screening via Quantile Correlation and
Composite Quantile Correlation
Bridging the Gap Between Qualitative Data and Quantitative
Analysis
Dictionaries and Word Lists for the 'qdap' Package
Regular Expression Removal, Extraction, and Replacement Tools
Fitting a Quadrilateral Dissimilarity Model to Same-Different
Judgments
Quantitative Fatty Acid Signature Analysis
Pricing of Vanilla and Exotic Option Contracts
Estimate Quantitative Genetics Parameters from Generalised
Linear Mixed Models
Graph Plotting Methods, Psychometric Data Visualization and
Graphical Model Estimation
Tools for Quantitative Genetics Data Analyses
Estimate the Coefficients for Non-Convex Penalized Quantile
Regression Model by using QICD Algorithm
Processing Data for Quantitative Language Comparison (QLC)
Utility Sparse Matrix Functions for Quantitative Language
Comparison
Visualization for Quantitative Language Comparison (QLC)
Statistical Transformations for Post-Processing Climate Model
Output
Analysis of Subjective Perspectives Using Q Methodology
Analysis of Health-Related Quality of Life in Oncology
Modelling and analysis of real-time PCR data
Quasi-Potential Analysis for Stochastic Differential Equations
Self Calibrating Quantile-Quantile Plots for Visual Testing
Tools that Create D3 JavaScript Force Directed Graph from R
Quantile Regression in Varying-Coefficient Models
Simultaneous simulation of Q and R mode factor analyses with
Spatial data
Joint Estimation in Linear Quantile Regression
Quantile Regression for Linear Mixed-Effects Models
Provides R-Language Code to Examine Quantitative Risk Management
Concepts
Data Sets for Quantitative Risk Management Practice
Quantile Regression for Nonlinear Mixed-Effects Models
Quantitative Structure Activity Relationship (QSAR) Data Sets
Densitometric Analysis of Thin-Layer Chromatography Plates
Interactive Graphics for QTL Experiments
Tools for Mapping Multiple Complex Traits
Tools for Mapping of Quantitative Traits of Genetically Related
Individuals and Calculating Identity Coefficients from
Pedigrees
QuACN: Quantitative Analysis of Complex Networks
Exact permutation moments of quadratic form statistics
Functions to solve Quadratic Programming Problems
Sparsity by Worst-Case Quadratic Penalties
Causal Inference with Qualitative and Ordinal Information on
Outcomes
Implements Indices of Qualitative Variation Proposed by Wilcox
(1973)
Streamline Descriptive Analysis of Quantitative Data Matrices
Quantitative chemical analysis: calibration and evaluation of
results
Quantification of Qualitative Survey Data
Estimation of Conditional Quantiles using Optimal Quantization
Quantile-Based Spectral Analysis of Time Series
Clustering Mutations using High Throughput Sequencing (HTS) Data
Analyzing RNA Sequencing Count Tables Using Quasi-Likelihood
Functions to Make Surveys Processing Easier
Analysis of Queueing Networks and Models
Calculation of Homology of Quandles, Racks, Biquandles and
Biracks
Regularized sparse inverse covariance matrix estimation
Fits Psychometric Functions for Multiple Groups
Build Regression Models Quickly and Display the Results Using
'ggplot2'
Summary charts of micro satellite profiles for a set of
biological samples
Variables Selection for Clustering and Classification
Quasi Variances for Factor Effects in Statistical Models
Generalized Eigenvalues and QZ Decomposition
Estimation of R0 and Real-Time Reproduction Number from
Epidemics
Compressive Sampling: Sparse Signal Recovery Utilities
Estimate Structured Additive Regression Models with BayesX
Bivariate (Two-Dimensional) Confidence Region and Frequency
Distribution
Converting R CRAN outputs into Google Earth
Simple R Interface to Microsoft PowerPoint using rcom or
RDCOMClient
A GTK GUI for fitting and comparing GLM and GLMM in R
r2stl, R package for visualizing data using a 3D printer
Running 'WinBUGS' and 'OpenBUGS' from 'R' / 'S-PLUS'
Racing methods for the selection of the best
R Package for Phylogenetic Analysis of RADseq Data
Normalization and Study of Rank Abundance Distributions
Tools for plotting skew-T diagrams and wind profiles
Inverse-Regression Estimation of Radioactive Doses
Radon and Soil Gas Transport in 2D Porous Medium
Convenience Functions for Routine Data Exploration
Ridge Estimation of Precision Matrices from High-Dimensional
Data
Ridge Estimation of the Vector Auto-Regressive (VAR) Processes
Data Fusion Filters for Attitude Heading Reference System (AHRS)
with Several Variants of the Kalman Filter and the Mahoney and
Madgwick Filters
Rainbow Plots, Bagplots and Boxplots for Functional Data
Obtain and Analyze Rainfall Data from the Climate Prediction
Center
Rainfall Frequency (Design Storm) Estimates from the US National
Weather Service
Retrieves Altmerics Data For Any Published Paper From
Altmetric.com
Tools For Managing File/function Dependencies In R
Regularized Generalized Linear Models with Interaction Effects
Structural Equation Modeling using the reticular action model
(RAM) Notation
Bayesian Geostatistical Modeling with RAMPS
Reinforced Angle-Based Multicategory Support Vector Machines
Random number generator based on AES cipher
Package Provides Access to Fake User Data
Simulation and Analysis of Random Fields
Utilities for the Simulation and Analysis of Random Fields
Breiman and Cutler's Random Forests for Classification and
Regression
Distributed 'randomForest' for Big Data using 'ddR' API
Random Forests for Survival, Regression and Classification
(RF-SRC)
Function to Create a Random List for Crossover Studies
Easy to Use Tools for Common Forms of Random Assignment
Function for Generating Random Names and a Dataset
A Parallel Analysis with Polychoric Correlation Matrices
Random Uniform Forests for Classification, Regression and
Unsupervised Learning
Toolbox for Pseudo and Quasi Random Number Generation and RNG
Tests
Occurrence Filtering and Generation of Species Range Polygons
A Platform for the Study of Macroecology of Life History Traits
Mid-Domain Effect and Species Richness Patterns
Model-Based Clustering for Multivariate Partial Ranking Data
Rank-Based Tests for General Factorial Designs
Ranking Responses in a Single Response Question or a Multiple
Response Question
Ranking of Nodes with Kernelized Score Functions
Fast Nearest Neighbour Search (Wraps Arya and Mount's ANN
Library)
Fast Nearest Neighbour Search (Wraps ANN Library) Using L1
Metric
Reliable Accurate Prenatal non-Invasive Diagnosis R package
Bindings to AppArmor and Security Related Linux Tools
Application Directories: Determine Where to Save Data, Caches,
and Logs
Miscellaneous (stats) helper functions with sane defaults for
reporting
Functions to import data from Arc/Info V7.x binary coverages
Testing Gene-Environment Interaction for Rare Genetic Variants
Ecological and biogeographical null model tests for comparing
rarefaction curves
Calculation of Rarity Indices for Species and Assemblages of
Species
Solvers for Large Scale Eigenvalue and SVD Problems
Range Ancestral State Estimation for Phylogeography and
Comparative Analyses
Kernel Based Estimates on in-Memory Raster Images
Routines for Solving Rate-Distortion Problems
A Modification of Fleiss' Kappa in Case of Nominal and Ordinal
Variables
Graphical User Interface for Data Mining in R
Parameter estimation for the averaging model of Information
Integration Theory
Interface to the Bird-Watching Dataset Proyecto AVIS
Read and Write BAM (Binary Alignment) Files
The Beta Random Number and Dirichlet Random Vector Generating
Functions
Tools for 'Box Geometry Model' (BGM) Files and Topology for the
Atlantis Ecosystem Model
Interface to the 'Biodiversity' 'Heritage' Library
Process Rhea, KEGG, MetaCyc, Unipathway Biochemical Reaction
Data
Handling Linear Gaussian Bayesian Networks
Extensible, Parallelizable Implementation of the Random Forest
Algorithm
Perform Rosenbaum bounds sensitivity tests for matched and
unmatched data
Rbundler manages an application's dependencies systematically
and repeatedly
Fast and Light-Weight Caching (Memoization) of Objects and
Results to Speed Up Computations
Calculation of the Integrated Flow of Particles between Polygons
Access and Plot CanVec and CanVec+ Data for Rapid Basemap
Creation in Canada
Loglinear Models for Capture-Recapture Experiments
This package builds maps with a full cartographic layout
Large, Sparse Optimal Matching with Refined Covariate Balance
Optimal Subset Matching with Refined Covariate Balance
Miscellaneous R Functions for Swedish Regional Cancer Centers
RCEIM - R Cross Entropy Inspired Method for Optimization
Conjugate Gradient Minimization of Nonlinear Functions
Chess Move, Generation/Validation, Piece Placement/ Movement,
and Check/Checkmate/Stalemate Detection
Discrete Choice (Binary, Poisson and Ordered) Models with Random
Parameters
Post-Processing of the Markov Chain Simulated by ChronoModel or
Oxcal
RClimMAWGEN (R Climate Index Multi-site Auto-regressive Weather
GENeretor): a package to generate time series of climate
indices from RMAWGEN generations
R tools for integrating with the www.clinicalcodes.org
repository
Download Aggregate Trial Information and Results from
ClinicalTrials.gov
Run 'R CMD check' from 'R' and Capture Results
Rcmdr Plug-In for Business and Customer Analytics
R Commander Plugin for (industrial) Design of Experiments
Plugin de R-Commander para el Manual 'EACSPIR'
Rcmdr Evidence Based Medicine Plug-in Package
R Commander Plug-in for the EZR (Easy R) Package
R Commander Plug-in for Fitting Generalized Waring Regression
Models
An Rcmdr Plug-in for Kaplan-Meier Plots and Other Plots by Using
the ggplot2 Package
Graphical User Interface for Conducting Meta-Analyses in R
Adds menu items to produce mosaic plots and assoc plots to Rcmdr
R Commander Plug-in for University Level Applied Statistics
Graphical POINT of view for questionnaire data Rcmdr Plug-In
Rcmdr Receiver Operator Characteristic Plug-In PACKAGE
Tools for sampling in Official Statistical Surveys
Rcmdr Plugin for Designing and Analyzing Single-case Experiments
R Commander Plug-in for the 'survival' Package
Graphical Integrated Text Mining Solution
Tools for Manipulating and Summarizing CMIP5 Data
Interface to Colombos Compendia using the Exposed REST API
A Collection of Small Text Corpora of Interesting Data
Regions of Common Profiles Modelling with Mixtures-of-Experts
'Rcpp' Bindings for 'Annoy', a Library for Approximate Nearest
Neighbors
'Rcpp' Interface to the APT Package Manager
'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra
Library
Rcpp bindings for the Boost Date_Time library
Examples using RcppClassic to interface R and C++
Read-Write Support for NumPy Files via Rcpp
Global Optimization by Differential Evolution in C++
'Rcpp' Integration for the 'Eigen' Templated Linear Algebra
Library
Examples using 'Rcpp' to Interface R and C++
'Rcpp' Bindings for the 'Faddeeva' Package
'Rcpp' Interface for Querying System Configuration Variables
'Rcpp' Integration for 'GNU GSL' Vectors and Matrices
Iterator Based Expression Template Expansion of Standard
Operators
'Rcpp' Integration for Numerical Computing Libraries
Seamless Interface to Octave -- And Matlab
An Interruptible Progress Bar with OpenMP Support for C++ in R
Packages
'Rcpp' Bindings for 'Redis' using the 'hiredis' Library
R Interface to the Shark Machine Learning Library
Rcpp bindings for Sequential Monte Carlo
'Rcpp' Integration of the 'Streamulus' 'DSEL' for Stream
Processing
'Rcpp' Bindings to Parser for Tom's Obvious Markup Language
'Rcpp' Integration of Different "Ziggurat" Normal RNG
Implementations
Access to Cryptsy Crypto-Currency Exchange Public Information
API via R
R Interface to the CSDP Semidefinite Programming Library
General Network (HTTP/FTP/...) Client Interface for R
Shrunken Centroids Regularized Discriminant Analysis
'DataCite' Client for 'OAI-PMH' Methods and their Search 'API'
Toolbox for Regression Discontinuity Design ('RDD')
Robust Data Envelopment Analysis (DEA) for R
Interact with the UK AIR Pollution Database from DEFRA
Relevant Dimension Estimation (RDE) in Feature Spaces
R interface to the dieharder RNG test suite
Importing Real-Time Thermo Cycler (qPCR) Data from RDML Format
Files
R Bindings for the Discourse Network Analyzer
Generating Various Numerical Representation Schemes of DNA
Sequences
R Interface to the Deutsche Nationalbibliothek (German National
Library) API
Get the Category of Content Hosted by a Domain
Update and Manipulate Rd Documentation Objects
Robust Data-Driven Statistical Inference in
Regression-Discontinuity Designs
Programmatic Interface to the 'Dropbox' API
R Interface to DSDP Semidefinite Programming Library
An R wrapper for the Data Science Toolkit API
The rDVR package allows you to start stop and save a video
server from within R
Reactive transport modelling in 1D, 2D and 3D
Simple Unified Interface to Read Bitmap Images (BMP,JPEG,PNG)
Reads Mass Spectrometry Data in Bruker *flex Format
Read Data Stored in DBC (Compressed DBF) Files
Suite of Functions to Flexibly Read Data from Files
Reading Machine Learning Benchmark Data Sets in Different
Formats
Reads Mass Spectrometry Data in mzXML Format
Monotonize Point and Interval Functional Estimates by
Rearrangement
Empirical Bayes Estimation and Inference in R
R Client for the eBird Database of Bird Observations
Finite Mixture Modeling, Clustering & Classification
Build Regular Expressions in a Human Readable Way
Core Functionality for the 'rebus' Package
Date and Time Extensions for the 'rebus' Package
Numeric Extensions for the 'rebus' Package
Unicode Extensions for the 'rebus' Package
Relevant Component Analysis for Supervised Distance Metric
Learning
Redundancy Control in Pathways databases
Ordination Methods for the Analysis of Beta-Diversity Indices
Compute the Rectangular Statistical Cartogram
Lab for Developing and Testing Recommender Algorithms
Book-Crossing Dataset (BX) for 'recommenderlab'
Recommender System using Matrix Factorization
Companion Package to the Book 'R: Einführung durch angewandte
Statistik'
Reconstruction of Daily Data - Precipitation
Markov Chain Monte Carlo Methods for Redistricting Simulation
Applications of Empirical Dynamic Modeling from Time Series
Regression Trees with Random Effects for Longitudinal (Panel)
Data
EWAS using Reference-Free DNA Methylation Mixture Deconvolution
Gene and Splice Site Annotation Using Annotation Data from
Ensembl and UCSC Genome Browsers
Straightforward 'BibTeX' and 'BibLaTeX' Bibliography Management
Refining Data Table Using a Set of Formulas
Interactive Plotting for Functional Data Analyses
Wavelet-Domain Regression with Functional Data
Tools for an Introductory Class in Regression and Modeling
Cluster analysis via regression coefficients
Detecting Mislabeled Samples in Genetic Data
Risk Estimation for Genetic and Environmental Traits
Gaussian linear models with linear covariance structure
Expander Functions for Generating Full Gradient and Hessian from
Single- and Multi-Slot Base Distributions
Random Subspace Method (RSM) for Linear Regression
Performs Regularization on Structural Equation Models
Non-Parametric Bayesian Spectrum Estimation for Multirate Data
Detect and Test Regular Sequences and Subsequences
Searching for Footprints of Selection using Haplotype
Homozygosity Based Tests
Item Analysis Package with Standard Errors
Relative importance of regressors in linear models
Data Structures and Algorithms for Relations
relax -- R Editor for Literate Analysis and lateX
Relaxation of glmnet models (as in relaxed lasso, Meinshausen
2007)
Functions for estimating parameters in software reliability
models
Tools for Structural Reliability Analysis
Package for some probability distributions
Relative Contribution of Effects in a Regression Model
Match Regular Expressions with a Nicer 'API'
Extensible Markov Model for Modelling Temporal Relationships
Between Clusters
Regularized Multivariate Regression for Identifying Master
Predictors
Empirical Orthogonal Teleconnections in R
Remote R: Control a Remote R Session from a Local One
Fitting Linear Models with Endogenous Regressors when No
External Instruments are Available
Renewal Method for Extreme Values Extrapolation
Reordering the dendrogram according to the class labels
GWAS for Multiple Observations on Related Individuals
Global tests for expression data of high-dimensional sets of
molecular features
Replicability Analysis for Multiple Studies of High Dimension
Tools for Handling EpiJSON (Epidemiology Data) Files
Two-Way ANOVA-Like Method to Analyze Replicated Point Patterns
Miscellaneous Tools for Reproducible Research
Repeated Measures Proportional Odds Logistic Regression
Microsoft Word, Microsoft PowerPoint and HTML Documents
Generation
External jars required for package ReporteRs
A General Message and Error Reporting System
Tools for automatically generating reproducible clinical report
Assist the Workflow of Writing Academic Articles and Other
Reports
Generate LaTeX Tables of Descriptive Statistics
R Interface to 'EPP-Lab', a Java Program for Exploratory
Projection Pursuit
Determine the representativity of two multidimensional data sets
Reproduce Statistical Analyses and Meta-Analyses
General Purpose Client for 'ERDDAP' Servers
Reordering and/or Reflecting Factors for Simulation Studies with
Exploratory Factor Analysis
Data Sets for Mathematical Statistics with Resampling in R
Regression and Similarity Evaluation for Memory-Based Learning
in Spectral Chemometrics
Tools for Analysis, Design, and Operation of Water Supply
Storages
Flexibly Reshape Data: A Reboot of the Reshape Package
A GUI for the reshape2 and plyr packages
electrical properties of resistor networks
Resource Selection (Probability) Functions for Use-Availability
Data
Tools for Conducting Respirometry Experiments
Functions for Working with the 'www.estimize.com' Web Services
Robust Estimation of Location and Scatter
Import Professional Baseball Data from 'Retrosheet'
Repeated Function Evaluation for Sensitivity Analysis
Revealed Preferences and Microeconomic Rationality
R Markdown Format for 'reveal.js' Presentations
R wrappers for EXPOKIT; other matrix functions
Get Seismic Data from the International Federation of Digital
Seismograph Networks
Rapid Feasible Generalized Least Squares
Importance Measure and Selection for Groups of Variables with
Random Forests
Easy Handling of and Access to Files Organized in Structured
Directories
'Programmatic Interface to the 'openfisheries.org' API'
Basic R Interface to the FLANN C++ Library
Multivariate Analysis of Metabolomics Data using Random Forests
MarkLogic NoSQL Database Server in-Database Analytics for R
Graphics for Spherical Distributions and Earthquake Focal
Mechanisms
Data Integration Feature for Force.com and Salesforce.com
Code Examples to Accompany the Book "R for Dummies"
BATWING for calculating forensic trace-suspect match
probabilities
Estimate Permutation p-Values for Random Forest Importance
Metrics
Random Forests Model Selection and Performance Evaluation
Gabriel Multiple Comparison Test and Plot the Confidence
Interval on Barplot
Gamma convolutions for methylation array background correction
Interface to the Global 'Biodiversity' Information Facility
'API'
Hierarchical Modeling and Frequency Method Checking on
Overdispersed Gaussian, Poisson, and Binomial Data
RGCCA and Sparse GCCA for multi-block data analysis
Bindings for the Geospatial Data Abstraction Library
Tools To Generate Daily-Precipitation Time Series
R Version of GENetic Optimization Using Derivatives
Interface to Geometry Engine - Open Source (GEOS)
Wrapper for the Geospatial Data Quality REST API
Build, Import and Export GEXF Graph Files
Access WHO Global Health Observatory Data from R
R Interface to Global Biotic Interactions
Unsampled Data in R for Google Analytics Premium Accounts
UI for the RGP genetic programming framework
Data and Functions from the Book R Graphics, Second Edition
Interface Between GRASS 7 Geographical Information System and R
Data frame editor and dialog making wrapper for RGtk2
Interface to the 'Handsontable.js' Library
Retrieve data sets from the HealthData.gov data API
Side Effect Risks in Hospital : Simulation and Estimation
Permits *apply() Style Dispatch for 'HPC'
Heart rate variability analysis of ECG data
Regularized Hotelling's T-square Test for Pathway (Gene Set)
Analysis
Methods for Accessing Huge Amounts of Data [deprecated]
ri: R package for performing randomization-based inference for
experiments
Randomization inference for treatment effects on a binary
outcome
Computes and Compares Species Richnesses
R Package for Ridge Fusion in Statistical Learning
Ridit Analysis (An extension of the Kruskal-Wallis Test.)
Accesses Weather Data from the Iowa Environment Mesonet
Read 'ImageJ' Region of Interest (ROI) Files
C++ Classes to Embed R in C++ Applications
Risk Regression Models for Survival Analysis with Competing
Risks
Riskset ROC curve estimation from censored survival data
Risk Quantification for Stock Portfolios under the T-Copula
Model
Isothermal Titration Calorimetry (ITC) Data Analysis
Integrated Taxonomic Information System Client
River Network Distance Computation and Applications
In vitro in vivo correlation linear level A
Steady and Unsteady Open-Channel Flow Computation
Reversible Jump MCMC for the Analysis of CGH Arrays
A Clean, Whitespace-Sensitive Template Language for Writing HTML
Analysis of Data Acquired Using the Receiver Operating
Characteristic Paradigm and Its Extensions
Provides access to databases through the JDBC interface
Perform JIVE Decompositions for Multi-Source Data
R-interface to Gene Drop Simulation from JPSGCS
R interface of the Gateway to Advanced and User-friendly
Statistics Service
Serialize R objects to JSON, JavaScript Object Notation
Using Apache 'Kafka' Messaging Queue Through 'R'
External Jars Required for Package 'rkafka'
Random KNN Classification and Regression
Topological Analysis of Knotted Proteins, Biopolymers and 3D
Structures
Mann-Kendall Test, Seasonal and Regional Kendall Tests
Data Exchange Between R and LabKey Server
R Interface to RNG with Multiple Streams
Ensemble Empirical Mode Decomposition (EEMD) and Its Complete
Variant (CEEMDAN)
A Toolbox for Non-Tabular Data Manipulation
R Parallel Implementation of Local Outlier Factor(LOF)
Exact (Restricted) Likelihood Ratio Tests for Mixed and Additive
Models
Modelling Ordinary Differential Equations Leading to
Luminescence
'Shiny' Applications for the R Package 'Luminescence'
Fit Multi-Modal Mallows' Models to ranking data
Continuous Optimization using Memetic Algorithms with Local
Search Chains (MA-LS-Chains) in R
Detect Marine Heat Waves and Marine Cold Spells
Read and Write MAT Files and Call MATLAB from Within R
The MCFS-ID Algorithm for Feature Selection and Interdependency
Discovery
HTML Output Formats and Templates for 'rmarkdown' Documents
'R' 'Markdown' Format for 'shower' Presentations
An Individual-Based Population Genetic Simulation Environment
Data Mining Classification and Regression Methods
Combining Mixture Components for Clustering
Miscellaneous Collection of Functions for Medical Data Analysis
Connect R with MOA for Massive Online Analysis
Rounded Mixture Package. Performs Probability Mass Function
Estimation with Nonparametric Mixtures of Rounded Kernels
R MPFR - Multiple Precision Floating-Point Reliable
Interface (Wrapper) to MPI (Message-Passing Interface)
RMRAINGEN (R Multi-site RAINfall GENeretor): a package to
generate daily time series of rainfall from monthly mean values
Amazing Random Facts About the World's Greatest Hacker
Root-mean-square goodness-of-fit test for simple null hypothesis
Signal-Noise Separation in Random Matrices by using Eigenvalue
Spectrum Analysis
Distributions, Statistics and Tests derived from Random Matrix
Theory
Weighted Rasch Modeling and Extensions using Conditional Maximum
Likelihood
Database Interface and 'MySQL' Driver for R
Wrapper for several R packages and scripts to automate RNA-seq
analysis
Using Graphs as a Navigational Infrastructure
Some image data used in the RnavGraph package demos
Visualization of High-Throughput Data on Large-Scale Biological
Networks
EUtils libraries for use in the R environment
Obtain, Organize, and Visualize NCEP Weather Data
Build and Grade Multiple Choice Exams with Randomized Content
Fast Network Modularity and Roles Computation by Simulated
Annealing (Rgraph C Library Wrapper for R)
Provides an Interface to the Agent-Based Modelling Platform
NetLogo
Tools for Analyzing Content Homogeneity and News Diffusion using
Computational Text Analysis
Semantically Rich I/O for the 'NeXML' Format
Seeding the Default RNG with a Numeric Vector
Utility functions for working with Random Number Generators
Toolbox for WELL Random Number Generators
Random number generator WELL19937a with 53 or 32 bit output
Image Registration Using the NiftyReg Library
An Interface to the NOAA Operational Model Archive and
Distribution System
Interface to the National 'Phenology' Network 'API'
UK National River Flow Archive Data from R
Robust Analysis of High Dimensional Data
Interpolation Grids for Packages of the 'RobASt' - Family of
Packages
Robust Estimation for Compositional Data
Optimally robust influence curves and estimators for location
and scale
Infinitesimally robust estimators for preprocessing omics data
A 'robots.txt' Parser and 'Webbot'/'Spider'/'Crawler'
Permissions Checker
Robust Periodogram and Periodicity Detection Methods
Three-Step Regression and Inference for Cellwise and Casewise
Contamination
Optimally robust influence curves for regression and scale
Robust Regularized Singular Value Decomposition
Data Management for Hydrology and Beyond Using the Observations
Data Model
Truncated Maximum Likelihood Fit and Robust Accelerated Failure
Time Regression for Gaussian and Log-Weibull Case
Robust Mixture Modeling Fitted via Spatial-EM Algorithm for
Model-Based Clustering and Outlier Detection
Robust Methods using Exponential Tilt Model
An Object Oriented Solution for Robust Factor Analysis
Robust Estimation for Generalized Additive Models
Robust Gaussian Stochastic Process Emulation
Robust Methods for High-Dimensional Data
Robust Estimation of the Generalized log Gamma Model
An Extended Rao-Stirling Diversity Index to Handle Missing Data
Robust Estimation of Variance Component Models
eXperimental Functionality for Robust Statistics
Construction of diagnostic or prognostic scoring system and
internal validation of its discriminative capacities based on
ROC curve and 0.633+ boostrap resampling
Robust Rank Correlation Coefficient and Test
Visualizing the Performance of Scoring Classifiers
Time-Dependent ROC Curve Estimators and Expected Utility
Functions
Non-parametric estimation of ROC curves without Gold Standard
Test
Provides Access to Databases Through the ODBC Interface
Parameterized Queries Extension for RODBC
Plots Surfaces of Rates of Mortality Improvement
R Object-Oriented Programming with or without References
Finds roots, extrema and inflection points of a curve
Nonlinear Root Finding, Equilibrium and Steady-State Analysis of
Ordinary Differential Equations
Distribution of Largest Root for Single and Double Wishart
Settings
Accesses Air Quality Data from the Open Data Platform OpenAQ
Optimally robust estimation - old version
Optimally robust estimation for regression-type models
OCI Based Oracle Database Interface for R
Plot Raster Map Tiles from Open Street Map and Other Sources
Interface to the 'Open Tree of Life' API
Roughened Random Forests for Binary Classification
Simplification of Decision Tables using Rough Sets
Data Analysis Using Rough Set and Fuzzy Rough Set Theories
Royston's H Test: Multivariate Normality Test
Simple interactive controls for R using the tcltk library
Recursive Partitioning and Regression Trees
Plot 'rpart' Models: An Enhanced Version of 'plot.rpart'
Classification trees for ordinal responses
Tools for parsing and manipulating rpart objects, including
generating machine readable rules
RobustPCA: Decompose a Matrix into Low-Rank and Sparse
Components
Tools for the Construction of Clinical Code Lists for Primary
Care Database Studies
RPCLR (Random-Penalized Conditional Logistic Regression)
Read, write, visualize and manipulate PDB files
Easy Interface to Advanced PostgreSQL Features
Interface to PHAST Software for Comparative Genomics
Phylogenetic Comparative Tools for Missing Data and
Within-Species Variation
Build Powerful Pivot Tables and Dynamically Slice & Dice your
Data
Interface to the Search 'API' for 'PLoS' Journals
Graphical User Interface (GUI) for Interactive R Analysis
Sessions
Converter and Interpreter for Reverse Polish Notation
Expressions
R interface to the PostgreSQL database system
Sample Size Computations Controlling the Type-II Generalized
Family-Wise Error Rate
Resolvable partially pairwise balanced design and Space-filling
design via association scheme
Reads, Annotates, and Normalizes Reverse Phase Protein Array
Data
Database Preferences and Skyline Computation
Estimating Disease Prevalence from Registry Data
Functions for Working with 'Eprime' Text Files
Goodness of Fit Tests for High-Dimensional Linear Regression
Models
rpubchem - Interface to the PubChem Collection
R Interface to the Pushbullet Messaging Service
Statistical Methods for the Randomized Response Technique
Estimating Replication Rate for Genome-Wide Association Studies
Ridge Regression and Other Kernels for Genomic Selection
Re-parametrization of RR-BLUP to allow for a fixed residual
variance
Scalable Robust Estimators with High Breakdown Point
Robust Multivariate Methods for High Dimensional Data
Scalable Robust Estimators with High Breakdown Point for
Incomplete Data
'DRNG' on Intel CPUs with the 'RdRand' Instruction for R
Environment for Assessing Recommender Systems
Invoke 'Repast Simphony' Simulation Models
Fitting Distributions to Given Data or Known Quantiles
Robust Regularized Linear Discriminant Analysis
Correlation and Regression Analyses for Randomized Response Data
Dynamic Generation of Scientific Reports
Randomized Response Techniques for Complex Surveys
Data related to the book "R Statistical Application Development
by Example"
SAGA Geoprocessing and Terrain Analysis in R
Resampling-Based Analysis of Geostatistical Data
Ports the Workflow of "Resampling Stats" Add-in to R
Functions to Create and Evaluate Search and Rescue Plans
Tools, Classes, and Methods for Interfacing with SaTScan
Stand-Alone Software
An R Package for Stepwise Cluster Analysis
Rao-Scott Cochran-Armitage by Slices Trend Test
Bi-Directional Interface Between R and Scala with Callbacks
SciMark 2.0 Benchmark for Scientific and Numerical Computing
Deployment Interface for R Markdown Documents and Shiny
Applications
A Method to Download Department of Education College Scorecard
Data
statconn: provides portable C-style interface to R
(StatConnector)
Ray Shooting Depth (i.e. RS Depth) functions for bivariate
analysis
Tools for Reading SDMX Data and Metadata
Estimating the Proportion of Genetically Modified Seeds in
Seedlots via Multinomial Group Testing
Robust Structural Equation Modeling with Missing Data and
Auxiliary Variables
Gini methodology-based correlation and clustering analysis of
microarray and RNA-Seq gene expression data
Robust Sparse Gaussian Graphical Modeling via the
Gamma-Divergence
Functions for Hierarchical Bayesian Estimation: A Flexible
Approach
Siena - Simulation Investigation for Empirical Network Analysis
Robust Signature Selection for Survival Outcomes
A Stemming Algorithm for the Portuguese Language
Submit R Calculations to a 'SLURM' Cluster
Loading Facebook and Instagram Advertising Data from Smartly.io
Get Real-Time Meteorological Data in SMET Format
Plant Root System Markup Language (RSML) File Processing
Neural Networks in R using the Stuttgart Neural Network
Simulator (SNNS)
Get SNP (Single-Nucleotide Polymorphism) Data on the Web
Efficient Score Statistics for Genome-Wide SNP Set Analysis
Adapt Numerical Records to Fit (in)Equality Restrictions
Spatially-Explicit Power Analysis for Conservation and Ecology
Conversion Between Attitude Representations of DCM, Euler
Angles, Quaternions, and Euler Vectors
SQL Server R Database Interface (DBI) and dplyr SQL Backend
A Collection of Methods for Singular Spectrum Analysis
Persistent Fast Amortized Stack and Queue Data Structures
Bayesian Applied Regression Modeling via Stan
Access to the Digital Universe Data set API
Random orthonormal matrix generation on the Stiefel manifold
Simulate and Develop Streaming Processing in [R]
A Convenience Interface for the Stripe Payment API
Suite of Nonlinear Differential Algebraic Equations Solvers in R
Interface to 'Sunlight' Foundation 'APIs'
Robust Estimation of the Proportion of Treatment Effect
Explained by Surrogate Marker Information
Design and Analysis of Disease Surveillance Activities
Render SVG Images into PDF, PNG, PostScript, or Bitmap Arrays
An R SVG Graphics Device with Dynamic Tips and Hyperlinks
R interface to SymPy computer algebra system
Manage and manipulate large collections of R objects stored as
tape-like files
Tools for analyzing sales report files of iTunes Connect
Tools for Tensor Analysis and Decomposition
Automatic Text Classification via Supervised Learning
Functions for calculation of texture metrics for Grey Level
Co-occurrence Matrices
Transcription Factor Binding Site Identification Tool
Inequality, Welfare and Poverty Indices and Curves using the
EU-SILC Data
STK++ Core Library Integration to R using Rcpp
Truncated Newton Function Minimization with Bounds Constraints
Interpolation of Data with Variable Spatial Support
Triangle - A 2D Quality Mesh Generator and Delaunay Triangulator
T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut
Implementation
The R Implementation of the 't-walk' MCMC Algorithm
Implementation of Unobserved Components Model (UCM)
Data and Functions for USA State and County Unemployment Data
Convert 'RUnit' Test Functions into 'testthat' Tests
Runiversal - Package for converting R objects to Java variables
and XML
Interface Utilities, Model Templates, Parallel Computing Methods
and Additional Distributions for MCMC Models in JAGS
R Interface to the UNU.RAN Random Variate Generators
A GUI for the UNU.RAN random variate generators
Detect and Remove Unwanted Variation using Negative Controls
Diverse Basic Statistical and Graphical Functions
R-Values for Ranking in High-Dimensional Settings
Manipulations of Triangular Meshes Based on the 'VCGLIB' API
Query 'R' Versions, Including 'r-release' and 'r-oldrel'
Search 'Vertnet', a 'Database' of Vertebrate Specimen Records
Rare Variants Association Analyses with Family Data
R Graphics Devices for Vector Graphics Output
Tools for Analyzing Non-Uniform Pseudo-Random Variate Generators
Calling haplotype-based and variant-based pedigree
disequilibrium test for rare variants in pedigrees
Variable Metric Nonlinear Function Minimization
Methods for Family-Based Rare-Variant Genetic Association Tests
Probability of Sharing Rare Variants among Relatives
population control weighted rare-variants TDT
A package for accessing World Bank climate data
Detects spatial outliers using a Random Walk on Bipartite Graph
R We There Yet? Visualizing MCMC Convergence in Phylogenetics
R x C Ecological Inference With Optional Incorporation of Survey
Information
Functions to Parse and Create XMCDA Files
Functions to Compute Chemical Reaction Similarity
Facilities for Simulating from ODE-Based Models
Maximum Likelihood Shrinkage via Generalized Ridge or Least
Angle Regression
R Interface to the Yacas Computer Algebra System
R package provide functions to translate English words into
Chinese
Companion to the Forthcoming Book - R you Ready?
Access to the YouTheria Mammal Trait Database
Grain size analysis, textural classifications and distribution
of unconsolidated sediments
GUI Tool for Data Management like SPSS or Stata
R Module for Working with the 'Zabbix API'
Functions for University of Auckland Course STATS 201/208 Data
Analysis
Set of Common Tools for Forecast Verification
Spatial Two Stage Least Squares Estimation
Biclustering via Sparse Singular Value Decomposition
Incorporating Stability Selection
Somatic Copy Number Alteration Analysis Using Sequencing and SNP
Array Data
Sabermetrics Functions for Baseball Analytics
Detection of Fixations in Eye-Tracking Data
SA Counterparty Credit Risk under Basel III
Maximum Likelihood Models for Species Abundance Distributions
Small Area Estimation: Time-series Models
Stochastic Approximation Expectation Maximization (SAEM)
algorithm
A Stacked Autoencoder Implementation with Interface to
'neuralnet'
Small Area Estimation for Rao and Yu Model
Simulation Tools for Small Area Estimation
Generalized and Safe-Bayesian Ridge and Lasso Regression
A Toolbox for the Analysis of Proteomics Data
Sensitivity Analysis for Functional Input
Software for the Analysis of Genetic Architecture
Elastic Net and (Adaptive) Lasso Penalized Sparse Asymmetric
Least Squares (SALES) and Coupled Sparse Asymmetric Least
Squares (COSALES) using Coordinate Descent and Proximal
Gradient Algorithms
A Framework for Comparing the Performance of MCMC Samplers
Sample Size Calculation for Various t-Tests and Wilcoxon-Test
Sample Size Calculations for Complex Surveys
Sample size calculations for normal means
Calculating sample size requirements when estimating the
difference between two binomial proportions
Optimal Stratification of Sampling Frames for Multipurpose
Sampling Surveys
Sampling Surface Simulation for Areal Sampling Methods
SAM: Significance Analysis of Microarrays
Stochastic Augmentation of Matched Data Using Restriction
Methods
Sensitivity Analysis of a Meta-analysis with Unpublished but
Registered Analytical Investigations
Statistical Analysis of Network Data with R
C/C++ source code to trigger Address and Undefined Behaviour
Sanitizers
Stratified Analysis with Nonparametric Covariable Adjustment
Spectral Analysis for Physical Applications
Import ASCII files directly into R using only a SAS input script
Data sets from "SAS System for Mixed Models"
Various Functions for Handling and Manipulating Remote Sensing
Data
Spanning Trees Used for Network Inference
Bayesian Emulation, Calibration and Validation of Computer
Models
Small-Sample Adjustments for Wald tests Using Sandwich
Estimators
Semiparametric Bayesian Gaussian copula estimation and
imputation
sbioPN: Simulation of deterministic and stochastic spatial
biochemical reaction networks using Petri Nets
Semidefinite Programming for Fitting Block Models of Equal Block
Sizes
Detecting structural breaks using rectangle covering
(non-parametric method)
Compute scagnostics - scatterplot diagnostics
Shape-Constrained Additive Regression: a Maximum Likelihood
Approach
Optimization Toolkit for Pharmacokinetic-Pharmacodynamic Models
Simultaneous Confidence Bands for the Mean of Functional Data
Construct Reduced Trees with Predefined Nodal Structures
Stellar CharactEristics Pisa Estimation gRid
Stellar CharactEristics Pisa Estimation gRid for Binary Systems
Supervised Component Generalized Linear Regression
Analyse Citation Data from Google Scholar
Functions and datasets for math used in school
Tools for Analyzing Factorial Experiments
A package on the Schwartz two-factor commodity model
Standardized Climate Indices Such as SPI, SRI or SPEI
A Tool Set for Analyzing Political Behavior Data
Scientific Graphing Functions for Factorial Designs
Measure Growth Patterns and Align Sampling Spots in Photographs
Statistical Comparison of Multiple Algorithms in Multiple
Problems
A Package to Score Behavioral Questionnaires
Score Persons Using the Generalized Graded Unfolding Model
Quickly Score Models in Data Science and Machine Learning
SCORER 2.0: an algorithm for distinguishing parallel dimeric and
trimeric coiled-coil sequences
Scoring Rules for Parametric and Simulated Distribution
Forecasts
The Scott-Knott Effect Size Difference (ESD) Test
Implements the Scout Method for Covariance-Regularized
Regression
Tools for Scraping Data from HTML and XML Documents
Screen and clean variable selection procedures
Analysis of High-Dimensional Categorical Data such as SNP Data
Transcript-Based Unit Tests that are Easy to Create and Maintain
Simulating the Evolution of Biological Sequences
Diving Calculations and Decompression Models
Shrinkage Discriminant Analysis and CAT Score Variable Selection
Statistical Disclosure Control Methods for Anonymization of
Microdata and Risk Estimation
Graphical User Interface for Package sdcMicro
Methods for Statistical Disclosure Control in Tabular Data
Statistical Disclosure Control Substitution Matrix Calculator
Shortcuts, Detours and Dead Ends (SDDE) Path Types in Genome
Similarity Networks
Simulation and Inference for Stochastic Differential Equations
Synthesizing List of Differentially Expressed Features
Subgroup Discovery with Evolutionary Fuzzy Systems in R
Species Distribution Modelling Tools: Tools for processing data
associated with species distribution modelling exercises
Create Virtual Species for Species Distribution Modelling
Scale-Dependent Hyperpriors in Structured Additive
Distributional Regression
Measures of Risk for the Compound Poisson Risk Process with
Diffusion
Spatially Balanced Sample Draws for Spatial Objects
Scenario Discovery Tools to Support Robust Decision Making
Tools for Custom Searches / Subsets / Slices of Named R Objects
Seasonal analysis and graphics, especially for climatology
Score Equity Assessment- summary index computation
Statistical Estimation of Cluster Parameters (SECP)
Sampling Design for Spatially Explicit Capture-Recapture
Spatially Explicit Capture-Recapture for Linear Habitats
Access Data from the SeeClickFix Web API
Simulation of Evolutionary and Epidemiological Dynamics
Statistics for Environmental Sciences, Engineering, and
Geography
Simulation of Ecological and Environmental Models
reading and writing SEER*STAT data files
SEER and Atomic Bomb Survivor Data Analysis Tools
A set of tools for measuring spatial segregation
Determine Event Boundaries in Event Segmentation Experiments
Regression Models with Breakpoints/Changepoints Estimation
Spatial Exposure-Hazard Model for Exposure and Impact Assessment
on Exposed Individuals
Predict Information Cascade by Self-Exciting Point Process
Fast Rolling Functions for Seismology using Rcpp
An Information About Deputies and Votings in Polish Diet from
Seventh to Eighth Term of Office
KoNLP static dictionaries and Sejong project resources
Correcting Biased Estimates Under Selection
A Tool for Calculation and Optimization of the Expected Gain
from Multi-Stage Selection
Estimation of Weight Functions in Meta Analysis
Translate CSS Selectors to XPath Expressions
Select Point Pattern Models Based on Minimum Contrast, AIC and
Goodness of Fit
Select Features Reliably with Cohen's Effect Sizes
Genotype Probabilities in Intermediate Generations of Inbreeding
Through Selfing
Regularization for Variable Selection in Model-Based Clustering
and Discriminant Analysis
Goodness-of-fit indexes for structural equation models
Hierarchical Models for Parametric and Semi-Parametric Analyses
of Semi-Competing Risks Data
Identifiability of Linear Structural Equation Models
Semi-Parametric Sample Selection Modelling with Continuous or
Discrete Response
Kernel PCA projection, and semi-supervised variant
Path diagrams and visual analysis of various SEM packages'
output
Structural Equation Modeling Using Partial Least Squares
Semiparametric Estimation of Stochastic Frontier Models
Useful Tools for Structural Equation Modeling
Tool for sending interactive plots with tool-tip content
Sensitivity Analysis for Comparative Methods
Global Sensitivity Analysis of Model Outputs
Sensitivity Analysis for 2x2xk Tables in Observational Studies
Sensitivity Analysis for Case-Control Studies
Sensitivity Analysis in Observational Studies
Sensitivity analysis using weighted M-statistics
Principal Stratification Sensitivity Analysis Functions
Analysis of Sensory and Consumer Data in a Mixed Model Framework
Simultaneous Model-Based Clustering and Imputation via a
Progressive Expectation-Maximization Algorithm
Thurstonian Models for Sensory Discrimination
Maximum Likelihood Estimation and Likelihood Ratio Test
Functions for Separable Variance-Covariance Structures
Sequential Allocation for Prospective Experiments
Simulation and Group Sequential Monitoring of Randomized
Two-Stage Treatment Efficacy Trials with Time-to-Event
Endpoints
A Tool to Associate FASTA Sequences and Features
Simple GUI for Graph Based Visualization of Cluster of DNA
Sequence Reads
Hidden Markov Models for Life Sequences and Other Multivariate,
Multichannel Categorical Time Series
Biological Sequences Retrieval and Analysis
Network Module-Based Model in the Differential Expression
Analysis for RNA-Seq
Meta-Analysis of Region-Based Tests of Rare DNA Variants
Efficiently Read Sequence Data (VCF Format, BCF Format and METAL
Format) into R
Sequential Monitoring of Clinical Trials
Generates a permutation matrix based upon a sequence
Simulation and visualization of restriction enzyme cutting
pattern from DNA sequences
Exact Sequential Analysis for Poisson and Binomial Data
Copy Number Estimation from Tumor Genome Sequencing Data
Infrastructure for Ordering Objects Using Seriation
Estimating Infection Rates from Serological Data
A Simple HTTP Server to Serve Static Files or Dynamic Documents
Spatially Explicit Structural Equation Modeling
Functions for interacting with, saving and restoring R sessions
Functions for Set-Theoretic Multi-Method Research and Advanced
QCA
Set (Normal) Random Number Generator and Seed
Sets, Generalized Sets, Customizable Sets and Intervals
Automatically Set the Width Option on Terminal Emulators
Calculates the historic date of extinction given a series of
sighting events
Straightforward Filtering Index for AP-MS Data Analysis (SFINX)
Utilities from "Seminar fuer Statistik" ETH Zurich
Functions for Systems Factorial Technology Analysis of Data
Spatial Graph Based Clustering Summaries for Spatial Point
Patterns
Stochastic Gradient Descent for Scalable Estimation
An Object-Oriented Framework for Geostatistical Modeling in S+
Fit a GLM (or cox model) with a combination of lasso and group
lasso regularization
An R package for power and boundary calculations in
pre-licensure vaccine trials using a sequential generalized
likelihood ratio test
Student Growth Percentiles & Percentile Growth Trajectories
Sparse Generalized Principal Component Analysis
Sparse Group Partial Least Square Methods
Enrichment Analysis of CRISPR/Cas9 Knockout Screen Data
Functions for plotting graphical shapes, colors
Change-Point Estimation using Shape-Restricted Splines
Tools for Analyzing Planar Shape and Associated Patterns
Collection and Analysis of Otolith Shape Data
Shape Selection for Landsat Time Series of Forest Dynamics
Statistical Significance of the Sharpe Ratio
Models and Data Sets for the Study of Species-Area Relationships
Tools to Support the Sheffield Elicitation Framework (SHELF)
Bootstrap 2 Web Components for Use with Shiny
A Server-Side File System Viewer For Shiny
Perform Common JavaScript Operations in Shiny Apps using Plain R
Code
Interactive Visual and Numerical Diagnostics and Posterior
Analysis for Bayesian Models
SHrinkage covariance Incorporating Prior knowledge
Slope Heuristic for Block-Diagonal Covariance Selection in High
Dimensional Gaussian Graphical Models
Convert a SpatialLinesDataFrame object to a "igraph-class"
object
Global, Parameterwise and Joint Shrinkage Factor Estimation
The Shuffle Estimator for Explainable Variance
Subgroup Identification Based on Differential Effect Search
Substitution and Indel Distances to Infer Evolutionary
Relationships
Perform Exact Sign Test and Asymptotic Sign Test in Large
Samples
Identify and Visualize Significantly Responsive Branches in a
Phylogenetic Tree
Calculate ANSI S3.5-1997 Speech Intelligibility Index
A Collection of functions for similarity analysis of vegetation
data
Simultaneous inference for diversity indices
Simulating Longitudinal Data with Causal Inference Applications
Simultaneous Comparisons for Multiple Endpoints
Safe Implementation of Monte Carlo Tests
Structure for Organizing Monte Carlo Simulation Designs
Simulation of Ecological (and Other) Dynamic Systems
Constrained Single Index Model Estimation
SIMEX- and MCSIMEX-Algorithm for measurement error models
Simulated Survival and Hazard Analysis for Time-Dependent
Exposure
A Framework for Data-Driven Stochastic Disease Spread
Simulations
Subnetwork Integration for Multi-Modal Signatures
Simulation of Event Histories for Multi-State Models
Statistical Inference for MOdular NEtworks (SIMoNe)
Simulation Model of Expression Data for Pathway Analysis
Tools for Simulating and Plotting Quantities of Interest
Estimated from Cox Proportional Hazards Models
Simple Graph Data Types and Basic Algorithms
Bayesian Inference and Sensitivity Analysis for Causal Effects
from 2 x 2 and 2 x 2 x K Tables in the Presence of Unmeasured
Confounding
Regression Analysis of Proportional Data Using Simplex
Distribution
Simulation of Synthetic Populations for Survey Data Considering
Auxiliary Information
Power Analysis for Generalised Linear Mixed Models by Simulation
Simulations to Predict the Number of RAD and GBS Loci
Linear Model Data Simulation and Design of Computer Experiments
Individual-Based, Spatially-Explicit Simulation and Analysis of
Multi-State Movements in River Networks and Heterogeneous
Landscapes
Tools for Simulation Studies in Parallel
'Simulates Univariate and Semi-Competing Risks Data Given
Covariates and Piecewise Exponential Baseline Hazards'
Nonparametric Simulation of RNA-Seq Data
Conduct Simulation Studies with a Minimal Amount of Source Code
Simulation process of 4 selection methods in predicting chemical
potent compounds
A SINful Approach to Selection of Gaussian Graphical Markov
Models
An Enhanced Chart for Simple and Truthful Representation of
Single Observations over Multiple Classes
Functions for Calculating Daily Solar Radiation and
Evapotranspiration
Supplementary Item Response Theory Models
SISUS: Stable Isotope Sourcing using Sampling
Some Invalid Some Valid Instrumental Variables Estimator
Super Imposition by Translation and Rotation Growth Curve
Analysis
Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' Header
Files
Format a number to a string with SI prefix
Sensitivity Indices with Dependent Inputs
Six Sigma Tools for Quality Control and Improvement
Estimating the Sizes of Populations at Risk of HIV Infection
from Multiple Data Sources Using a Bayesian Hierarchical Model
Data Transformation and Labelled Data Utility Functions
Data Visualization for Statistics in Social Science
Collection of Convenient Functions for Common Statistical
Computations
SNP-Set (Sequence) Kernel Association Test
Efficient meta analysis for the SKAT test
Sparse (Multicategory) Kernel Discriminant Analysis
Densities and Sampling for the Skellam Distribution
The Skew Hyperbolic Student t-Distribution
The Skillings-Mack Test Statistic for Block Designs with Missing
Observations
Send Messages, Images, R Objects and Files to 'Slack'
Channels/Users
Estimation and Use of the Quantile-Based Skew Logistic
Distribution
Serial Limiting Dilution Assay Statistics
Data Sets from Ramsey and Schafer's "Statistical Sleuth (2nd
Ed)"
Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd
Ed)"
Tools for Fitting Sparse Latent Factor Model
Maximin-Distance (Sliced) Latin Hypercube Designs
Discrete Prolate Spheroidal (Slepian) Sequence Regression
Smoothers
Smoothing methods for nonparametric regression and density
estimation
Sparse Multi-category Angle-Based Large-Margin Classifiers
Statistical Methods for the Analysis of Case-Control Point Data
Statistical Modeling of Animal Movements
Sparse Multivariate Analysis via Rank Transformation
Tools for Accessing Various Datasets Developed by the Foundation
SmarterPoland.pl
(Standardised) Major Axis Estimation and Testing Routines
Multiple Imputation of Covariates by Substantive Model
Compatible Fully Conditional Specification
A simple Monte Carlo optimizer using adaptive coordinate
sampling
Smoothed minimax concave penalization (SMCP) method for
genome-wide association studies
Data Sets for Statistical Methods in Customer Relationship
Management by Kumar and Petersen (2012)
Utility functions for sequential Monte Carlo
Data to accompany Smithson & Merkle, 2013
R functions and data from Chapter 5 of 'Statistical Methods for
Financial Engineering'
SMfSB 2e: Stochastic Modelling for Systems Biology, second
edition
Smooth Multivariate Interpolation for Gridded and Scattered Data
Provides two taxonomic coefficients from E. S. Smirnov
"Taxonomic analysis" (1969) book
Fitting Univariate Censored Regression Model Under the Family of
Scale Mixture of Normal Distributions
Single and Multi-Objective Optimization Test Functions
Functions Relating to the Smoothing of Numerical Data
Fitting illness-death model for interval-censored data
Smooth Hazard Ratio Curves Taking a Reference Value
Smoothed M-estimators for 1-dimensional location
Survival Regression with Smoothed Error Distribution
Smooth Estimation of GPD Shape Parameter
Practicals for use with Davison (2003) Statistical Models
Datasets for Agresti and Finlay's "Statistical Methods for the
Social Sciences"
The Skew-Normal and Skew-t Distributions
Gadget N-body cosmological simulation code snapshot I/O
utilities
Snipping methods for robust estimation and clustering
Snowball stemmers based on the C libstemmer UTF-8 library
Easier cluster computing (based on snow)
Fault Tolerant Simple Network of Workstations
SNPs-based whole genome association studies
Maximally selected statistics for SNP data
Bivariate Gaussian Genotype Clustering and Calling for Illumina
Microarrays
Random Forest for SNPs to Prevent X-chromosome SNP Importance
Bias
Flexible writing of snpStats objects to flat files
Accessing, subsetting and plotting mouse SNPs
Standard and Nonstandard Statistical Models and Methods for Test
Equating
Memory management in R by delayed assignments
Specific Correspondence Analysis for the Social Sciences
Tools for Collecting Social Media Data and Generating Networks
for Analysis
Generates social networks based on distance
Social Position Indicators Construction Toolbox
Functions and Examples for "Software for Data Analysis"
SODA: Main and Interaction Effects Selection for Discriminant
Analysis and Logistic Regression
Optimal Discriminant Clustering(ODC) and Sparse Optimal
Discriminant Clustering(SODC)
Interfaz interactiva con fines didacticos
Matrix Completion via Iterative Soft-Thresholded SVD
A package to consistently represent soil properties along a soil
profile
Models of Soil Organic Matter Decomposition
Soil Spectroscopy Tools and Reference Models
Functions for Soil Texture Plot, Classification and
Transformation
Implementation of Parametric Formulas for Soil Water Retention
or Conductivity Curve
Solar Position Algorithm for Solar Radiation Applications
General-Purpose Optimisation With the Self-Organising Migrating
Algorithm
SOM Bound to Realize Euclidean and Relational Outputs
Controlling the Generalized Familywise Error Rate
Estimating Abundance of Clones from DNA fragmentation data
Single Objective Optimization Benchmark Functions
Load Russian Economic Indicators from the Archive of Economic
and Social Data
Non-Parametric Estimation of the Off-Pulse Interval of a Pulsar
Estimation using Sequential Offsetted Regression
Turns a data frame into an HTML file containing a sortable
table
Search Contributed R Packages, Sort by Package
An R client for the OGC Sensor Observation Service
Stochastic Ordering Using Permutations (and Pairwise
Comparisons)
Fits a Non-Parametric Bayesian Source Attribution Model
Tools for the Reading and Tokenization of R Code
Soybean Nested Association Mapping Dataset
Design and Simulation of seamless Phase II-III Clinical Trials
Implements The Sequential Predictions Algorithm
SPA3G: R package for the method of Li and Cui (2012)
A Program to Estimate Animal Abundance and Density using
Bayesian Spatially-Explicit Capture-Recapture Models
Sparse conditional graph estimation with joint additive models
Classes and Methods for Spatio-Temporal Data
Spatial and Phylogenetic Analysis of Community Diversity
Spatially Weighted Context Data for Multilevel Modelling
Develop and Run Spatially Explicit Discrete Event Simulation
Models
Mixed Models, Particularly Spatial GLMMs
Perform rare variants association analysis based on summation of
partition approaches
Perform sparse hierarchical clustering and sparse k-means
clustering
Sparklines and Graphical Tables for TeX and HTML
Sparse Biclustering of Transposable Data
Learning Sparse Bayesian Networks from High-Dimensional Data
Utilities for Learning Sparse Bayesian Networks
Sparse and Regularized Discriminant Analysis
Scaling Count and Binary Data with Sparse Factor Analysis
Sparse Learning Algorithms Using a LASSO-Type Penalty for
Coefficient Estimation and Model Prediction
RcppEigen back end for sparse least trimmed squares regression
Multivariate Normal Functions for Sparse Covariance and
Precision Matrices
Fit sparse linear regression models via nonconvex optimization
Sparse Bayesian Models for Regression, Subgroup Analysis, and
Panel Data
Sparse-aware Maximum Likelihood for Structural Equation Models
Sparse Truncated Singular Value Decomposition (from 'SVDLIBC')
Solution Paths of Sparse Linear Support Vector Machine with
Lasso or ELastic-Net Regularization
Sparse Time Series Chain Graphical Models
A Package for Sparse VAR/VECM Estimation
Simulation Parameter Analysis R Toolkit ApplicatioN: Spartan
Spatio-Temporal Modeling of Large Data Using a Spectral SPDE
Approach
Graph Edge Computations for Spatial Point Patterns
Functions for Kriging and Point Pattern Analysis
Computation of Spatial Covariance Matrices for Data on
Rectangles
Methods and Data for Spatial Epidemiology
Application of 2D Convolution Kernel Filters to Matrices or 3D
Arrays
Hierarchical spatial generalized extreme value (GEV) modeling
with Bayesian Model Averaging (BMA)
Nonparameteric estimation of spatial segregation in a
multivariate point process
Performs spatial NBDA in a Bayesian context
Multivariate nonparametric methods based on spatial signs and
ranks
Segregation measures for multitype spatial point patterns
Estimation of spatial tail dependence models
R functions for working with spatial data
Regularized Spatial Maximum Covariance Analysis
Regularized Principal Component Analysis for Spatial Data
Spatial Analysis of Field Trials with Splines
Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Bayesian Spatial Survival Analysis with Parametric Proportional
Hazards Models
Univariate and Multivariate Spatial-temporal Modeling
Bayesian Modeling and Analysis of Spatially Correlated Survival
Data
Statistical Process Control -- Collection of Some Useful
Functions
Functions for Calibrating Control Charts
A New Reduced-Rank Linear Discriminant Analysis Method
Spatial Coverage Sampling and Random Sampling from Compact
Geographical Strata
Sparse Estimation of a Covariance Matrix
Spatial Dependence: Weighting Schemes, Statistics and Models
Data Manipulation Verbs for the Spatial Classes
Spatio-Dynamic Wetland Plant Communities Model
Tools for Nuclear Magnetic Resonance Spectrum Alignment and
Quantitative Analysis
Alternative spectral clustering, with automatic estimation of k
Statistical package for species richness estimation
Prepare Species Distributions for the Use in Phylogenetic
Analyses
Specificity of personality trait-outcome (or trait-trait)
associations
Metabolomics and Spectral Data Analysis and Mining
Forecast Verification Routines for the SPECS FP7 Project
Approximate Gaussian Processes Using the Fourier Basis
Singular Spectrum Analysis (SSA) Tools for Time Series Analysis
Spectra Visualization, Organizer and Data Preparation
Estimation of the Relative Importance of Factors Affecting
Species Distribution Based on Stability Concept
Fitting Linear and Generalized Linear Models to Large Data Sets
Semiparametric efficient estimation for a two-sample treatment
effect
Calculation of the Standardised Precipitation-Evapotranspiration
Index
Auxiliary Functions to Estimate Centers of Biodiversity
Spatial Error Estimation and Variable Importance
Interface Between GRASS 6+ Geographical Information System and R
Statistical Patterns in Genomic Sequences
Numerical Integration over Spheres and Balls in n-Dimensions;
Multivariate Polar Coordinates
Spherical Wavelets and SW-based Spatially Adaptive Methods
Estimation of spatial autoregressive models with and without
heteroskedastic innovations
A Genetic-Based Assay for the Identification of Cell Lines
Compute SPI Index using the Methods Genetic Algorithm and
Maximum Likelihood
Prediction and variable selection using spike and slab
regression
Bayesian Variable Selection and Model Choice for Generalized
Additive Mixed Models
Sparse Generative Model and Its EM Algorithm
Spatial and Space-Time Point Pattern Analysis
Stack and Reshape Datasets After Splitting Concatenated Values
Econometric Models for Spatial Panel Data
Sparse Partial Least Squares (SPLS) Regression and
Classification
Wrapper Functions for SPM (Statistical Parametric Mapping)
Version 12 from the Wellcome Trust Centre for Neuroimaging
Semiparametric Maximum Likelihood Method for Interactions
Gene-Environment in Case-Mother Control-Mother Designs
Interface to Species Occurrence Data Sources
Semiparametric proportional odds rate model
Sparse Arrays and Multivariate Polynomials
Statistical Package for Reliability Data Analysis
Selecting a Predictive Function for a Given Gene Expression Data
Calculate Species Richness and Extrapolation Metrics
Framework for Screening Prognostic Interactions
Sparse and Non-Sparse Partial Robust M Regression and
Classification
Wald's Sequential Probability Ratio Test
Optimization of Sample Configurations using Spatial Simulated
Annealing
Shape-Preserving Uni-Variate and Bi-Variate Spline Interpolation
Site Percolation on Square Lattice (SPSL)
spsmooth: An Extension Package for 'mgcv'
Spatially Varying and Spatio-Temporal Dynamic Linear Models
Nonparametric Hypothesis Tests of Isotropy and Symmetry
Functions for Spatial Thinning of Species Occurrence Records for
Use in Ecological Models
Spatio-Temporal Bayesian Modelling Using R
Functions and Datasets for "Introduction to Scientific
Programming and Simulation Using R"
Rendering Parameterized SQL and Translation to Dialects
Squared Extrapolation Methods for Accelerating EM-Like Monotone
Algorithms
Color-Based Plots for Multivariate Visualization
Statistical Quantification of Individual Differences
Statistical Ranking Color Scheme for Multiple Pairwise
Comparisons
Nonparametric Smooth ROC Curves for Continuous Data
The Stepwise Response Refinement Screener (SRRS)
'dplyr'-Like Syntax for Summary Statistics of Survey Data
Fisheries Stock Assessment Simulation Testing with Stock
Synthesis
Sample Size Adjusted for Nonadherence or Variability of Input
Parameters
Robust Correlation Estimation and Testing Based on Spatial Signs
Sample Size Determination (SSD) for Unordered Categorical Data
Tools Developed for Structured Sufficient Dimension Reduction
(sSDR)
Fitting of parametric models using summary statistics
Local and remote system commands with output and error capture
Sample Size Calculations for Microarray Experiments
Sample Size Calculation for RNA-Seq Experimental Design
Skew Scale Mixtures of Normal Distributions
Robust estimation and inference in sample selection models
Estimating Hidden Population Size using Respondent Driven
Sampling Data
Two-dimensional sociometric status determination with rating
scales
Sample Size Calculation using Restricted Mean Survival Time
Tools for Importing Files in the Triple-s (Standard Survey
Structure) Format
Fitting Semi-Parametric log-Symmetric Regression Models
Shrinkage t Statistic and Correlation-Adjusted t-Score
Estimate the Four Parameters of Stable Laws using Different
Methods
Stable Specification Search in Structural Equation Models
Stylized concatenation of data.frames or ffdfs
ODBC Connection Class for Package stacomiR
Mixture of Two-Stage Logistic Regressions with Fixed Candidate
Knots
Modelling the Population Dynamics of a Stage-Structured Species
in Continuous Time
Statistical Analysis of Mixed Ploidy Populations
Well-Formatted Regression and Summary Statistics Tables
Modelling Space Time AutoRegressive Moving Average (STARMA)
Processes
Tools Inspired by 'Stata' to Manipulate Tabular Data
Extract Statistics from Articles and Recompute p Values
Statistical Analysis for Environmental Data
U.S. State Cartogram Heatmaps in R; an Alternative to Choropleth
Maps for USA States
Get Hourly Meteorological Data from Global Stations
Easy Data Manipulation, Data Quality and Statistical Checks
Software Tools for the Statistical Analysis of Network Data
Common R Scripts and Utilities Used by the Statnet Project
Software
A Graphical User Interface for Network Modeling with 'Statnet'
Statistical Tools for Social Network Analysis
Statistical Rank Aggregation: Inference, Evaluation, and
Visualization
Statistical Analysis of Metabolite Profile
Calculate the Standardized Difference for Numeric, Binary and
Category Variables
ICA and Tests of Independence via Multivariate Distance
Covariance
Testing Steepness of Dominance Hierarchies
Semi-Parametric Stein-Like Estimator with Instrumental Variables
Subpopulation Treatment Effect Pattern Plot (STEPP)
L2 penalized logistic regression with a stepwise variable
selection
Stepwise detection of recombination breakpoints
Stereo Camera Calibration and Reconstruction
Klimontovich's S-Theorem Algorithm Implementation and Data
Preparation Tools
Calculation of the Standardized Temperature Index
Separable Gaussian Process Interpolation (Emulation)
Simultaneous Threshold Interaction Modeling Algorithm
Stineman, a consistently well behaved method of interpolation
Enhanced Seasonal Decomposition of Time Series by Loess
Estimation of the Structural Topic Model
A Tool for Structural Topic Model Visualizations
Plots a QQ-Norm Plot with several Gaussian simulations
Fit a Spatial Occupancy Model via Gibbs Sampling
Stochastic Profiling using Maximum Likelihood Estimation
Efficient Bayesian Inference for Stochastic Volatility (SV)
Models
Real-Time Stock Price & Volume in China Market
Build stock models and analyze stock portfolios
Fast Functions for Stock Market Analysis
R Functions for Solving Stoichiometric Equations
Write Storm Bolts in R using the Storm Multi-Language Protocol
Stochastic Simulator for Reliability Modeling of Repairable
Systems
Selection of Training Populations by Genetic Algorithm
Stochastic Process Model for Analysis of Longitudinal and
Time-to-Event Outcomes
Space-Time Point Pattern simulation, visualisation and analysis
Perform residual analysis on space-time point process models
Stratigraphic Tree Analysis for Palaeontology
Summaries and Population Structure Analyses of Genetic Data
Univariate Stratification of Survey Populations
Performs Stratified Covariate Balancing for Data with Discrete
and Continuous Outcome Variables
Toolkit for the plotting and analysis of stratigraphic and
palaeontological data
Calculate Single Station Metabolism from Diurnal Oxygen Curves
Interface for MOA Stream Clustering Algorithms
Functions to help the process of learning structural equation
modelling
Fetch and plot financial stress index and component data
Computation and Estimation of Reliability of Stress-Strength
Models
Approximate String Matching and String Distance Functions
PPI and Gaussian Network Construction from Transcriptomic
Analysis Results Integrating a Multilevel Factor
Simple, Consistent Wrappers for Common String Operations
Structured Trellis Displays Without Strips for Lattice Graphics
R Codes and Datasets for Generalized Linear Mixed Models: Modern
Concepts, Methods and Applications by Walter W. Stroup
Testing, Monitoring, and Dating Structural Changes
Multiple Testing for Hypotheses with Hierarchical or Group
Structure
STRUctural Modeling of Latent Variables for General Pedigree
Process Control and Internal Validation of Forensic STR Kits
Class and Methods for Structural Time Series Models
Functions for a Variety of Stylometric Analyses
Maximum-Likelihood Cultural Consensus Analysis with Sub-Cultures
Detect Subgroup with an Enhanced Treatment Effect
Methods for exploring treatment effect heterogeneity in subgroup
analysis of clinical trials
Gene selection using Lasso for Microarray data with user-defined
genes fixed in model
Within Outlying Mean Index Analysis: Exploratory Niche Methods
Identify Metabolic Subpathways Mediated by MicroRNAs
Identify Signal Subpathways Competitively Regulated by LncRNAs
Based on ceRNA Theory
Unconstrained Optimization using the Subplex Algorithm
Computes Copula using Ranks and Subsampling
Computing Subscores in Classical Test Theory
An Ensemble Method for Combining Subset-Specific Algorithm Fits
Cluster analysis to find molecular subtypes and their assessment
Visual Exploration of Protein Alignments Resulting from Multiple
Substitution Matrices
Tools for Making and Spoiling Sudoku Games
Dataframe Summaries, Frequency Tables and Numerical Summaries
with Customizable Output
Supervised Clustering of Predictor Variables such as Genes
Generating Robust Biclusters from a Bicluster Set (Ensemble
Biclustering)
R Code for Testing Markov Chain Nonconvergence
Exact Test and Visualization of Multi-Set Intersections
Implements the supervised multidimensional scaling (superMDS)
proposal of Witten and Tibshirani (2011)
Supervised Classification Learning and Prediction using Patient
Rules Induction Method (PRIM)
Basic Functions for Supporting an Implementation of Best-Worst
Scaling
Basic Functions for Supporting an Implementation of Choice
Experiments
Calculates Likelihood Support Intervals for Common Data Types
Fitting Hansen Models to Investigate Convergent Evolution
Evaluation of Surrogate Endpoints in Clinical Trials
LaTeX descriptive statistic reporting for survey data
Inference for model-free between-group parameters for censored
survival data
Estimate accuracy measures for risk prediction markers from
survival data
Estimators of prediction accuracy for time-to-event data
C-statistics for risk prediction models with censored survival
data
Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic
Phenomena
Tools for the Bootstrap with Survey Data
Generate a Survey that can be Completed by Survey Respondents
The Gini concentration test for survival data
IDI and NRI for comparing competing risk prediction models with
censored survival data
Penalised Maximum Likelihood for Survival Analysis Models
Time-dependent ROC curve estimation from censored survival data
Survival Prediction by Joint Analysis of Microarray Gene
Expression Data
Analysis of Proportional Hazards Model with Sparse Longitudinal
Covariates
Miscellaneous Functions for Survival Data
Presmoothed Estimation in Survival Analysis
Survival analysis for recurrent event data
Weibull Regression for a Right-Censored Endpoint with
Interval-Censored Covariate
Simulation of Simple and Complex Survival Data
Power Calculations for SNP Studies with Censored Outcomes
Measures of the Sturdiness of Regression Coefficients
Surrogate variable analysis using partial least squares in a
gene expression study
2d and 3d Space-Varying Coefficient Models
Interfaces to Various State-of-Art SVD and Eigensolvers
SciViews GUI API - Dialog boxes using Tcl/Tk
R 'Htmlwidget' to Add Pan and Zoom to Almost any R Graphic
SciViews GUI API - Functions to manage GUIs
3D Animated Interactive Visualizations Using SVG
SciViews GUI API - IDE and code editor functions
SciViews GUI API - Functions to interface with Komodo Edit/IDE
Linear/Nonlinear SVM Classification Solver Based on ADMM and
IADMM Algorithms
SciViews GUI API - Miscellaneous functions
Causal Effect Estimation and Diagnostics with Support Vector
Machines
SciViews GUI API - Tools (wrapper for packages tools and
codetools)
Nomograms for Right-Censored Outcomes from Survey Designs
A package for complex surveys including plausible values
Visualization, analysis and adjustment of high-dimensional data
in respect to sample annotations
Ensemble Learning Algorithms Based on Support Vector Machines
A multi-OS implementation of the TAMU SWAT model
Utilities for Sweave Together with TeX 'listings' Package
Miscellaneous Functions for Southwest Fisheries Science Center
Air Quality Data of Switzerland for one year in 30 min
Resolution
Switching nonparametric regression models for a single curve and
functional data
Installing, Managing, and Switching Between Distinct Sets of
Installed Packages
Publish Package Manifests to GitHub Gists
Retrieving, Organizing, and Analyzing Estuary Monitoring Data
Efficient Constrained Based Modelling in R
Cost Constrained FLux Balance Analysis: MetabOlic Modeling with
ENzyme kineTics (MOMENT)
Dynamic FBA : Dynamic Flux Balance Analysis
Using Gene Expression Data to Improve Flux Balance Analysis
Predictions
Symbolic central and noncentral moments of the multivariate
normal distribution
Framework for the Analysis of Genomic Prediction Data using R
Methods for computing spatial, temporal, and spatiotemporal
statistics
Subsample Temporal Data to Synchronal Events and Compute the MCI
SYNCSA - Analysis of functional and phylogenetic patterns in
metacommunities
Interface to The Synergizer service for translating between sets
of biological identifiers
Calculate and Visualize Synergy Scores for Drug Combinations
Inference and Analysis of Sympatry Networks
Synthetic Likelihood methods for intractable likelihoods
Synthetic RNA-Seq Network Generation and Mutual Information
Estimates
Synthetic Control Group Method for Comparative Case Studies
Synthetic Microdata and Spatial MicroSimulation Modeling for ACS
Data
Generating Synthetic Versions of Sensitive Microdata for
Statistical Disclosure Control
Estimating Systems of Simultaneous Equations
Extracts Sentiment and Sentiment-Derived Plot Arcs from Text
Functions for Creating Summary Tables for Statistical Reports
Write Formatted Tables in Excel Workbooks
Produces Summary Tables and Exports Them to Multi-Tab
Spreadsheet Format (.xls or .xlsx)
Create "Table 1" to Describe Baseline Characteristics
Represents tables as semi-graphic displays
Tableplot, a Visualization of Large Datasets
Tabplotd3, interactive inspection of large data
Helpers for Data Analysis and Presentation Focused on Undergrad
Psychology
Minimum Distance Estimation of Tail Dependence Models
Estimate the Probability in the Upper Tail of the Aggregate Loss
Distribution
A Two-Stage Approach to Maximize Interpretability of Drug
Response Models Based on Multiple Molecular Data Types
Time Course Analysis of Variance for Microarray
Flexible Tree Taper Curves Based on Semiparametric Mixed Models
Replicate Tariff Method for Verbal Autopsy
Collection of utility and convenience functions
Earthquake Traveltime Calculations for 1-D Earth Models
Efficient Computation and Testing of the Bergsma-Dassios Sign
Covariance
Clean Covariance Matrices Using Random Matrix Theory and
Shrinkage Estimators for Portfolio Optimization
Taxonomic Information from Around the Web
Taxonomic Standardization of Plant Species Names
Functions for tuberculosis diagnostics research
Tree Branches Evaluated Statistically for Tightness
Survival Analysis using a Transform-Both-Sides model
Simple TCGA Data Access for Integrated Statistical Analysis in R
Retrieve Genomic and Clinical Data from TCGA
Time-Course Gene Set Analysis for RNA-Seq Data
Advanced Data Analysis of Immune Receptor Repertoires
Statistical Tools for Topological Data Analysis
Analyze High-Dimensional Data Using Discrete Morse Theory
A Boosted Tweedie Compound Poisson Model
Gene Network Inference from Time-Series Transcriptomic Data
Time-Domain Deconvolution of Seismometer Response
Nonparametric Estimation of Time-Dependent ROC Curve from Right
Censored Survival Data
Demonstrations for Teaching and Learning
Selection of Samples and Parameter Estimation in Finite
Population
Fits neural networks to learn about back propagation
Turbulence Time Series Event Detection and Classification
Trimmed Elemental Estimation for Linear Models
Model-Based Clustering and Classification with the Multivariate
t Distribution
Social Representation Theory Application: The Free Evocation of
Words Technique
Methods for Temporal Disaggregation and Interpolation of Time
Series
Advanced tensors arithmetic with named indices
Blind Source Separation Methods for Tensor-Valued Observations
Covariance Inference and Decompositions for Tensor Datasets
Test for A+B Traditional Escalation Rule
Fit, Simulate and Diagnose Models for Network Evolution Based on
Exponential-Family Random Graph Models
Visualisation, verification and calibration of ternary
probabilistic forecasts
Diversification Rate Estimation and Fast Simulation of
Reconstructed Phylogenetic Trees under Tree-Wide
Time-Heterogeneous Birth-Death Processes Including
Mass-Extinction Events
Missing Item Responses Imputation for Test and Assessment Data
Tests and checks characteristics of R objects
Bootstrap Test for Similarity of Dose Response Curves Concerning
the Maximum Absolute Deviation
GUI for Entering Test Items and Obtaining Raw and Transformed
Scores
Statistical tests to compare two survival curves with recurrent
events
Treatment Effect eXplorer for Microbial Ecology eXperiments
(using Sequence Counts)
Conversion of R Regression Output to LaTeX or HTML Tables
Fast Text Mining Framework for Vectorization and Word Embeddings
Functions for Text Mining and Topic Modeling
Textual Data Analysis Package used by the TXM Software
n-Gram Text Regression, aka Concise Comparative Summarization
Detect Text Reuse and Document Similarity
Technology Forecasting using DEA (Data Envelopment Analysis)
Efficient and Accurate P-Value Computation for Position Weight
Matrices
The Standard Distribution Functions for the Truncated
Generalised Gamma Distribution
Binary Regressions under Independent Student-t Priors
Temperature Measurement with Thermocouples, RTD and IC Sensors
Design and Analysis of Clinical Non-Inferiority or Superiority
Trials with Active and Placebo Control
Thresholded variable selection and prediction based on
estimating equations
ML Estimator for Baseline-Placebo-Treatment (Three-Group)
Experiments
Interactive 3D Scatter Plots, Networks and Globes
Represent Precise Coordinates in Three Words
Threshold Regression for Interval-Censored Data with Cure-Rate
or without Cure-Rate Model
Three-Stage Least Squares Estimation for Systems of Simultaneous
Equations
Execution Functions for Tick Data Back Test
Functions for timing R scripts, as well as implementations of
Stack and List structures
Create dynamic reports using a TiddlyWiki template
Tide Analysis and Prediction of Predominantly Semi-Diurnal Tides
A Grammar for Turning 'JSON' into Tidy Tables
Easily Tidy Data with `spread()` and `gather()` Functions
Text Mining using 'dplyr', 'ggplot2', and Other Tidy Tools
Pre-Process of Time Series Data Set in R
R Tools for Inferring New Immunoglobulin Alleles from Rep-Seq
Data
Load Census TIGER/Line Shapefiles into R
Hidden Markov Models for ChIP-on-Chip Analysis
Characterization of functional genes in complex microbial
communities using tiling DNA microarrays
Variable Selection via Tilted Correlation Screening Algorithm
Survival and Competing Risk Analyses with Time-to-Event Data as
Covariates
Rmetrics - Chronological and Calendar Objects
Time Delay Estimation for Stochastic Time Series of
Gravitationally Lensed Quasars
Timeline and Time Duration-Related Tools
Time-ordered and time-aggregated network analyses
Flexible Regression Models for Survival Data
Time-Dependent ROC Curve and AUC for Censored Survival Data
Bootstrap computations for time series objects
Detecting Differentially Expressed Genes in Time Course RNA-Seq
Data
Rmetrics - Financial Time Series Objects
Manage Time Series with R and PostgreSQL
Seasonal/Sequential (Instants/Durations, Even or not) Time
Series
Interface to the TimeTree of Life Webpage
Create Interactive Timeline Visualizations in R
Target Inhibition Interaction using Maximization and
Minimization Averaging
Fitting Separable Nonlinear Models in Spectroscopy and
Microscopy
TIMe Series Analysis and Control package
Tinflex - Universal Non-Uniform Random Number Generator
Using Tip Dates with Phylogenetic Trees in BEAST (Software for
Phylogenetic Analysis)
Automated measure-based classification for flint tools
Enhanced Tipping Point Displays the Results of Sensitivity
Analyses for Missing Data
Titration analysis for mass spectrometry data
Acid/Base, Complexation, Redox, and Precipitation Titration
Curves
Pairwise Distance Estimation with TKF91 and TKF92 Model
Effects under Linear, Logistic and Poisson Regression Models
with Transformed Variables
Linear Student-t Mixed-Effects Models with Censored Data
Two-level normal independent sampling estimation
Template Model Builder: A General Random Effect Tool Inspired by
ADMB
Targeted Maximum Likelihood Estimation for Network Data
Targeted Learning of a NP Importance of a Continuous Exposure
Feature Set Enrichment Analysis for Metabolomics and
Transcriptomics
Import texts from files in the Alceste format using the tm text
mining framework
Import Articles from 'Europresse' Using the 'tm' Text Mining
Framework
Import articles from Factiva using the tm text mining framework
Import Articles from 'LexisNexis' Using the 'tm' Text Mining
Framework
Retrieve Structured, Textual Data from Various Web Sources
Truncated Multivariate Normal and Student t Distribution
Temporal Network Autocorrelation Models (TNAM)
Software for Analysis of Weighted, Two-Mode, and Longitudinal
Networks
Big Data in-Database Analytics with Teradata Aster
Total Operating Characteristic Curve and ROC Curve
A Consistent Interface to Tokenize Natural Language Text
Fundamental Definitions and Utilities of the Time Oriented
Language (TOL)
Functions for Calculating Tolerance Intervals
Function for Converting Cardinal to Ordinal Numbers by Adding a
Language Specific Ordinal Indicator to the Number
Inference, Aggregation and Visualization for Top-K Ranked Lists
Implementation of the hydrological model TOPMODEL in R
Gene Set Analysis Exploiting Pathway Topology
TOPSIS method for multiple-criteria decision making (MCDM)
Instrumental Variables Two Stage Least Squares estimation
Bootstrap Methods for 'ToxCast' High Throughput Screening Data
Experimental design for binary toxicity tests
Estimation of Transition Probabilities for the Illness-Death
Model
Estimation of Transition Probabilities in Multistate Models
A Tool for Downloading Functional Traits Data for Plant Species
Infrastructure for Running and Cycling Data from GPS-Enabled
Tracking Devices
Reconstruct animal tracks from magnetometer, accelerometer,
depth and optional speed data
Read, Manipulate and Visualise Magnetic Resonance Images
Tree Ring Analysis of Disturbance Events in R
An interface for creating GUIs modeled in part after traits UI
module for python
A Predictive Model for Trait Based Community Assembly of Plant
Species
Trajectory Miner: a Toolbox for Exploring and Rendering
Sequences
'TRFLP' Analysis and Matching Package for R
Automated Transcription of Audio Files Through the HP IDOL API
Bindings for the Google and Microsoft Translation APIs
Toolset for Translating SPSS-Syntax to R-Code
R Manuals Literally Translated in Korean
Fit Linear Transformation Models for Censored Data
Implementation of Transportation Problem Algorithms
Estimating a Survival Distribution in the Presence of Dependent
Left Truncation and Right Censoring
Sensitivity Analysis for Causal Inference
Discovery, Access and Manipulation of 'TreeBASE' Phylogenies
Numerical Calibration of Proxy-Climate Relationships
Centre of Mass Assessment and Consolidation of Trees
An Adaptive Multi-Scale Basis for High-Dimensional, Sparse and
Unordered Data
Phylogenetic Tree Manipulation Class and Methods
Estimating birth and death rates based on phylogenies
Exact and Asymptotic K Sample Permutation Test
'dplyr' Functionality for Matched Tree and Data Objects
Statistical Exploration of Landscapes of Phylogenetic Trees
Simulating Phylogenetic Trees under a General Model
Methods for Tree-Based Local Adaptive Thresholding
Create and Navigate Large Multi-Panel Visual Displays
Non-Parametric Trend Tests and Change-Point Detection
Odds Ratio Estimation for the Trend in Tend Model
Provides the Standard Distribution Functions for the Triangle
Distribution
Analysing and Visualizing Tribology Measurements
Some basic facilities for ternary fields and plots
Propensity Score Matching of Non-Binary Treatments
An Implementation of Common Response Time Trimming Methods
Trimmed opinion pools of trees in a random forest
A data smoothing approach to explore and test gene-environment
interaction in case-parent trio data
Tools for the Analysis of Animal Track Data
Triangulation of Irregularly Spaced Data
Metropolis Sampler and Supporting Functions for Estimating
Animal Movement from Archival Tags and Satellite Fixes
Social Relation Model (SRM) Analyses for Single or Multiple
Groups
Pseudo-Vectors Containing All Permutations, Combinations and
Subsets of Objects Taken from a Vector
Functions and Datasets to Accompany the Book "The R Software:
Fundamentals of Programming and Statistical Analysis"
Implementation the TrueSkill algorithm in R
GoF tests allowing for left truncated data
Semi-parametric estimators of truncated regression models
Trust Region Optimization for Nonlinear Functions with Sparse
Hessians
Calculate normalising constants for Bayesian time series models
Tools for Blind Source Separation for Time Series
Likelihood-ratio Tests for Two-Sample Comparisons
Nonlinear Time Series Models with Regime Switching
Time Series Analysis and Computational Finance
Entropy Based Analysis and Tests for Time Series
Mining Univariate and Multivariate Motifs in Time-Series Data
'TSdbi' Extensions to Wrap Miscellaneous Data Sources
Time Series Modeling for Air Pollution and Health
Tools for Temporal Social Network Analysis
T-Distributed Stochastic Neighbor Embedding for R (t-SNE)
Transposable Sphering for Large-Scale Inference with Correlated
Data
Improved Prediction Intervals for ARIMA Processes and Structural
Time Series
Instance Feature Calculation and Evolutionary Instance
Generation for the Traveling Salesman Problem
Functions for Baseline-Based Time Series Prediction
'TSdbi' Extension to Connect with 'SDMX'
Generic SQL Helper Functions for 'TSdbi' SQL Plugins
Ternary Search Tree for Auto-Completion and Spell Checking
Fitting and Predict Time Series Interactive Laboratory
Temporal Trend Analysis Graphical Interface
Sampling and Calculating the First and Second Moments for the
Doubly Truncated Multivariate t Distribution
Master Curve Estimates Corresponding to Time-Temperature
Superposition
Genome-wide DNA methylation sites screening by use of training
and testing samples
Tufte-style html document format for rmarkdown
Multi-objective parameter tuning for classifiers
Find every match, or orphan, duplicate, triplicate, or other
replicated values
A Suite of Convergence Acceleration Schemes for EM, MM and other
fixed-point algorithms
Turn vectors and lists of vectors into indexed structures
Convert R Markdown Files to DataCamp Light HTML Files
Lumped Hydrological Model for Education Purposes
Toolkit for Weighting and Analysis of Nonequivalent Groups
Twitter Collector for R and Export to 'SQLite', 'postGIS' and
'GIS' Format
Interactive manipulation of R expressions
Nonparametric test of equality between two copulas
Estimate Gene-Treatment Interaction Exploiting Randomization
Compute thresholds and power for two-stage gwas
Conditional Logistic Regression: A Two-Step Estimation Method
Parse Browser 'User-Agent' Strings into Data Frames
Functions to Simulate and Conduct Dose-Escalation Phase I
Studies
An Implementation of Re-Sampling Approaches to Utility-Based
Learning for Both Classification and Regression Tasks
UC Berkeley graduate division thesis template
Construct an Unsupervised Hidden Markov Model
Bayesian Analysis of a Non-Informative Parametrization for
Gaussian Mixture Distributions
Structural Equation Modelling in R with 'OpenMx'
Function estimation via Unbalanced Haar wavelets
Implements Models of Uncertainty into the Interpolation
Functions
Unification of Clustering Results from Multiple Datasets using
External Specifications
Tools for Creating Universal Numeric Fingerprints for Data
Stereological Unfolding for Spheroidal Particles
Collate Gene Annotation Data from Uniprot and NIH Gene Databases
Univarate shrinkage prediction in the Cox model
Abbreviate Strings to Short, Unique Identifiers
Finding Unique or Duplicated Rows or Columns for Atomic Matrices
Unimodal Penalized Spline Regression using B-Splines
Assessment and Evaluation of Formations in United
Measurement Units of Physical Quantities for R Vectors
United Nations General Assembly Voting Data
Updated Classification Methods using Unlabeled Data
Unsupervised Photometric Membership Assignment in Stellar
Clusters
A More Scalable Alternative to Venn and Euler Diagrams for
Visualizing Intersecting Sets
Unit Root and Cointegration Tests for Time Series Data
R Wrapper for the 'Bit.ly', 'Goo.gl' and 'Is.gd' URL Shortening
Services
Vectorised Tools for URL Handling and Parsing
Unit Root Tests for Seasonal Time Series
Historical and Contemporary Boundaries of the United States of
America
Create US cancer datasets from SEER, IARC, and US Census data
US Census 2000 Designated Places Shapefiles and Additional
Demographic Data
US Census 2000 Tract Level Shapefiles and Additional Demographic
Data
Uncertainty Analysis for Species Distribution Models
Replaced by 'states2k' -- United States of America Map with the
NAD 1983 Albers Projection
Data Sets, Etc. for the Text "Using R for Introductory
Statistics", Second Edition
Model-Based Clustering via Mixtures of Unrestricted Skew-t
Sactor Analyzer Models
Analyze System Scalability with the Universal Scalability Law
Construct, Evaluate and Plot Value and Utility Functions
Tools for generating and handling of UUIDs
Unbinned weighted histogram analysis method (UWHAM)
Vaccination Activities Coverage Estimation Model
Non-Domestic Vaccine Adverse Event Reporting System (VAERS)
Vaccine Data for Present
US Vaccine Adverse Event Reporting System (VAERS) Vaccine Data
for Present
Validation Tools for Artificial Neural Networks
One-Sided Multivariate Testing Procedures for Rating Systems
Results from the Virginia Lottery Draw Games
Large-Scale Bayesian Variable Selection Using Variational
Methods
Variance Estimation for Sample Surveys by the Ultimate Cluster
Method
Computes value at risk and expected shortfall for over 100
parametric distributions
VAR modelling: estimation, testing, and prediction
Capture the Genes and Variants Related to a Genetic Disease from
Public Databases and PubMed
Testing of Genotypic Variance Heterogeneity to Detect
Potentially Interacting SNP
High-Dimensional Screening for Semiparametric Longitudinal
Regression
An Algorithm for Morphometric Characters Selection and
Statistical Validation in Morphological Taxonomy
Variable Selection for Model-Based Clustering using the
Integrated Complete-Data Likelihood of a Latent Class Model
Sign Restrictions, Bayesian, Vector Autoregression Models
Pricing a variance swap on an equity index
Variational Bayes Discrete Mixture Model
Variational Bayes Latent Position Cluster Model for Networks
Variational Bayes Spike Regression Regularized Linear Models
Tree-Based Varying Coefficient Regression for Generalized Linear
and Ordinal Mixed Models
Variance Dispersion Graphs and Fraction of Design Space Plots
Variance dispersion graphs and Fraction of design space plots
for response surface designs
Plots of Scaled Prediction Variances for Response Surface
Designs
like base::sets tools but keeps duplicate elements
Vector Analysis using Graphical and Analytical Methods in 2D
Vector analysis using graphical and analytical methods in 3D
Tools to Encode Visualizations with the 'Grammar of
Graphics'-Like 'Vega-Lite' 'Spec'
Static and Dynamic 3D Plots for the 'vegan' Package
Access Vegetation Databases and Treat Taxonomy
Jost Diversity Measures for Community Data
Generate High-Resolution Venn and Euler Plots
Query and Install Specific Versions of Packages on CRAN
Creates Vertex Similarity Matrix for an Undirected Graph
Linear Mixed Models - An Introduction with Applications in
Veterinary Research
Vector Generalized Linear and Additive Models
Discrimination/Classification in very high dimension with linear
and quadratic rules
Vertical and Horizontal Inheritance Consistence Analysis
VIF Regression: A Fast Regression Algorithm For Large Data
Detecting Change-Points via VIFCP Method
Variational Bayesian Inference for Genome-Wide Regression
Visualization and Imputation of Missing Values
Multivariate Dependence Modeling with Vines
Combination of violin plot with mean and standard deviation
1-D Scatter Plots with Jitter Using Kernel Density Estimates
Plot Categorical Data Using Quasirandom Noise and Density
Estimates
Default Color Maps from 'matplotlib' (Lite Version)
Generation of Virtual Species Distributions
Network Visualization using 'vis.js' Library
Graph Probability Distributions with User Supplied Parameters
and Stats
Visualisation of Clusters in Multivariate Data
Fitting Routines for the Vitality Family of Mortality Models
Graphical visualization tools for complex observational data
with focus on health sciences (VizOR)
Frequency Matrix Approach for Assessing Very Low Frequency
Variants in Sequence Records
Variable Length Markov Chains ('VLMC') Models
GUI Tools to Process, Analyze and Plot Fisheries Data
Using V-algorithm and Newton-Raphson Method to Obtain
Multiple-objective Optimal Design
Generic Voss algorithm (random sequential additions)
Vowel Manipulation, Normalization, and Plotting
Metrics extraction of trees from T-LiDAR data
Genome Scans to Accommodate and Target Genetic and Non-Genetic
Effects on Trait Variance
Change Point Estimation for Regression with Varying Segments and
Heteroscedastic Variances
Generate 3D visualizations for data exploration on the web
Variance Ratio tests and other tests for Martingale Difference
Hypothesis
Variable selection for clustering and classification
A Collection of Tools for the Analysis of Remote Acoustic
Telemetry Data
Visualization of Univariate Data for Comparison
Tools for Preprocessing Visual World Data
Useful functions for visual word recognition research
A Graphical Tool for Wavelet (Cross) Correlation and Wavelet
Multiple (Cross) Correlation Analysis
R Interface to W3C Markup Validation Services
Multivariate Weather-State Approach Conditionally Skew-Normal
Generator
A package to simulate constrained phenotypes under a disease
model H1
Autocorrelation and Heteroskedasticity Correction in Fixed
Effect Panel Data Model
Random Walks in the Intersection of Hyperplanes and the
N-Simplex
Retrieve 'Magic' Attributes from Files and Directories
Weaning Age Reconstruction with Nitrogen Isotope Analysis
Visualisation and analysis of output files of the hydrological
model WASIM
Actual Evapotranspiration with Energy Balance Models
An R Package for Retrieval, Analysis, and Anomaly Calculation of
Daily Hydrologic Time Series Data
Fetch and Analyze Data from 'WaterML' and 'WaterOneFlow' Web
Services
Spatial Watershed Aggregation and Spatial Drainage Network
Analysis
Computes credible intervals for Bayesian wavelet shrinkage
A package of functions for computing wavelet filters, wavelet
transforms and multiresolution analyses
Wavelet routine for multiple correlation
Data Estimation using Weighted Averages of Multiple Regressions
Basic wavelet routines for one-, two- and three-dimensional
signal processing
Wild Binary Segmentation for Multiple Change-Point Detection
Programmatic Access to Data and Statistics from the World Bank
API
Multiple Change-Point Detection for Nonstationary Time Series
SOM Networks for Comparing Patterns with Peak Shifts
Detection of QTL effects in a small mapping population
World Development Indicators (World Bank)
Functions to Convert Between Weather Metrics
Tools for Handling and Scrapping Instant Weather Forecast Feeds
A New Format for Lossless and Lossy Image Compression
Tools for Reading Formatted Access Log Files
Weighted Portmanteau Tests for Time Series Goodness-of-fit
Weighted Scores Method for Regression Models with Dependent Data
Estimating Weight-Function Models for Publication Bias in R
A Hydraulics Package to Compute Open-Channel Flow over Weirs
Weighted Linear Fixed Effects Regression Models for Causal
Inference
Whole Genome Average Interval Mapping for QTL Detection using
Mixed Models
Wilcoxon based gene set enrichment analysis
WhatIf: Software for Evaluating Counterfactuals
{{mustache}} for R, logicless templating
White Matter Normalization for Magnetic Resonance Images using
Whitestripe
R Client for the World Health Organization API
Username, Full Name, Email Address, 'GitHub' Username of the
Current User
High-Speed Processing of VCF, FASTA and Alignment Data
Weighting by Inverse Distance with Adaptive Least Squares for
Massive Space-Time Data
Penalized Regression with Polynomial Basis Expansions
Functions and datasets of the german WikiBook "GNU R"
Public Subject Attention via Wikipedia Page View Statistics
Wilcoxon-based variable selection in cross-validation
Calculate Indices of Dynamic Interaction for Wildlife Telemetry
Data
Best Hand Analysis for Poker Variants Including Wildcards
windex: Analysing convergent evolution using the Wheatsheaf
index
Run Code 'With' Temporarily Modified Global State
Convert Between Spatial Objects and Well-Known Binary Geometry
GUI Implementing Bayesian Working Memory Models
Discriminant Analysis Methods by Weight Mahalanobis Distance and
bayes
Wavelet Leaders in Multifractal Analysis
Wavelet Methods for Time Series Analysis
Computes Weight of Evidence and Information Values
Computing Word Alignment Using IBM Model 1 (and Symmetrization)
for a Given Parallel Corpus and Evaluation
Matches words in one file with words in another file
Classical word pools used in studies of learning and memory
IRT Item-Person Map with 'ConQuest' Integration
Function for exporting data to SNNS pattern files
Cross-Platform Perl Based R Function to Create Excel 2003 (XLS)
and Excel 2007 (XLSX) Files
A Collection of Robust Statistical Methods
Functions for working with Worldwide Reference System (WRS)
Weighted Random Sampling without Replacement
Benchmark and Correctness Data for Weighted Random Sampling
Without Replacement
Who Are You? Bayesian Prediction of Racial Category Using
Surname and Geolocation
Weighted Subspace Random Forest for Classification
Weighted SVM with boosting algorithm for improving accuracy
Competing Risks Regression Models with Covariate-Adjusted
Censoring Weights
The W-Test on Genetic Interactions Testing
R Wrapper for the 'Wufoo.com' - The Form Building Service
Wegener Center Climate Uncertainty Explorer
x12 - wrapper function and structure for batch processing
Provide the 'x13ashtml' Seasonal Adjustment Binary
Extraction of Business Financial Information from 'XBRL'
Documents
Extensions of Exponential Random Graph Models
Common Infrastructure for Extensions of Exponential Random Graph
Models
Interface to the XGobi and XGvis programs for graphical data
analysis
Exploring Genomic Relations for Precision Interpretation Through
Enrichment, Similarity, Network and Annotation Analysis
Plotting ggplot2 Graphics in an XKCD Style
JAR Dependencies for the XLConnect Package
Read, write, format Excel 2007 and Excel 97/2000/XP/2003 files
Package required POI jars for the xlsx package
A Toolbox for Multivariate Meta-Analysis
Xiaobei's miscellaneous classes and functions
Tools for Parsing and Generating XML Within R and S-Plus
Markov Random Fields for High-Throughput Genetics Data
Exact Goodness-of-Fit Test for Multinomial Data with Fixed
Probabilities
Tools for Analyzing Crossover Interference
Tools for Nonlinear Mixed-Effect Model Building and Diagnostics
Assessing Functional Impact on Gene Expression of Mutations in
Cancer
Terminal Text Formatting Using Escape Sequences
Calculates Credit Risk Valuation Adjustments
A Method for Creating Xylophone-Like Frequency Density Plots
Yet Another Canonical Correlation Analysis Package
Nearest Neighbor Observation Imputation and Evaluation Tools
A Simple Wrapper for the k-Means Library Yakmo
Data exploration tools from Yale University
Methods to convert R data to YAML and back
Yield curve or zero-coupon prices interpolation and
extrapolation
Modelling and estimation of the yield curve
Analyze Cricket Performances Based on Data from Cricsheet
Plant Architectural Analysis with Yplant and QuasiMC
The Short-Term and Long-Term Hazard Ratio Model for Survival
Data
A Simple Approach to Scale Gene Expression Data Derived from
Different Platforms for Integrated Analyses
Imputation of Zeros and Nondetects in Compositional Data Sets
ZeBook Working with dynamic models for agriculture and
environment
Functions to Compute Compositional Turnover Using Zeta Diversity
Bayesian Inference for Zero-Inflated Count Models
R Interface to Zillow Real Estate and Mortgage Data API
Zero-Inflated Models for Count Time Series with Excess Zeros
Statistical models for word frequency distributions
Seismic Reflection and Scattering Coefficients
Bayesian Inference for Beta Regression and Zero-or-One Inflated
Beta Regression
S3 Infrastructure for Regular and Irregular Time Series (Z's
Ordered Observations)
Analytical Tools for Zooarchaeological Data
Analysis of numerical zooplankton images
Reproducible, Accessible & Shareable Species Distribution
Modelling
Dynamic Plots for Time Series Forecasting
Zebra-Striped Tables in LaTeX and HTML Formats
http://www.r-project.org,
http://www.cs.utexas.edu/users/sustik/QUIC
http://glaros.dtc.umn.edu/gkhome/views/metis
http://www.pcg-random.org/download.html
https://gcc.gnu.org/projects/gomp/
'Expectation-Maximization Binary Clustering for Behavioural
Annotation', (submitted to PLOS ONE)
For source code, development versions and issue tracker see
https://github.com/hofnerb/gamboostLSS
http://www.hiplar.org , http://icl.cs.utk.edu/magma/ ,
http://icl.cs.utk.edu/plasma/,
http://www.nvidia.com/object/cuda_home_new.html
The publishers web page is
http://www.crcpress.com/product/isbn/9781482204582
http://www.kasparrufibach.ch ,
http://www.ceremade.dauphine.fr/~fadoua ,
http://www.math.yorku.ca/~hkj
http://multcomp.R-forge.R-project.org The publishers web page is
http://www.crcpress.com/product/isbn/9781584885740
http://en.opasnet.org/w/Main_Page ,
http://en.opasnet.org/w/Modelling_in_Opasnet ,
http://en.opasnet.org/w/OpasnetUtils
https://github.com/abarbour/psd, Barbour and Parker (2014):
http://dx.doi.org/10.1016/j.cageo.2013.09.015, Riedel and
Sidorenko (1995): http://dx.doi.org/10.1109/78.365298
http://www.r-project.org, http://groovy.codehaus.org/,
http://www.groovy-lang.org/indy.html,
http://docs.groovy-lang.org/latest/html/api/index.html,
https://coherentlogic.com/middleware-development/rgroovy?source=cran
The database is described at:
http://astro.df.unipi.it/stellar-models/
Wing Wong's lab (http://www.stanford.edu/group/wonglab/) &
Stanford Genome Technology Center
(http://gluegrant1.stanford.edu/~DIC/)
Orphaned on 2014-10-16 at the request of the maintainer.
Orphaned on 2013-11-12 as the maintainer repeatedly failed to respond to requests for valid portable C++ code.
Orphaned on 2009-02-23 as maintainer address <amy_kapp@hotmail.com> bounced.
Orphaned and repaired on 2014-07-21 as Fortran errors were ignored.
Orphaned on 2014-01-12 as maintainer address <mpineda@math.ualbeta.ca> bounced.
Orphaned on 2014-02-07 as the maintainer could not maintain it officially any more.
Orphaned on 2014-12-07 as maintainer address <chenjun@mail.med.upenn.edu> bounced.
Orphaned on 2011-08-11 as requested by the original maintainer, Tamas K Papp <tpapp@princeton.edu>.
Orphaned on 2012-01-10 as maintainer address bounces and maintainer is untraceable.
Orphaned on 2013-12-20 as requested by the maintainer <rgentlem@gmail.com>.
Previous maintainer address bounced in Oct 2012, maintainer is unresponsive so orphaned 2012-12-06.
Orphaned on 2012-12-21 as the maintainer failed to respond to requests for an update for R >= 2.14.0
Orphaned on 2014-12-07 as maintainer address <sarah.gerster@isb-sib.ch> bounced.
Orphaned on 2013-12-21 as maintainer address <mgerster@health.sdu.dk> bounced.
Orphaned on 2015-06-20 as incomplete maintainer address was not corrected despite reminders.
Orphaned on 2015-03-01 and corrected by the CRAN team as misuse of \donttest was not corrected.
Orphaned on 2014-12-07 as maintainer address <shaoyu.li@stjude.org> bounced.
Removed on 2013-03-02 for licence incompatibility.
Orphaned on 2013-03-22: the maintainer is unresponsive.
Orphaned on 2014-06-16 as the maintainer address bounced.
abctools, Bagidis, BCBCSF, depth, dgmb, EBMAforecast, fractaldim, hyperdirichlet, informR, interplot, LSDinterface, magic, MetStaT, mlogitBMA, multicon, MultiPhen, multipol, mvmesh, mvProbit, plfm, population, pop.wolf, RcmdrPlugin.EACSPIR, RcmdrPlugin.EBM, RcmdrPlugin.epack, simSummary, spatialfil, spBayes, wux, zoib
ade4TkGUI, adegenet, adehabitat, adehabitatHR, adehabitatHS, adehabitatLT, adephylo, cati, DDD, ecospat, ENiRG, FactoClass, FD, genoPlotR, oncomodel, pamctdp, sideChannelAttack, subniche, treescape, VARSEDIG
mmod, pegas, PopGenReport, poppr, strataG
GNE, lba, LEAPFrOG, likelihoodAsy, mbbefd
adhoc, apex, apTreeshape, BAMMtools, BarcodingR, bayou, BioGeoBEARS, BPEC, Canopy, caper, cati, coalescentMCMC, CommEcol, convevol, corHMM, DAMOCLES, DDD, DiscML, distory, diversitree, ecospat, expoTree, FD, geiger, geomorph, GUniFrac, HAP.ROR, hisse, HyPhy, ips, iteRates, jrich, laser, MCMCglmm, metricTester, MiSPU, MonoPhy, MPSEM, mvMORPH, mvSLOUCH, OUwie, paleotree, pastis, pegas, perspectev, pez, phangorn, phybreak, phyclust, phyloclim, phylolm, phylotools, phyloTop, phytools, picante, RADami, rase, recluster, RNeXML, Rphylip, Rphylopars, Rsampletrees, rwty, sensiPhy, spider, strap, surface, TESS, treebase, TreePar, treeplyr, treescape, TreeSim, windex
arulesNBMiner, arulesSequences, arulesViz, ibmdbR, rCBA, recommenderlab
bayesMCClust, compositions, mpbart, ocomposition, siar
BinNonNor, GNE, LIHNPSD, mederrRank, NPCD, PoisBinNonNor, PoisBinOrdNonNor, PoisNonNor, RobPer
BatchJobs, cmaesr, ecr, flacco, mlr, netgen, rpn, smoof
bigalgebra, biganalytics, biglasso, bigpca, bigtabulate, GHap
bnstruct, cdb, CHCN, cherry, couchDB, GENEAread, muma, R4CouchDB, RCurl
addhaz, aods3, attribrisk, BACprior, bootES, boottol, cardidates, chngpt, CircStats, classyfire, Comp2ROC, Compind, cramer, dawai, DCluster, dhglm, DLMtool, equivalence, eventstudies, experiment, fishmethods, fishmove, frailtypack, gb, HPbayes, imputeYn, IUPS, joineR, laeken, LCAextend, mdhglm, MDSGUI, mem, nFactors, Oncotree, ordinalCont, pastecs, plsgenomics, popKorn, prLogistic, PsumtSim, QuantPsyc, R2WinBUGS, random.polychor.pa, reglogit, relaimpo, rtip, sampSurf, simboot, simpleboot, SiZer, survrec, TestSurvRec, timesboot, titan, tlm, truncSP, verification, wBoot
AtelieR, brainGraph, fit4NM, gWidgetsRGtk2, MetSizeR, PKgraph, playwith, rsgcc, RunuranGUI, sdcMicroGUI, WMCapacity
AER, alr3, alr4, bartMachine, bgmm, candisc, CrypticIBDcheck, DAMisc, Deducer, DiagTest3Grp, DistatisR, DJL, epr, extRemes, genridge, granova, heplots, hysteresis, ibd, ITEMAN, lmSupport, mlma, mma, muma, mvinfluence, papeR, pequod, phia, quantification, Rcmdr, RcmdrMisc, RcmdrPlugin.SM, seeg, specificity, stepp, systemfit, VARSEDIG
adabag, AntAngioCOOL, conformal, fscaret, hsdar, ordBTL
DRIP, flux, GAMens, iCluster, meta4diag, muma
cmrutils, crn, ensembleBMA, ensembleMOS, ImportExport, Interpol.T, kerdiest, MicSim, PhysActBedRest, RH2, RMAWGEN, StreamMetabolism, ViSiElse
adehabitatLT, CircOutlier, LogicForest, moveHMM, verification
CircOutlier, depth, isocir, localdepth, NPCirc, SOPIE, wle
BarcodingR, CepLDA, clv, ddalpha, EILA, geneSignatureFinder, kmlShape, KODAMA, kohonen, longitudinalData, mda, Modalclust, multisom, protoclass, svapls, wccsom
abodOutlier, AdaptFit, AssocTests, bios2mds, ccChooser, clusterSim, ClusterStability, clv, clValid, COMMUNAL, CORM, dbstats, divo, dpmixsim, FunCluster, gclus, geneSignatureFinder, GLDEX, ICGE, IntNMF, isopam, knnGarden, labdsv, maptree, MiSPU, MSeasy, NMF, nomclust, optpart, pamr, qrfactor, RPMM, spa, tclust, TraMineRextras, treeClust, TSclust, WeightedCluster
kml, kml3d, longitudinalData, MOCCA, wskm
crrp, crrstep, crskdiag, currentSurvival, gcerisk, missDeaths
adaptMCMC, adaptsmoFMRI, anominate, B2Z, BANOVA, bayesDccGarch, BayesFactor, BayesLCA, bayespref, BayesSAE, bayesSurv, Bayesthresh, bayou, BAYSTAR, Bergm, bisoreg, bmk, boral, coalescentMCMC, codadiags, cplm, cubfits, dclone, eiPack, elrm, endorse, FME, gemtc, HelpersMG, HSROC, HybridMC, hzar, iFad, InSilicoVA, lira, MasterBayes, mcgibbsit, MCMCglmm, MCMC.OTU, MCMCpack, mcmcplots, MCMC.qpcr, mcsm, metamisc, ocomposition, PhaseType, phcfM, phenology, popReconstruct, prevalence, R2MLwiN, R2WinBUGS, ramps, relevent, rjags, season, siar, SPACECAP, spatial.gev.bma, spBayes, spTDyn, stochvol, superdiag, TESS, Ultimixt, WMCapacity, zoib
asht, kaps, pAnalysis, RcmdrPlugin.coin, uplift
biclust, BiplotGUI, coloc, frontiles, ips, mixAK, paramGUI, prefmod, R2BayesX, RcmdrPlugin.SM, snpStatsWriter, spacodiR, tourrGui, VIM, ViSiElse, W2CWM2C
AssocTests, BayClone2, bayess, bgmm, fcd, FLR, forensic, GameTheory, genetics, MetaDE, NSM3, PoissonSeq, prob, QuACN, REREFACT, RMallow, SNPmaxsel, steadyICA, symmoments
gskat, iGasso, LGEWIS, LGRF, MiST, pedgene, rvTDT, skatMeta
cgam, ConSpline, DoubleCone, isotonic.pen, ShapeChange, ShapeSelectForest
BivarP, censorcopula, ClusterStability, CoClust, CoImp, gofCopula, HAC, HiDimMaxStable, lcopula, RGENERATEPREC, RMRAINGEN, SemiParSampleSel, vines
arf3DS4, BinNonNor, BinNor, care, clustrd, EDISON, FRB, FRCC, GeneNet, GLSME, Hotelling, HPbayes, idm, kcirt, leapp, longitudinal, MAVTgsa, mgpd, miRtest, MultiOrd, mvMORPH, mvSLOUCH, netgsa, OrdNor, penalizedSVM, PoisBinNonNor, PoisBinOrd, PoisBinOrdNonNor, PoisBinOrdNor, PoisNonNor, PoisNor, qtlhot, sda, sideChannelAttack, SMFI5, st, ttScreening
spatialTailDep, SphericalCubature, stppResid, symmoments, yuima
AF, ARTP2, BuyseTest, cffdrs, cvAUC, drgee, edgeRun, EurosarcBayes, GenomicTools, greport, ie2misc, iemisc, lookupTable, LSPFP, oec, orgR, panelaggregation, partools, popEpi, psidR, Rbitcoin, robCompositions, sdcMicro, simPop, simstudy, splitstackshape, surveyplanning, synthACS, tcpl, ttwa, validateRS, vardpoor, VIM, word.alignment
ilc, Interpol.T, kerdiest, modiscloud, RcmdrPlugin.survival, relsurv, RMAWGEN, ROCt
bibliospec, biglm, datamap, filehashSQLite, gmDatabase, ODB, ora, RecordLinkage, RJDBC, RMySQL, ROracle, rpostgis, RPostgreSQL, RSQLite, RSQLServer, sqlutils
DeducerExtras, DeducerPlugInExample, DeducerPlugInScaling, DeducerSpatial, DeducerSurvival, DeducerText
adehabitatHR, BiplotGUI, datautils, expp, highriskzone, ibeemd, stppResid
EcoHydRology, galts, IBHM, likeLTD, micEconCES, quickpsy, selectMeta
AquaEnv, BacArena, bvpSolve, DAMOCLES, DDD, deTestSet, diffEq, DivE, ecolMod, ecosim, embryogrowth, EpiModel, expoTree, FME, growthrates, hgm, hisse, insideRODE, neuRosim, nlmeODE, pauwels2014, phaseR, primer, PSM, ReacTran, scaRabee, simecol, SoilR, TDCor, TESS, TreePar, tseriesChaos, ZeBook
DiceEval, DiceOptim, DiceView, fanovaGraph, GPareto, KrigInv, MuFiCokriging
blockmodels, ElstonStewart, gmDatabase, gWidgets2, gWidgets2tcltk, gWidgetstcltk, LLSR, OpenMx, traitr
distrEllipse, distrEx, distrMod, distrRmetrics, distrSim, distrTeach, RandVar, RobAStBase, ROptEst, ROptEstOld, Statomica
distrEllipse, distrMod, distrTeach, RandVar, RobAStBase, ROptEst, ROptEstOld
DoE.wrapper, FrF2, pid, RcmdrPlugin.DoE, support.CEs
BANFF, dCovTS, EmiStatR, gdm, GenCAT, GiNA, gofCopula, MEGENA, MixRF, MonoInc, OmicKriging, perspectev, PTE, ramsvm, randomGLM, REPTILE, Rlof, RVPedigree, sdcTarget, SDDE, sms, turboEM, unbalanced, VTrack
anametrix, ANLP, censusr, chunked, corrr, dggridR, efreadr, etl, GenCAT, ggmcmc, manifestoR, mosaic, PogromcyDanych, poplite, quickpsy, rmdHelpers, SEERaBomb, spdplyr, surveybootstrap, tcR, texmexseq, treeplyr, turfR, vqtl, VWPre
BayesLCA, bayesMCClust, bios2mds, BSDA, classyfire, ClueR, clustrd, conformal, dad, eegAnalysis, flip, GameTheoryAllocation, gskat, InventorymodelPackage, KODAMA, MAclinical, mlDNA, obliqueRF, parallelSVM, PASWR, penalizedSVM, RMediation, tiger, VHDClassification
betaper, CrypticIBDcheck, FreeSortR, lvm4net, mada, mdsdt, MetabolAnalyze, metamisc, RAMpath, sigloc, SMPracticals
approximator, BACCO, calibrator, cmvnorm, lmmlasso, MM
Bergm, blkergm, CCMnet, ergm.count, ergm.ego, ergm.graphlets, ergm.rank, ergm.userterms, gwdegree, hergm, latentnet, lvm4net, statnetWeb, tergm, VBLPCM, xergm.common
condmixt, crackR, ddst, evt0, mgpd, Renext, ROptEstOld, truncdist, vqtl
ClustGeo, EnQuireR, Factoshiny, HDoutliers, RcmdrPlugin.FactoMineR, SensoMineR
AnalyzeFMRI, fastHICA, gogarch, icaOcularCorrection, isva, rgr
distrRmetrics, fArma, fAsianOptions, fAssets, fBonds, fCertificates, fCopulae, fExoticOptions, fExtremes, fGarch, fMultivar, fNonlinear, fOptions, fPortfolio, fRegression, fTrading, fUnitRoots, HBSTM, LSMonteCarlo, MetFns, rsgcc, Statomica
Actigraphy, CCA, CollocInfer, ctmcmove, cyphid, fdatest, fda.usc, FDRreg, Funclustering, funFEM, funHDDC, geofd, gpDDE, GPFDA, mar1s, pencopula, pendensity, penDvine, quantreg.nonpar, RFgroove, sde, sft, switchnpreg, vows
DBGSA, DiffCorr, GeneCycle, GeneNet, sda, st, TBEST
BayesSummaryStatLM, biglars, dualScale, ETLUtils, ffbase, PopGenome, propagate, RecordLinkage, sprint, tabplot
distrRmetrics, fExtremes, fNonlinear, gogarch, mleur
ASMap, aSPU, BaySIC, Canopy, CCA, cmsaf, crqa, eegAnalysis, EMD, Geneland, geoelectrics, geosptdb, gptk, gwrr, highriskzone, ibeemd, LatticeKrig, LSC, mgpd, paramGUI, phenology, phylotools, ProbForecastGOP, R2GUESS, sGPCA, spatialfil, SpatialVx, SpherWave, spThin, stilt, SynchWave, TIMP, TrackReconstruction, UncerIn2, verification, Voss, wux
enveomics.R, genasis, goft, mbbefd, qmap, SCI
BANFF, biganalytics, cffdrs, clustvarsel, cubfits, DNMF, doFuture, doMC, doMPI, doParallel, doRedis, doRNG, doSNOW, eiCompare, EmiStatR, GA, gam, gamsel, gdm, GenCAT, GiNA, glmnet, gmDatabase, gofCopula, gpmap, hdlm, hzar, localgauss, MAVTgsa, MEGENA, MetaPCA, MetaQC, missForest, MixRF, MonoInc, multicon, PAGWAS, parfossil, PAWL, penDvine, permGPU, perspectev, PortfolioAnalytics, QuantumClone, ramsvm, randomGLM, REPTILE, Rlof, RVPedigree, s4vd, sdcTarget, SDDE, selfingTree, sms, spatial.tools, SurvRank, survSNP, turboEM, unbalanced, vacem, VTrack
demography, dendrometeR, Dowd, expsmooth, fma, forecastHybrid, forecTheta, forega, fpp, ftsa, hts, ilc, MAPA, Mcomp, RcmdrPlugin.epack, Rssa, StMoMo, TSPred, ZRA
AnDE, diverse, epiDisplay, psidR, rsubgroup, Rz, shapefiles, UScensus2000cdp, UScensus2000tract, UScensus2010, vegdata
ARTP2, BayesGESM, BayesSAE, brnn, clusterSEs, DCchoice, detect, DirichletReg, games, gmnl, Hmisc, kaps, mhurdle, mlogit, MRSP, mvctm, npsf, OutlierDC, PanJen, plm, plmm, quint, Rchoice, rdd, sharx, simplexreg, smbinning, spBayes, ssym, StratSel, threg, thregI, zoib
DoE.wrapper, FrF2.catlg128, pid, RcmdrPlugin.DoE, simrel
GAabbreviate, mcga, recmap, Rothermel, SPIGA
CausalGAM, GAMens, LSC, MapGAM, mtsdi, ProDenICA, xpose4
acid, binequality, BSagri, gamlss.add, gamlss.cens, gamlss.mx, gamlss.nl, gamlss.spatial, gamlss.tr, gamlss.util
acid, binequality, gamlss, gamlss.add, gamlss.cens, gamlss.demo, gamlss.mx, gamlss.spatial, gamlss.tr, gamlss.util, SemiParSampleSel
BigTSP, bst, ecospat, gbm2sas, mma, twang
cccrm, chromoR, COMBIA, compareGroups, enaR, genetics, iCluster, ImportExport, joineR, LeLogicielR, MixedDataImpute, mixexp, mpMap, NanoStringNorm, nCal, nonparaeff, pSI, REREFACT, TRSbook, weights
aSPU, diffdepprop, DTComPair, GEEaSPU, gskat, JGEE, mmm, mmm2, saws
bayou, convevol, DAMOCLES, iteRates, laser, surface, TreeSim, windex
boostSeq, forensic, introgress, luca, MasterBayes
BinOrdNonNor, OrdNor, PoisBinOrd, PoisBinOrdNonNor, PoisBinOrdNor
alphashape3d, contoureR, disp2D, EDFIR, FD, gensphere, Maeswrap, modQR, munsellinterpol, mvmesh, nonparaeff, RadOnc, YplantQMC
aqfig, FeedbackTS, geofd, geoRglm, lmenssp, LS2Wstat, PrevMap, StatDA
ACSNMineR, alakazam, AmpliconDuo, aoristic, apsimr, bde, benchmark, biomod2, bootnet, braidReports, brms, caret, CINOEDV, cjoint, climwin, clustrd, coefplot, conformal, corkscrew, cowplot, crmPack, Crossover, CRTgeeDR, cystiSim, dae, Deducer, DengueRT, DepthProc, dfexplore, dggridR, diffeR, difNLR, dMod, DoTC, dotwhisker, dslice, DTRlearn, dtwclust, dtwSat, dynr, earlywarnings, ecr, eeptools, ESGtoolkit, factoextra, fbroc, fishmove, forestmodel, freqparcoord, gapfill, gapmap, gcerisk, GenCAT, genomeplot, geomnet, gettingtothebottom, ggalt, ggbeeswarm, ggcorrplot, ggfortify, ggghost, ggiraph, ggmap, ggmcmc, ggnetwork, ggpolypath, ggpubr, ggraptR, ggrepel, ggROC, ggseas, ggsn, ggswissmaps, ggtern, gmwm, GOplot, gpmap, granovaGG, gsDesign, GSE, gwdegree, Hmisc, HRM, hyperSpec, idm, ifaTools, InSilicoVA, interplot, ITEMAN, LambertW, learnstats, LexisPlotR, likeLTD, likert, lmms, localgauss, lsbclust, MCMC.OTU, MCMC.qpcr, mcprofile, MergeGUI, meteogRam, MissingDataGUI, MIXFIM, mixOmics, mlr, mlxR, mosaic, multilevelPSA, ncappc, NeatMap, nullabor, openVA, orgR, OriGen, OutbreakTools, PairedData, pAnalysis, ParallelTree, PASWR2, pauwels2014, PAWL, PedCNV, pequod, perry, perspectev, PhaseType, pid, pitchRx, PKgraph, PKreport, plotly, plotROC, pointRes, PopED, popgraph, PortfolioEffectHFT, PPtreeViz, precintcon, prevR, PRISMA, profileR, ProgGUIinR, PSAboot, quadrupen, QualInt, quickpsy, RAM, randomizeR, RcmdrPlugin.KMggplot2, RJafroc, rms, robCompositions, robustHD, rorutadis, rotations, RSA, RSDA, rstan, rtip, rwty, Rz, SciencesPo, season, SEERaBomb, selfea, sensiPhy, sglr, shazam, simmr, sinaplot, SmarterPoland, SMFI5, soc.ca, sparkTable, SparseFactorAnalysis, sparsereg, spoccutils, sprm, survminer, SWMPr, synthpop, TcGSA, tcR, tdr, texmexseq, tigger, timeline, trackeR, TriMatch, TripleR, tspmeta, useful, userfriendlyscience, varian, vdg, vrcp, VWPre, waffle, walkr, XGR, xkcd, zooaRch
hglasso, lassoscore, MInt, netgsa, rrlda, rsggm, spaceExt, sparseBC, Tsphere
AdapEnetClass, bapred, bigdata, BigTSP, BioMark, CAM, cosso, covTest, DivMelt, DTRlearn, elasso, EstHer, fcd, FindIt, glmnetcr, glmvsd, Grace, hdlm, HiCfeat, InvariantCausalPrediction, ipflasso, lassoscore, mht, MMMS, MMS, MNS, netgsa, oblique.tree, parcor, PAS, PRIMsrc, prototest, qut, refund.wave, regsel, relaxnet, roccv, RVtests, selectiveInference, SIMMS, SML, SOIL, SparseLearner, sparsenet, SubLasso, widenet
logmult, multgee, prefmod, StMoMo, vcdExtra
allanvar, ARTIVA, bayesMCClust, bayess, cellVolumeDist, corkscrew, DandEFA, datautils, DensParcorr, DiagTest3Grp, ghyp, highSCREEN, iCluster, MDplot, MetabolAnalyze, metabolomics, Meth27QC, mlma, mma, muma, PRISMA, RCA, reGenotyper, rehh, ReorderCluster, rnaseqWrapper, ROCR, rsgcc, SubLasso, swamp, YplantQMC
ACSNMineR, climwin, difNLR, dotwhisker, ESGtoolkit, GOplot, HH, ncappc, onlineCPD, PPtreeViz, primerTree, rorutadis, sparkTable, tcR
aws, evmix, metacor, palinsol, pgs, QRM, rGammaGamma, tggd
ASMap, bayesMCClust, Biocomb, ConsRank, crossdes, dice, GameTheory, genetics, GESTr, GSM, hier.part, HUM, iCluster, IDPSurvival, interferenceCI, iteRates, JASPAR, likeLTD, MAMA, MasterBayes, MDplot, MetabolAnalyze, modMax, muma, mvtmeta, ordBTL, orQA, PairViz, REQS, RI2by2, rnaseqWrapper, rpsychi, rvHPDT, sensory, SRRS, trioGxE, Ultimixt, WMCapacity
apt, bayesDem, dbConnect, fit4NM, gWidgetsRGtk2, gWidgetstcltk, MetSizeR, mrMLM, nCal, pmg, RenextGUI, reshapeGUI, rsgcc, RunuranGUI, sdcMicroGUI, tourrGui, traitr, WMCapacity
AtelieR, bayesDem, FAiR, fit4NM, iBUGS, MergeGUI, MetSizeR, MicroStrategyR, MissingDataGUI, mrMLM, PKgraph, playwith, pmg, reshapeGUI, RQDA, rsgcc, RunuranGUI, sdcMicroGUI, VIMGUI, WMCapacity
BOG, COMBIA, GABi, HAP.ROR, KoNLP, neuroim, orderbook, rpartitions
acid, anesrake, aspace, cg, colorscience, compareGroups, crackR, EBMAforecast, ENmisc, EstCRM, etable, FRESA.CAD, FunCluster, funModeling, greport, greyzoneSurv, gset, ImportExport, its, lawstat, LifeHist, MEET, nonparaeff, PredictABEL, PRIMsrc, prLogistic, pse, RcmdrPlugin.Export, RcmdrPlugin.mosaic, rms, RM.weights, Scale, tables, UsingR, visualFields, weights
birdnik, censusr, couchDB, GAR, hkex.api, httping, instaR, LightningR, markmyassignment, ores, osi, Rcolombos, request, Rfacebook, RFc, RGoogleAnalytics, RGoogleAnalyticsPremium, rHealthDataGov, Rlinkedin, rosetteApi, SmarterPoland, TMDb, tumblR, ungeneanno, whoapi, WikipediaR
agop, ARTIVA, bc3net, BDgraph, BPEC, brainGraph, c3net, camel, cccd, CePa, CINOEDV, clickstream, cooptrees, corclass, corkscrew, cvxbiclustr, cvxclustr, dcGOR, DiffCorr, dils, disparityfilter, dnet, dpa, ebdbNet, editrules, ESEA, fanovaGraph, fastclime, FisHiCal, flare, G1DBN, gdistance, GeneReg, genlasso, ggm, gRapfa, hglasso, huge, igraphtosonia, InteractiveIGraph, iRefR, JGL, linkcomm, LncPath, locits, MEGENA, micropan, mlDNA, MNS, modMax, mRMRe, NEpiC, netassoc, netgsa, NetSwan, optrees, OutrankingTools, PAGI, pathClass, picasso, popgraph, PROFANCY, ProNet, qtlnet, ragt2ridges, RCA, ReliabilityTheory, rEMM, rgexf, RNetLogo, RNewsflow, ror, RWBP, sand, SDDE, secrlinear, SEMID, sglasso, shp2graph, SOMbrero, spacejam, SubpathwayGMir, SubpathwayLNCE, synRNASeqNet, tcR, timeordered, tnet, wfg, XGR
Bchron, BMA, cxxfunplus, imprProbEst, mkin
clustvarsel, doFuture, doMC, doMPI, doParallel, doRedis, doSNOW, GA, hdlm, itertools, MetaQC, MonoInc, parboost, SDDE, sms, spatial.tools
ECharts2Shiny, GAR, instaR, jSonarR, oec, RFc, RGoogleAnalyticsPremium, RGoogleFit, rHealthDataGov, TMDb
CVST, DTRlearn, kappalab, netClass, pathClass, probsvm, svmadmm, SVMMaj
CHsharp, DiagTest3Grp, EMMIXskew, FCGR, gammSlice, GenKern, GoFKernel, ICE, IsoCI, ks, MEET, mpm, mpmi, qualV, stpp, TPmsm
ElstonStewart, FamEvent, Familias, GESE, LCAextend, MasterBayes, paramlink, pedantics, pedgene
BrailleR, EasyHTMLReport, OutbreakTools, PopGenReport, rmdHelpers, rrecsys, sdcMicro, SOMbrero, spThin, svSweave, tufterhandout
AdapEnetClass, aml, covTest, cumSeg, elasticnet, ExactPath, FeaLect, FindIt, GPC, gwrr, monomvn, multiPIM, OTRselect, PAGWAS, pass, pfa, qut, relaxo, RXshrink, scalreg, sealasso, sisVIVE, spikeslab
abcdeFBA, abd, adaptTest, agsemisc, ASMap, assist, backtest, barcode, bayespref, BayesSAE, bc3net, bgmm, biclust, bifactorial, bigdata, biotools, BSDA, camel, cardidates, caret, cem, coalescentMCMC, COMBIA, compeir, ConvergenceConcepts, Cubist, cvTools, cwhmisc, DAAG, dad, DATforDCEMRI, DCL, deseasonalize, designmatch, Devore7, DMwR, DoseFinding, dualScale, eHOF, ELT, EmiStatR, EMMIXskew, EngrExpt, equivalence, erboost, EstCRM, factorQR, fastclime, FAwR, FitAR, fit.models, flare, flexclust, flexmix, FTICRMS, gammSlice, gbm, gcbd, geoelectrics, Giza, growthrates, gsbDesign, hett, hgam, HH, Hmisc, hotspots, HSROC, huge, hyperSpec, ICEinfer, iClick, iCluster, IDPmisc, iGasso, insideRODE, irtProb, jagsUI, joineR, kmlShape, kwb.hantush, kzs, latticeExtra, lfstat, loa, Maeswrap, mapStats, MCPMod, McSpatial, MDR, memisc, mirt, mixexp, mixOmics, mleur, MM2S, MOJOV, MortalitySmooth, mosaic, mritc, msme, nFactors, nlmeODE, nonmem2R, odfWeave, OLScurve, optiscale, orderbook, OUwie, overlapping, PairedData, paleoMAS, PASWR, PASWR2, pbo, pems.utils, pencopula, pendensity, penDvine, phenmod, phmm, picasso, PKgraph, PKreport, playwith, pmg, portfolio, portfolioSim, primer, PROFANCY, ProTrackR, pscl, qtlhot, R2MLwiN, R330, randomLCA, rasterVis, RcmdrPlugin.plotByGroup, RcmdrPlugin.temis, rCUR, REPPlab, rmatio, Rmisc, rms, robfilter, robust, RSA, RxCEcolInf, rysgran, SALTSampler, scaRabee, SEL, semPLS, SetMethods, sExtinct, simFrame, simPop, sme, smint, SML, soilprofile, solaR, spuRs, statnetWeb, stripless, survSNP, svdvisual, sybil, synthpop, TDboost, tdr, titan, TROM, twang, unmarked, vegan, VHDClassification, violinmplot, VizOR, vwr, waterfall, Watersheds, wgaim, wskm, xpose4
COMBIA, DCL, ELT, HH, pencopula, rasterVis, solaR, statnetWeb, twang, vwr, wskm
autoSEM, blavaan, bmem, coefficientalpha, EffectLiteR, eqs2lavaan, fSRM, influence.SEM, lavaan.survey, MIIVsem, profileR, RAMpath, regsem, RMediation, RSA, rsem, semTools, simsem, stremo
BACprior, bestglm, BMA, DEMOVA, FitAR, Kpart, MAR1, pampe, R330, reams, regclass, speff2trial, TSA
acebayes, ATmet, DiceOptim, mtk, netgen, penalizedSVM
BCE, EMMAgeo, LIM, MLCIRTwithin, MultiLCIRT, spaceExt
afex, agRee, aods3, ArfimaMLM, arm, bapred, Bayesthresh, BBRecapture, blme, BradleyTerry2, cAIC4, carcass, CLME, difR, fishmethods, fullfact, gamm4, GLMMRR, GWAF, iccbeta, influence.ME, JAGUAR, JointModel, lmerTest, longpower, marked, MEMSS, merTools, Metatron, mixAK, MixRF, mlma, mlmRev, nonrandom, pbkrtest, pedigreemm, predictmeans, prLogistic, robustlmm, simr
AER, cjoint, dcv, erer, fpp, frontier, ivlewbel, ivpack, mfx, micEconAids, rdd, systemfit, vars
abc, BBRecapture, curvetest, DATforDCEMRI, ELT, EMD, mcll, McSpatial, nlts, SimpleTable, TSA
AcrossTic, cherry, clime, EDFIR, goalprog, ibd, imprProbEst, irr, kappalab, linprog, mcclust, modQR, mpcv, nonparaeff, pathClass, RcmdrPlugin.sampling, StatMatch, WhatIf
Benchmarking, boostSeq, DJL, GameTheory, GameTheoryAllocation, qVarSel, safeBinaryRegression, sdcTable, TFDEA
difR, infutil, irtoys, kequate, PerFit, QVM
MetFns, MRMR, orgR, RGoogleAnalytics, RGoogleAnalyticsPremium, seawaveQ, TimeProjection, tolBasis, weatherr
DMR, geometry, MM, sdcTarget, SNSequate, SODC, spBayes
efreadr, forestplot, gitlabr, gwdegree, imager, jug, multiplyr, packagetrackr, sp500SlidingWindow
etasFLP, FeedbackTS, geo, M3, swfscMisc, ternvis, vmsbase
BPEC, cope, ETAS, FeedbackTS, fields, fossil, geo, GeoLight, HBSTM, letsR, M3, mapdata, mapproj, muRL, NightDay, OIdata, openair, OriGen, paleobioDB, phytools, ramps, RNCEP, s2dverification, speciesgeocodeR, ternvis, vmsbase, warbleR, YplantQMC
cleangeo, cshapes, DeducerSpatial, Digiroo2, geospacom, GISTools, GWmodel, helsinki, itcSegment, KappaV, lakemorpho, mapStats, McSpatial, micromap, monographaR, Nippon, pycno, qrfactor, rCarto, shp2graph, STMedianPolish, StreamMetabolism, ternvis, UScensus2000cdp, UScensus2000tract, UScensus2010, vdmR, Watersheds
Bayesthresh, BioPhysConnectoR, dualScale, flexrsurv, HRM, hts, MRSP, pom, rrlda, semGOF, zoib
aSPU, DAMOCLES, FastHCS, FastPCS, FastRCS, GAD, localgauss, LS2Wstat, NSA, r2dRue, samr, ttScreening, visualFields
censReg, games, gmnl, hermite, ihs, IntLik, intReg, lmmot, mhurdle, mlogit, mlogitBMA, mvProbit, oglmx, pglm, PrevMap, Rchoice, sampleSelection, ssfa, truncreg
CAM, expectreg, FDboost, gamboostLSS, globalboosttest, InvariantCausalPrediction, parboost
BiSEp, clustvarsel, CNprep, CNVassoc, GESTr, IntNMF, LifeTables, MetabolAnalyze, msir, msos, npde, prabclus, qclust, robustDA, Simpsons, SNPMClust, SQN, tclust, Traitspace, treeHFM, upclass, WACS
adaptsmoFMRI, anominate, bacr, BayesMed, bayespref, CoinMinD, cudia, gset, HSROC, hzar, milonga, NHMM, optDesignSlopeInt, PhViD, R2GUESS, RxCEcolInf, SimpleTable, uskewFactors
bgeva, CAM, coenoflex, dlmap, dsm, DSsim, eHOF, fda.usc, gamlss.add, gamlss.spatial, gamm4, gammSlice, gvcm.cat, ibr, icaOcularCorrection, ismev, itsadug, labdsv, logistf, MAPLES, modTempEff, mombf, MPINet, multipleNCC, nontarget, ordPens, PanJen, R2BayesX, reams, robustgam, scam, season, SemiParBIVProbit, SemiParSampleSel, semsfa, STAR, trioGxE, TSA, TTS
accelmissing, CALIBERrfimpute, genpathmox, HardyWeinberg, hot.deck, logistf, miceadds, roughrf, stpm, SYNCSA, TestDataImputation, weights, weightTAPSPACK
AquaEnv, cellVolumeDist, HydroMe, micEconCES, mkin, onls, propagate, qpcR, Ritc, tumgr
lordif, mirtCAT, NominalLogisticBiplot, OrdinalLogisticBiplot, PerFit
brainR, grt, kml3d, ks, longitudinalData, mritc, ptinpoly, VecStatGraphs3D
FRESA.CAD, intReg, IQCC, lmmlasso, maxLik, polywog
bayesMCClust, bayess, DiceOptim, EXRQ, FAMT, MaXact, mdsdt, PACBO, PAGWAS, PLordprob, qtlhot, quantreg.nonpar, Rgbp, siar, StratSel, Sunder, timedelay, WACS
earlywarnings, irtProb, LIHNPSD, mixedsde, spfrontier
ATmet, BVS, CEoptim, eiPack, hysteresis, ltm, NEff, NHMM, RM2, score, spatial.gev.bma, Surrogate, trioGxE, WPC
bifactorial, BSagri, HH, ILS, MAVTgsa, medflex, mutossGUI, nparcomp, RcmdrPlugin.coin, RcmdrPlugin.doex
adaptsmoFMRI, AdMit, asd, aSPU, AssocTests, AssotesteR, B2Z, BACprior, BAEssd, Bayesianbetareg, BayesPiecewiseICAR, Bayesthresh, BAYSTAR, bdots, Bergm, bglm, bgmm, bifactorial, BinNonNor, BinNor, Bmix, bnormnlr, BNPTSclust, CAMAN, caper, CDM, condMVNorm, covmat, CPMCGLM, cslogistic, cudia, dawai, depend.truncation, distrEllipse, dmt, DoseFinding, DunnettTests, edrGraphicalTools, EMC, EMMIXskew, emulator, FactMixtAnalysis, FAmle, faoutlier, fExpressCertificates, fgof, ForImp, freqdom, freqparcoord, genetics, GenForImp, GenOrd, GGMridge, GGMselect, glmm, glmpathcr, GLSME, growthrate, gset, hbim, hdrcde, hglasso, highmean, HPbayes, hsmm, hyperSpec, ICS, ICSNP, IMIS, imputeYn, JPEN, kcirt, ks, lava.tobit, lawstat, LCAextend, lmec, lmenssp, LogConcDEAD, logcondiscr, LSMonteCarlo, mada, MAMS, mc2d, MCPMod, mdhglm, mediation, MetabolAnalyze, metamisc, MetSizeR, mgarchBEKK, mhsmm, miscFuncs, MitISEM, MIXFIM, mixsmsn, mmcm, MNS, Modalclust, mombf, MRsurv, msma, multcomp, MultiGHQuad, multinomRob, MultiOrd, multxpert, muma, mutoss, mvnTest, mvProbit, mvSLOUCH, netgen, nicheROVER, nlsem, nonmem2R, nparcomp, OptInterim, OrdNor, PairedData, parallelMCMCcombine, party, PAWL, PGEE, pGMGM, plgp, PoisBinNonNor, PoisBinOrd, PoisBinOrdNor, PoisNor, polycor, powerGWASinteraction, psbcGroup, qclust, qcr, QGglmm, QRM, R2GUESS, RAD, reglogit, RidgeFusion, rPowerSampleSize, rtip, RxCEcolInf, SamplerCompare, schwartz97, selectiongain, SeleMix, SemiParSampleSel, SEMModComp, simboot, snipEM, SNPassoc, SNPmaxsel, sp23design, spate, spatialnbda, spatialprobit, spatialTailDep, spfrontier, sscor, ssmrob, SSsimple, Stem, symmoments, tclust, texmex, tilting, tlmec, tmvtnorm, TTmoment, uskewFactors, WACS, wbsts, weightedScores, yuima
biglasso, ExactPath, glmvsd, mombf, pass, SOIL
Bergm, Blaunet, blkergm, CCMnet, enaR, ergm, ergm.count, ergm.ego, ergm.graphlets, ergm.rank, ergm.userterms, haplotypes, hergm, latentnet, lvm4net, mpa, ndtv, networkDynamic, networkDynamicData, networksis, OutbreakTools, sna, statnetWeb, tergm, tsna, VBLPCM, xergm.common
EpiModel, ndtv, networkDynamicData, tergm, tsna
acc, alphaOutlier, drgee, GNE, likelihoodAsy, ph2bye, sigloc, SPmlficmcm
abd, AdaptFit, AdaptFitOS, assist, bdots, BiDimRegression, BIOdry, cati, cccrm, CorrMixed, covBM, CpGassoc, DengueRT, dlmap, DPpackage, far, FCGR, FlexParamCurve, frailtypack, gamlss, goric, HydroMe, insideRODE, ipdmeta, IPMpack, JM, JMbayes, joineR, JointRegBC, JoSAE, likelihood, lmenssp, lmeSplines, lmfor, longpower, LoopAnalyst, LVMMCOR, mbest, meboot, MethComp, mgcv, MSwM, multilevel, mvctm, nlmeODE, orQA, pheno, picante, plmm, portfolio, prc, predictmeans, ProfileLikelihood, psychometric, qrLMM, ramps, REEMtree, RepeatedHighDim, sae, sitar, spatstat, SPREDA, TapeR
CCpop, corHMM, episplineDensity, hisse, MaxPro, OUwie, parma, stpm
abc, BarcodingR, CBPS, depmixS4, epiDisplay, gamlss.add, gamlss.mx, HIest, HydeNet, ImpactIV, introgress, LOGICOIL, MDM, partialOR, pocrm, roughrf, SIDES, sodavis, synthpop
CovSel, DepthProc, generalCorr, rddtools, semsfa, stam
alabama, B2Z, bayesDccGarch, bnormnlr, catIrt, CBPS, CompLognormal, compound.Cox, copCAR, dhglm, DOBAD, dsm, FENmlm, fgof, fracprolif, frailtyHL, GAS, ghyp, HPbayes, lbfgsb3, lmeNB, ltbayes, mdhglm, mederrRank, mgpd, mipfp, mvglmmRank, mvSLOUCH, optextras, PSM, QRM, SemiMarkov, sgt, SpeciesMix, ssym, stremo, ThresholdROC, turboEM
brainR, COMBIA, cudaBayesreg, dcemriS4, dpmixsim, fslr, mritc
ddst, gaussquad, GPC, LaplaceDeconv, LPTime, uniftest
AtelieR, frmqa, hpcwld, iteRates, MM, NSM3, rTableICC
evtree, NHEMOtree, psychotree, quint, smbinning, vcrpart
ccaPP, DetMCD, muma, rainbow, rrlda, sscor
DIFtree, lmmlasso, multiPIM, ROC632, subtype, uplift
astro, audiolyzR, cytoDiv, DIFtree, dupiR, EasyStrata, epade, GeneticTools, lba, magicaxis, MetFns, mutossGUI, optpart, plotmo, randomizeR, SeqFeatR, simplexreg, SPEDInstabR, surv2sampleComp
autopls, BioMark, ChemometricsWithR, dbstats, dmm, LGEWIS, lspls, MetStaT, monomvn, muma, obliqueRF, plsVarSel, RcmdrPlugin.NMBU, robCompositions, RVtests, svapls
abctools, acc, acs, anametrix, bcpa, bmk, boottol, BSGS, ClustGeo, CPMCGLM, cshapes, DataLoader, DoTC, EBMAforecast, EIAdata, EurosarcBayes, evolqg, Fgmutils, fishmove, gcbd, gpmap, HRM, imager, ivlewbel, JAGUAR, merTools, MScombine, NAPPA, oec, ONETr, plotSEMM, PMA, pxR, rcbalance, rcbsubset, rcqp, RDSTK, remix, reshapeGUI, Rmisc, RSAGA, RStorm, rtip, sclero, selfea, smatr, SSrat, StagedChoiceSplineMix, StratifiedBalancing, surveybootstrap, timeordered, unitedR, weightTAPSPACK, wordmatch
adhoc, embryogrowth, gaussquad, kzft, LaplaceDeconv, orthopolynom, rationalfun
colorscience, conicfit, crqa, episplineDensity, GORCure, ICGOR, likelihoodAsy, mousetrack, RAHRS, TapeR, TDD, VideoComparison
DistatisR, ExPosition, InPosition, MExPosition, TExPosition, TInPosition
bimixt, FRESA.CAD, RcmdrPlugin.ROC, roccv, ThresholdROC
argparse, AtelieR, benchmark, gsubfn, MetaQC, nls2, PKgraph, pmg, R2STATS, SparseFactorAnalysis, sqldf, traitr
cba, ConsRank, diverse, dtw, dtwclust, kst, recommenderlab, rEMM, rrecsys, smdc, StatMatch, stream, TSdist
accelmissing, anominate, BSGS, emIRT, lctools, oc, wnominate
BinNor, Compind, DeducerPlugInScaling, GAabbreviate, generalCorr, HDMD, multicon, MultiOrd, nFactors, nonparaeff, orddom, PoisBinOrdNor, random.polychor.pa, REREFACT, Rz, Scale, SODC, SSDforR, SubLasso
ASMap, dlmap, eqtl, mpMap, mQTL, pheno2geno, qtlbook, qtlhot, qtlnet, vqtl, wgaim, xoi
AdapEnetClass, BLCOP, BSquare, cosso, DAGGER, ForecastCombinations, FRAPO, gtop, imputeYn, iterLap, kappalab, kinship2, ldlasso, MonoPoly, pencopula, RefFreeEWAS, SEL, ShapeChange, SPIn, ternvis, vottrans, wSVM
abc, alphaOutlier, BSquare, cqrReg, EILA, emplik, EXRQ, ForecastCombinations, genpathmox, GeoXp, lss, McSpatial, mvctm, OutlierDC, pfa, pheno, plaqr, QRegVCM, qrjoint, quantregGrowth, quantreg.nonpar, Rearrangement, riv, RobPer, rqPen, turboEM, vdg
Agreement, FFD, HTMLUtils, permPATH, RcmdrPlugin.EACSPIR, STAR
DSpat, Geneland, GeoGenetix, LS2Wstat, ProbForecastGOP, UncerIn2
AUCRF, bartMachine, BigTSP, D2C, interpretR, MAVTgsa, missForest, MixRF, mlDNA, ModelMap, partitionMap, quantregForest, regclass, RFgroove, RFinfer, rfPermute, roughrf, spikeslab, sprint, trimTrees, varSelRF
celestial, McSpatial, RapidPolygonLookup, RWBP, saasCNV, StatMatch
BAT, biomod2, cffdrs, cmsaf, ctmcmove, diffeR, dismo, downscale, dtwSat, ENiRG, gdistance, gdm, geostatsp, geotopbricks, gfcanalysis, gimms, hsdar, itcSegment, kissmig, letsR, lulcc, mapmisc, maxlike, meteoForecast, MigClim, ModelMap, modiscloud, move, osc, paleobioDB, phyloclim, PopGenReport, PrevMap, rangeBuilder, rasterVis, rbgm, remote, rts, sampSurf, satellite, ShapeSelectForest, SiMRiv, SpatialPosition, spatial.tools, spdynmod, SPEDInstabR, TOC, usdm, virtualspecies, water, zoon
EnQuireR, RcmdrPlugin.BCA, RcmdrPlugin.coin, RcmdrPlugin.depthTools, RcmdrPlugin.doex, RcmdrPlugin.EBM, RcmdrPlugin.EcoVirtual, RcmdrPlugin.epack, RcmdrPlugin.Export, RcmdrPlugin.KMggplot2, RcmdrPlugin.mosaic, RcmdrPlugin.MPAStats, RcmdrPlugin.plotByGroup, RcmdrPlugin.pointG, RcmdrPlugin.ROC, RcmdrPlugin.seeg, RcmdrPlugin.SM, RcmdrPlugin.steepness, RcmdrPlugin.UCA
ASMap, bayespref, beadarrayFilter, ChaosGame, corkscrew, DeducerText, ENmisc, FieldSim, GISTools, GOplot, introgress, latticeExtra, LeLogicielR, linkcomm, LSC, MDplot, MDSGUI, micromap, MonoPhy, mvtsplot, PanJen, phenmod, profileR, PST, qdap, qPCR.CT, quantregForest, RArcInfo, rCarto, RcmdrPlugin.pointG, RcmdrPlugin.SM, RFLPtools, TrackReconstruction, TraMineRextras, TRSbook, wordcloud
AdaptiveSparsity, Amelia, ASPBay, BaBooN, bcpa, beanz, bifactorial, bigReg, Biocomb, blockmodels, BuyseTest, CARBayes, CARBayesST, clogitL1, ClusterStability, ClustMMDD, collUtils, ConConPiWiFun, copCAR, CoxPlus, cqrReg, dbmss, DeLorean, dendextendRcpp, DepthProc, dfpk, dils, drgee, dslice, ecp, EditImputeCont, eggCounts, emIRT, EPGLM, erah, fastGHQuad, FBFsearch, FCNN4R, FDGcopulas, flan, FRESA.CAD, FSInteract, fugeR, gaston, GeneticTools, GENLIB, GenomicTools, glmgraph, Gmisc, gMWT, growcurves, growfunctions, GSE, GUTS, hkevp, HUM, hypervolume, IBHM, IsingSampler, JAGUAR, jmotif, kergp, lm.br, matchingR, mice, miscF, MixedDataImpute, Mposterior, multicool, MVB, mvcluster, NetSim, ngspatial, nonlinearTseries, NPBayesImpute, NPflow, oem, OneArmPhaseTwoStudy, OpenMx, orQA, PACVB, PedCNV, PerMallows, PoweR, ProbitSpatial, ProNet, propagate, quadrupen, Rborist, Rclusterpp, RcppClassicExamples, RcppOctave, RcppXts, recmap, regsem, remote, rexpokit, Rfast, Rmalschains, Rmixmod, RmixmodCombi, robustgam, rotations, RoughSets, RSNNS, Rsomoclu, rstanarm, rtkore, rtkpp, satellite, sdcTable, seismicRoll, sequences, simFrame, snipEM, SOD, spacodiR, steadyICA, StMoSim, survSNP, tagcloud, tbart, treeclim, trustOptim, unmarked, VideoComparison, waffect, wingui, wsrf
FBFsearch, FisHiCal, MVB, PedCNV, prospectr, robustgam
anametrix, aqr, brewdata, CHCN, couchDB, crn, factualR, fds, helsinki, hkex.api, jSonarR, LightningR, LSPFP, notifyR, OIdata, ONETr, osmar, psidR, pullword, pumilioR, R4CouchDB, rbiouml, rbitcoinchartsapi, RDSTK, restimizeapi, RGoogleFit, rHpcc, Rjpstatdb, Rlabkey, rLTP, RNaviCell, rneos, ROMIplot, ropensecretsapi, rPlant, RSelenium, RStars, Rtts, RYoudaoTranslate, scrapeR, shopifyr, sos4R, sotkanet, source.gist, SPARQL, streamR, support.CEs, SynergizeR, tibbrConnector, tumblR, VarfromPDB, VideoComparison, zendeskR
biomod2, emme2, gcbd, generalhoslem, Giza, lctools, PAWL, pedigree, PhaseType, profileR, rapportools, RcmdrPlugin.EACSPIR, reportRx, RSAP, SMFI5, unmarked, wux
afex, CINOEDV, diverse, ESGtoolkit, gapmap, HRM, ifaTools, JAGUAR, mmppr, onlineCPD, pxR, reshapeGUI, ScottKnottESD, STMedianPolish, tcR, tmpm, TriMatch, validateRS, wordmatch
cffdrs, DeducerSpatial, dggridR, diffeR, divagis, hsdar, landsat, M3, mgraph, micromap, ModelMap, modiscloud, move, prevR, r2dRue, rangeBuilder, ShapePattern, ShapeSelectForest, spatial.tools, SPODT, TOC, UScancer, water
anchors, DiceOptim, FAiR, KrigInv, multinomRob, RobPer
cleangeo, DivE, expp, geospacom, GISTools, Grid2Polygons, highriskzone, ibeemd, itcSegment, KappaV, pycno, ShapePattern, Watersheds
abcdeFBA, alphashape3d, animalTrack, bios2mds, BiplotGUI, bpca, brainR, ChaosGame, ConsRank, corregp, depth, DiceView, directPA, DirichletReg, dti, edrGraphicalTools, eegkit, etasFLP, fdaPDE, FieldSim, foodweb, frontiles, fso, gdimap, gensphere, geoelectrics, geomorph, GeoXp, GGEBiplotGUI, grt, hgam, hiPOD, hyper.fit, hypervolume, kml3d, ks, longitudinalData, LSAfun, Maeswrap, MDSGUI, molaR, mtk, mvmesh, nat, nat.nblast, nat.templatebrains, NeatMap, nonlinearTseries, optBiomarker, pavo, plot3Drgl, qpcR, qtlc, QuantifQuantile, R330, RadOnc, RcmdrPlugin.TeachingDemos, Rknots, ROCS, rotations, Rpdb, sphereplot, tkrgl, VDA, VecStatGraphs3D, YplantQMC
abcdeFBA, cosso, DAGGER, designmatch, FRAPO, LPmerge, rorutadis, sdcTable, sparkTable
brainGraph, CITAN, fit4NM, gWidgets2RGtk2, gWidgetsRGtk2, HomoPolymer, MenuCollection, PKgraph, RGtk2Extras, tourrGui
auRoc, BANOVA, BaySIC, bsam, HydeNet, lira, metamisc, pcnetmeta, prevalence, PurBayes, R2jags, simmr, zoib
AntAngioCOOL, arulesNBMiner, bartMachine, bartMachineJARs, CollapsABEL, collUtils, Crossover, edeR, ENMeval, extraTrees, gemtc.jar, glmulti, gMCP, helloJavaWorld, InSilicoVA, iplots, JGR, KoNLP, mallet, matchingMarkets, MSIseq, mwa, rCBA, rcdklibs, rChoiceDialogs, rDNA, REPPlab, rGroovy, RH2, RImpala, RJDBC, rJPSGCS, RJSDMX, rJython, rkafka, rkafkajars, rmcfs, RMOA, RMongo, RNCBIEUtilsLibs, RNetLogo, ror, rrepast, rsubgroup, SBRect, scagnostics, sjdbc, spcosa, streamMOA, venneuler, x.ent, xlsx, xlsxjars
couchDB, df2json, edeR, notifyR, RDSTK, Rfacebook, rJython, Rlabkey, rosetteApi, rPlant, RYoudaoTranslate, source.gist, Storm, streamR, tibbrConnector, zendeskR
audiolyzR, factualR, LightningR, pxR, R4CouchDB, rbiouml, rbitcoinchartsapi, restimizeapi, RNaviCell, ropensecretsapi, rPython, RSelenium, RStars, RXKCD, SynergizeR, tumblR, VideoComparison, WDI, weatherr
AMOEBA, CNprep, MicSim, pbdMPI, pbdSLAP, snowFT, sprint
ACTCD, CellularAutomaton, curvetest, DATforDCEMRI, GAD, NSA, R.oo
Bessel, CryptRndTest, frmqa, LDOD, LIHNPSD, pvrank
contrast, CPE, FeaLect, LCAextend, lordif, missDeaths, nonparaeff, Tsphere
BMA, ccaPP, compositions, cvTools, ddalpha, DetMCD, dmm, FastHCS, ForwardSearch, GWmodel, ltsbase, MBmca, muma, perry, qpcR, robCompositions, robfilter, RobPer, robust, RobustAFT, robustgam, robustHD, robustX, rrcov, rrcovHD, rrcovNA, sscor, ssmrob
Comp2ROC, cvAUC, genMOSS, iFad, MEET, obliqueRF, pathClass, PredictABEL, RcmdrPlugin.ROC, rocc, sperrorest, subtype
ibmdbR, ImportExport, mixsep, RODBCext, RODM, stacomirtools, toaster
CellularAutomaton, curvetest, DATforDCEMRI, NPCD, NSA, plmDE, R.filesets, R.utils
AdvBinomApps, diffdepprop, diffEq, ecolMod, eel, errint, FME, hsdar, kmc, LLSR, mkin, pbatR, ProbYX, prop.comb.RR, ReacTran, weightedScores
biotools, erpR, gamlss.demo, GUIDE, LinRegInteractive, MDSGUI, optBiomarker, RVideoPoker, soilphysics
ada, adabag, AntAngioCOOL, chemometrics, DidacticBoost, DStree, fda.usc, gamlss.add, GPLTR, maboost, maptree, multiPIM, NHEMOtree, PSAgraphics, quint, REEMtree, regclass, rpart.plot, rpartScore, rpart.utils, spatstat, sperrorest, stima, treeClust
biwt, BMA, DepthProc, FAiR, FRB, groc, muma, riv, RobAStBase, robust, robustfa, rrcovHD, rrcovNA
alphaOutlier, depmixS4, DiscreteInverseWeibull, DiscreteWeibull, DNAtools, Familias, GAS, GEVStableGarch, GsymPoint, IDPSurvival, JOP, LDOD, likelihoodAsy, mipfp, qualityTools, robustDA, SemiMarkov
bibliospec, CITAN, filehashSQLite, filematrix, gcbd, MUCflights, RecordLinkage, refGenome, RQDA, snplist, sqldf, SSN
bmlm, brms, CopulaDTA, eggCounts, hBayesDM, MIXFIM, varian
discrimARTs, DistributionUtils, FKF, futile.paradigm, GeneralizedHyperbolic, permGPU, rkafka, schwartz97, SkewHyperbolic, SoilR, VarianceGamma
acnr, aroma.affymetrix, aroma.cn, aroma.core, calmate, HyPhy, MSIseq, NSA, PubBias, tmle.npvi
AER, CADFtest, cjoint, COUNT, gmm, inference, ivpack, list, mediation, mfx, midasr, RcmdrMisc, rdd, strucchange, vars
ACSNMineR, bios2mds, DeducerSpatial, dslice, onlineCPD, precintcon, RSDA, TriMatch
bpca, CHsharp, GPCSIV, ISDA.R, lle, MDSGUI, poLCA, windex
bmem, dpa, faoutlier, qtlnet, semdiag, semGOF
CNOGpro, DCODE, LSPFP, MEET, mlgt, rPlant
CryptRndTest, Demerelate, distr, ICEbox, modiscloud, plfm, polycor, simrel, TTS
diagram, ecolMod, EMMAgeo, marelac, pathdiagram, ReacTran, sparsenet, spnet, symbols
adehabitat, aspace, BayesX, DSsim, fossil, RPyGeo, RSAGA
bde, CLME, ECharts2Shiny, EmiStatR, EMMAgeo, enviPick, EurosarcBayes, Factoshiny, gmDatabase, gwdegree, ifaTools, meta4diag, MetaAnalyser, mirtCAT, paramGUI, plotSEMM, quipu, RJafroc, sglr, shinystan, Sofi, sparkTable, statnetWeb, SubVis
gem, hsdar, ProTrackR, Rivivc, TBEST, TDD
biogram, cherry, designmatch, maptpx, qlcMatrix, RcmdrPlugin.temis, Rcplex, Rglpk, sdcTable
fpca, irtoys, magicaxis, mem, plmm, vioplot
cSFM, enveomics.R, GenForImp, LIHNPSD, Rgbp, tclust
bipartite, CCMnet, CEoptim, cssTools, egonet, enaR, hergm, ndtv, NetCluster, Rambo, relevent, SSrat, statnet
BioPhysConnectoR, CePa, doSNOW, snowfall, snowFT
AMOEBA, autoSEM, bmem, BuyseTest, classyfire, DLMtool, fugeR, GlobalDeviance, graphscan, hsphase, kcirt, lle, megaptera, mglmn, MicSim, mlDNA, NUCOMBog, peperr, PIGE, R2GUESS, reddPrec, rsgcc, widals
adehabitat, adehabitatHR, adehabitatHS, adehabitatLT, adehabitatMA, automap, BarcodingR, biomod2, CAMAN, cartography, cmsaf, colorscience, constrainedKriging, cshapes, DeducerSpatial, diseasemapping, dismo, divagis, DivE, ecospat, ENiRG, excursions, expp, FedData, FeedbackTS, fossil, frontiles, georob, geospacom, geosphere, geospt, geosptdb, geostatsp, GISTools, graticule, Grid2Polygons, GWmodel, ibeemd, INLABMA, intamap, itcSegment, KappaV, landsat, MapGAM, mapmisc, maptools, MBA, meta4diag, meteoForecast, micromap, modiscloud, move, MUCflights, Nippon, orsifronts, plotGoogleMaps, polyCub, postGIStools, prevR, pycno, r2dRue, RandomFields, rangeBuilder, RapidPolygonLookup, raster, rbgm, rcanvec, recmap, RFc, rgdal, rgrass7, rtop, rts, rworldmap, rworldxtra, sampSurf, sdm, SDraw, secrlinear, seg, ShapePattern, sos4R, SpatialEpi, spdep, spdplyr, spdynmod, spgrass6, spgwr, splancs, spnet, SPODT, spsurvey, spTDyn, ssfa, SSN, stam, STMedianPolish, stplanr, surveillance, tbart, trip, UncerIn2, UScensus2000cdp, UScensus2000tract, UScensus2010, usdm, USGSstates2k, vec2dtransf, vetools, water, Watersheds, wux
copCAR, fields, gamlss.spatial, GPFDA, latticeDensity, LatticeKrig, smnet, spThin
evmix, hts, maxent, McSpatial, modelfree, pheno, QRegVCM, quantreg, rexpokit, RItools, rms, RTextTools
adaptsmoFMRI, aoristic, BAT, dbmss, Digiroo2, dixon, DSpat, ecespa, GriegSmith, latticeDensity, ppmlasso, RcmdrPlugin.seeg, sclero, seeg, selectspm, SGCS, siar, siplab, sparr, spatialsegregation, SpatialVx, stpp
AMOEBA, DCluster, Digiroo2, expp, GeoXp, ibeemd, latticeDensity, LS2Wstat, spatialprobit, spfrontier, splm, ssfa
aspace, dixon, DSsim, ecespa, latticeDensity, soilprofile, stpp, stppResid, Watersheds
Fgmutils, GPCSIV, RSDA, smbinning, vmsbase
asht, exact2x2, exactci, nivm, rPowerSampleSize
cond, CopulaREMADA, csampling, dglm, diffIRT, GHQp, h2o, joineR, JointModel, lmeNB, marg, mcll, mixcat, MVR, nlreg, PCS, penalizedSVM, survsim
blkergm, ergm, ergm.count, ergm.graphlets, ergm.rank, ergm.userterms, latentnet, sna, tergm
acs, AnDE, dMod, enaR, eqs2lavaan, exsic, Fgmutils, FRESA.CAD, fslr, geotopbricks, KoNLP, lettercase, LindenmayeR, Maeswrap, mpoly, mtk, neuroim, orgR, patchSynctex, PepPrep, PhysActBedRest, pMineR, pxR, quipu, recoder, RGENERATEPREC, RJafroc, rsgcc, RSMET, sdcTable, sqlutils, ssh.utils, surveybootstrap, tumblR, vardpoor, VarfromPDB, ViSiElse
CalibrateSSB, cjoint, lavaan.survey, mapStats, MOJOV, odfWeave.survey, pedgene, relaimpo, samplingbook, sptm, ssfit, StatMatch, svyPVpack, twang, VIMGUI, weightTAPSPACK
AER, AF, ahaz, AHR, AIM, anoint, APtools, attribrisk, BayesMixSurv, bayesSurv, BivarP, BMA, BSGW, bshazard, BuyseTest, carcass, cchs, cmprsk, CNVassoc, coin, compound.Cox, concreg, cond, CoxBoost, coxinterval, coxme, coxphw, CoxRidge, coxrobust, CPE, crossmatch, crrp, crrSC, csampling, ctqr, currentSurvival, distcomp, DPpackage, drgee, dynpred, dynsurv, eha, ELYP, epiDisplay, epiR, etm, FamEvent, fitdistrplus, flexPM, flexrsurv, flexsurv, frailtyHL, frailtypack, frailtySurv, gamlss.cens, gamlss.nl, gbm, gcerisk, geneSignatureFinder, glmpath, globalboosttest, glrt, GORCure, greyzoneSurv, GSAgm, gte, gtx, HapEstXXR, haplo.ccs, Hmisc, ICBayes, icenReg, ICGOR, IDPSurvival, imputeYn, InferenceSMR, InformativeCensoring, interval, invGauss, ipflasso, isoph, JM, JMbayes, joineR, JointModel, JointRegBC, kaps, kin.cohort, km.ci, kmconfband, kmi, lava.tobit, lcmm, linERR, LncMod, LogicReg, luca, marg, MetaDE, mexhaz, mfp, mhurdle, missDeaths, mmc, MMMS, MPLikelihoodWB, MRH, mRMRe, MRsurv, mstate, multcomp, multipleNCC, NADA, NestedCohort, nlreg, NPHMC, NSM3, OIsurv, optmatch, OrdFacReg, OTRselect, OutlierDC, p3state.msm, packHV, paf, pamr, parfm, partDSA, pbatR, pch, penalized, PenCoxFrail, peperr, permGPU, PHeval, phmm, PIGE, plac, plRasch, PRIMsrc, prognosticROC, PwrGSD, QoLR, qrcm, QualInt, RcmdrPlugin.coin, RcmdrPlugin.survival, relsurv, remix, risksetROC, rms, RobustAFT, ROC632, ROCt, RPCLR, rprev, rsig, rstpm2, season, seawaveQ, selectiveInference, SemiCompRisks, seqDesign, seqMeta, SIDES, SIMMS, simMSM, skatMeta, smcure, smoothHR, smoothSurv, SNPassoc, sp23design, speff2trial, SPREDA, sprinter, sptm, ssym, STAND, STAR, stepp, stpm, superpc, surv2sampleComp, survAccuracyMeasures, survAUC, survC1, survexp.fr, survey, Survgini, survIDINRI, survivalMPL, survJamda, survMisc, SurvRank, SurvRegCensCov, survRM2, survSNP, tdROC, TH.data, threg, thregI, time2event, timereg, tnet, TraMineRextras, TransModel, uniah, uniCox, WPC
BacArena, GlobalFit, RSeed, sybilccFBA, sybilcycleFreeFlux, sybilDynFBA, sybilEFBA, sybilSBML
accrual, AnthropMMD, BiplotGUI, forensim, MDSGUI, mixsep, SeqFeatR, SRRS, stosim, TELP
earth, plotmo, RcmdrPlugin.epack, RcmdrPlugin.TeachingDemos, SPEDInstabR
humanFormat, kergp, markmyassignment, MInt, SortableHTMLTables, StableEstim
fArma, fAsianOptions, fAssets, fBasics, fBonds, fCopulae, fExoticOptions, fExtremes, fGarch, fImport, fMultivar, fNonlinear, fOptions, forecast, fPortfolio, fractalrock, fRegression, fTrading, fUnitRoots, TimeProjection, timeSeries
fArma, fAsianOptions, fAssets, fBasics, fBonds, fCopulae, fExoticOptions, fExtremes, fGarch, fImport, fMultivar, fNonlinear, fOptions, fPortfolio, FRAPO, fRegression, fTrading, fUnitRoots, QRM
adehabitat, biotools, BiplotGUI, ConvergenceConcepts, FFD, fisheyeR, fit4NM, forensim, GGEBiplotGUI, GUIDE, MDSGUI, OligoSpecificitySystem, onemap, RHRV, RSA, RVideoPoker, soilphysics, SyNet, VIMGUI
ANLP, DeducerText, manifestoR, maxent, RcmdrPlugin.temis, RNewsflow, smdc, tm.plugin.dc
eiCompare, fExpressCertificates, imputeLCMD, propagate, spatialprobit, spfrontier, uskewFactors, WACS
FamEvent, GsymPoint, imp4p, NPflow, spate, validateRS, zCompositions
aster, cepp, dMod, glmm, iWeigReg, mcemGLM, MInt, relevent, UWHAM
TScompare, TSfame, TSmisc, TSMySQL, TSodbc, TSPostgreSQL, TSsdmx, TSSQLite
acp, AnalyzeTS, CADFtest, earlywarnings, fma, forecTheta, fpp, Mcomp, mgarchBEKK, nonlinearTseries, RcmdrPlugin.epack, RcmdrPlugin.UCA, TSA
AnalyzeTS, egcm, quantmod, smoother, SSDforR
dualScale, ENmisc, RcmdrPlugin.mosaic, RcmdrPlugin.SM, simPop, vcdExtra
analogue, BAT, betaper, BiodiversityR, bipartite, blender, cocorresp, CommEcol, CommunityCorrelogram, dave, Demerelate, FD, flowDiv, FreeSortR, GUniFrac, iDynoR, isopam, metacom, MiSPU, mpmcorrelogram, ordiBreadth, palaeoSig, paleoMAS, picante, RAM, rareNMtests, recluster, simba, SYNCSA, vegan3d, vegclust
Bayesthresh, BSquare, EffectStars, errint, EurosarcBayes, GEVcdn, iteRates, lawstat, multgee, ordBTL, pheno2geno, prob, regclass
adwave, brainwaver, RHRV, W2CWM2C, wavemulcor, wmlf
binhf, BootWPTOS, costat, CVThresh, haarfisz, locits, LS2W, MeanShift, refund.wave, treethresh, waveband
dvfBm, eegAnalysis, RFgroove, TSclust, wbsts
condformat, cosmosR, DataLoader, ELT, ImportExport, RJafroc
acs, aidar, anametrix, apsimr, biorxivr, brewdata, compareODM, easyPubMed, EcoHydRology, EcoTroph, EIAdata, ESEA, gnumeric, grImport, hkex.api, iDynoR, ips, mseapca, mtk, MUCflights, odfWeave, ONETr, osmar, pMineR, pmml, pumilioR, rFDSN, RFinanceYJ, rgexf, rgrass7, rHpcc, Rjpstatdb, Rlinkedin, rneos, RSDA, RSelenium, RXMCDA, scrapeR, SequenceAnalysis, sos4R, SPARQL, spgrass6, StatDataML, SubpathwayGMir, support.CEs, symbolicDA, ungeneanno, VarfromPDB, weatherr, WikipediaR, XML2R
A3, acnr, AmpliconDuo, bayesMCClust, compareGroups, DATforDCEMRI, etable, FactoClass, fifer, generalCorr, gsDesign, IndependenceTests, klausuR, LeLogicielR, likert, LinRegInteractive, MAMA, multilevelPSA, pamctdp, papeR, permPATH, PIGE, quipu, RcmdrPlugin.Export, RcmdrPlugin.NMBU, reporttools, rplotengine, rtable, sdcMicro, SeleMix, seqDesign, surveillance, survSNP, TableMonster, TRSbook, twang
aqr, bdrift, bsts, cotrend, egcm, EIAdata, eventstudies, FinancialInstrument, GAS, highfrequency, hydroTSM, IBrokers, lfstat, PerformanceAnalytics, PortfolioAnalytics, Quandl, quantmod, RcmdrPlugin.epack, RcppXts, RFinanceYJ, rts, YieldCurve
acc, AER, AutoSEARCH, bdrift, betategarch, bsts, caschrono, changepoint, dendrometeR, dtwSat, dyn, dynlm, egcm, EIAdata, EloRating, Evapotranspiration, eventstudies, fast, FinancialInstrument, FinTS, FLIM, forecast, fts, fxregime, gamlss.util, GAS, geotopbricks, gets, ggseas, glogis, highfrequency, hydroGOF, hydroTSM, IBrokers, lgarch, lmtest, mar1s, meteoForecast, Modalclust, phenology, PortfolioAnalytics, QoLR, quantmod, RcmdrPlugin.temis, rdatamarket, reGenotyper, RelValAnalysis, RJSDMX, RObsDat, rts, sde, solaR, STMedianPolish, StreamMetabolism, strucchange, SWMPr, tgram, trackeR, VideoComparison, xts, yuima
alleHap, arm, BayesComm, bayesPop, biomod2, bootnet, brainGraph, brms, CFC, cocoreg, DLMtool, DMwR, factoextra, funData, gdimap, geostatsp, glmmBUGS, Gmisc, HH, kamila, latentnet, magclass, merTools, MFPCA, mlVAR, ncdf4.helpers, ncdf.tools, NetRep, neuroim, OpenRepGrid, oro.nifti, pcalg, pssm, quantspec, R2jags, Rcmdr, RcmdrMisc, RCMIP5, rfPermute, RItools, RNCEP, rosm, rprev, RSDA, s2dverification, secr, secrdesign, SparseTSCGM, spatial.tools, spatstat, spectral.methods, synbreed, treeclim
BTSPAS, ChainLadder, eggCounts, mbbefd, ReliabilityTheory
adegraphics, adespatial, ads, brainGraph, clusterSim, DrBats, entropart, hierfstat, IntClust, Laterality, memgene, msap, PBD, pez, phylobase, PopGenReport, poppr, RAM, rmetasim, RVAideMemoire, seqinr, STEPCAM, symbolicDA, virtualspecies
adephylo, AFLPsim, apex, hierfstat, outbreaker, rmetasim, StAMPP, treescape
agricolae, conjoint, DoE.wrapper, SPOT, VdgRsm
anim.plots, gfcanalysis, mptools, phytools, spdynmod, srd, stream, TED
AutoModel, DTR, ExomeDepth, LogisticDx, mmeta, reportRx, StroupGLMM, xmeta
adegenet, adephylo, bcRep, betapart, BMhyd, BoSSA, brranching, CommT, entropart, EpiModel, evobiR, evolqg, expands, gamclass, gquad, GrammR, graphscan, gromovlab, HMPTrees, homals, indelmiss, kdetrees, lefse, markophylo, megaptera, Momocs, monogeneaGM, msap, nLTT, nodiv, outbreaker, OutbreakTools, P2C2M, PBD, PCPS, phyext2, phylobase, phylocurve, phyloland, PhyloMeasures, phylosignal, phyndr, PhySortR, PIGShift, poppr, primerTree, RAM, Reol, rotl, RPANDA, SeqFeatR, sharpshootR, shazam, sidier, SigTree, STEPCAM, strataG, stylo, taxize, TKF, TotalCopheneticIndex, vcfR
blmeco, carcass, CosmoPhotoz, eeptools, hbsae, mi, migui, mlVAR, rr, squid
Biocomb, clickstream, inTrees, preprocomb, sbrl, TELP
assertive, assertive.code, assertive.data, assertive.data.uk, assertive.data.us, assertive.datetimes, assertive.files, assertive.matrices, assertive.models, assertive.numbers, assertive.properties, assertive.reflection, assertive.sets, assertive.strings, assertive.types, multipanelfigure, pathological
assertive, assertive.code, assertive.types, multipanelfigure, pathological
assertive, assertive.data, assertive.data.uk, assertive.data.us, pathological
assertive, assertive.code, assertive.datetimes, assertive.strings, multipanelfigure, pathological
aemo, AntWeb, bigrquery, bold, boxr, broman, citr, coala, codyn, condformat, dataonderivatives, dplyr, easypackages, ecoengine, FastKNN, fiery, fuzzr, ggthemes, ggvis, gistr, highcharter, jaatha, listWithDefaults, luzlogr, managelocalrepo, mcglm, milr, neuroim, ngram, nima, prcbench, precrec, prettyunits, rchess, RCMIP5, RDML, rdrop2, remoter, reutils, rfisheries, rotl, rpcdsearch, rprime, RSQLServer, saeRobust, simcausal, solr, spareserver, textreuse, tibble, tidyjson, tmlenet, wordbankr
hydroTSM, intamap, intamapInteractive, psgp, spBayesSurv
aws.signature, AzureML, d3heatmap, dataone, emuR, FastRWeb, gitlabr, gmailr, jug, leaflet, MALDIquantForeign, manifestoR, MTurkR, placement, plotly, R.devices, readMzXmlData, rmarkdown, RSiteCatalyst, sendmailR, swirlify, threejs, trelliscope, tutorial, UNF, wordcloud2
aftgee, antitrust, BinOrdNonNor, CatDyn, DSBayes, LifeHist, mlt, optimx, orsk, pim, reReg
BatchExperiments, fail, llama, metagen, parallelMap, ParamHelpers, RBPcurve, rsig, SwarmSVM, tspmeta, yakmoR
emdbook, Luminescence, metaplus, rstpm2, ss3sim
pcalg, plm, plsVarSel, sortinghat, sparsediscrim, splm
CollapsABEL, cooccurNet, geneSLOPE, mbest, multiplyr, Rdsm, s2dverification
biogram, Cyclops, DNAprofiles, ETLUtils, ffbase, MSBVAR, Stack
caTools, geozoo, gepaf, HierO, IgorR, nhlscrapr, oro.nifti, osrm, Pasha, rLiDAR, SocialMediaLab
adegenet, bandit, biotools, bootLR, brainGraph, BSagri, btergm, catenary, Causata, circular, complmrob, CorrBin, Countr, crs, dagitty, DAMisc, deming, DescTools, drsmooth, eggCounts, energy, extremogram, frair, GeneralOaxaca, gsg, hdpca, ic.infer, InformativeCensoring, Kendall, lga, lmeresampler, MBESS, medflex, metaplus, mixtools, moveHMM, MplusAutomation, multiwayvcov, netdiffuseR, np, OptimaRegion, pairwiseCI, pdR, perspectev, pgirmess, phylosignal, plsRbeta, plsRglm, polyapost, poppr, pse, pubmed.mineR, qat, Qtools, R2OpenBUGS, randomLCA, referenceIntervals, refund, rich, RVAideMemoire, SCBmeanfd, sem, sensitivity, shotGroups, simmr, sisal, soilphysics, sparkTable, SpatialVx, spdep, SPreFuGED, sprint, TraMineR, treeclim, yhat
BatchJobs, diezeit, leafletR, mapview, opencpu, rdnb, Rook, roxygen2, tabplotd3
AutoModel, cdom, DeLorean, dotwhisker, eyetrackingR, forestmodel, ggpmisc, highcharter, mason, merTools, pixiedust, sjPlot, StroupGLMM, tadaatoolbox, tidytext, vdmR
MergeGUI, MissingDataGUI, plfMA, R2STATS, SeqGrapheR, vmsbase, x12GUI
afex, anacor, apaTables, apt, ART, ARTool, AutoModel, bayesLife, BCA, caret, Countr, drc, drsmooth, dynlm, easyanova, EffectLiteR, ez, FactoMineR, FSA, funcy, fxregime, gamclass, gcmr, ldamatch, matlib, medflex, miceadds, micEconCES, mixlm, mvdalab, NHPoisson, panelAR, pdR, plm, plsRglm, rasclass, RcmdrPlugin.BCA, referenceIntervals, robCompositions, rockchalk, rpubchem, RVAideMemoire, ryouready, sdcMicro, StroupGLMM, tadaatoolbox, translateSPSS2R, userfriendlyscience, VIM, VSE, zetadiv
aLFQ, blkbox, caretEnsemble, crtests, darch, datafsm, DecisionCurve, dtwSat, ESKNN, fitcoach, kinn, LOGIT, NoiseFiltersR, parboost, preprocomb, preprosim, preproviz, quantable, RStoolbox, specmine, SSL, TLBC
AdaptGauss, bdynsys, climdex.pcic, CorrectOverloadedPeaks, diveMove, dtwclust, dynRB, envlpaster, erah, funcy, gplots, growthcurver, IntegratedMRF, kinn, NHMSAR, PharmacoGx, photobiology, rmarkdown, RSelenium, RTextTools, SchemaOnRead, sdPrior, sValues
AEDForecasting, FlowScreen, GeoLight, MPAgenomics, msltrend
BatchExperiments, BatchJobs, BBmisc, cointReg, ecr, fail, hdm, HydeNet, icd, icd9, lasvmR, lazysql, llama, mcparallelDo, mlr, parallelMap, ParamHelpers, pixiedust, RBPcurve, RcppShark, rjstat, rscimark, SwarmSVM, tspmeta, yakmoR
activpalProcessing, bdvis, data.table, dga, Dominance, drLumi, ncdf.tools, qdap, qdapTools, redcapAPI, rugarch, SASxport, SpaDES, sqldf, TideCurves, TideTables, uHMM, vmsbase, wakefield
activity, kineticF, monogeneaGM, monographaR, sharpshootR
Biocomb, chemometrics, classifly, classInt, clValid, DMwR, dprep, e1071, fpc, gencve, HistDAWass, ipred, lineup, mlearning, msSurv, popsom, RPEnsemble, Rsomoclu, stylo, supclust, uHMM, UNCLES, wux
aoristic, cartography, FAOSTAT, GoodmanKruskal, mapStats, plotKML, questionr, rangeMapper, tmap
backShift, cds, DESnowball, JADE, lsbclust, movMF, pcalg, skmeans, stream
ADPclust, agricolae, Anthropometry, aqp, biplotbootGUI, clue, comato, convevol, CORElearn, CrossClustering, DESnowball, disclapmix, DisimForMixed, DrugClust, EMA, factoextra, FactoMineR, fpc, funcy, funrar, geophys, GrammR, gromovlab, Hmisc, hybridHclust, inpdfr, IntClust, ldstatsHD, MEGENA, MixGHD, monogeneaGM, multibiplotGUI, openair, optCluster, PANDA, PReMiuM, PSF, rainbow, randomUniformForest, recluster, relations, rEMM, robCompositions, RPANDA, rrcov, rrcovNA, sdcMicro, semiArtificial, SemiPar, SensoMineR, seriation, sharpshootR, skmeans, spatialEco, spikeSlabGAM, StatDA, stream, symbolicDA, TcGSA, traj, TSdist, uHMM, vegan, vegan3d, vmsbase, wordspace
agRee, arm, auRoc, BaBooN, BaM, BANFF, BayesComm, bayescount, bayesGARCH, bayesLife, bayesmix, BayesSingleSub, bayesTFR, BayesX, Bchron, bdpopt, BDWreg, BEST, bfa, BPEC, brms, BRugs, bsam, btergm, btf, BTSPAS, CARBayes, CARBayesST, conting, dcmle, DeLorean, DrBats, EasyMARK, eggCounts, eiwild, emdbook, EpiBayes, ergm, ergm.ego, evolqg, evolvability, geiger, geoBayes, GERGM, glmBfp, hierarchicalDS, HLSM, hSDM, idem, IFP, immer, jagsUI, kobe, latentnet, list, lsmeans, marked, MfUSampler, mixAK, MixSIAR, morse, MplusAutomation, MRH, MSBVAR, multimark, networkTomography, nLTT, pcnetmeta, plotMCMC, polySegratioMM, pomp, ptycho, PVAClone, qrjoint, R2admb, R2jags, R2OpenBUGS, r4ss, RcmdrPlugin.RMTCJags, redist, RMark, rr, runjags, rwty, SAVE, scape, SeqFeatR, simmr, sirt, sisus, slfm, sns, sparsereg, spBayesSurv, spdep, spikeSlabGAM, spTimer, sspse, stocc, TBSSurvival, tergm, tglm, Zelig, zic
AzureML, datadr, foreach, globals, lintr, markmyassignment, MonetDBLite, MonetDB.R, multcomp, pkgmaker, PopED, pryr, RStoolbox, svTools
afex, glycanr, matchMulti, nlnet, NPC, NSM3, pairwiseCI, party, rankFD, shotGroups, sjmisc, sjstats
anacor, arulesViz, BayesX, BiplotGUI, cds, circlize, copula, DepthProc, DiffusionRgqd, DiffusionRimp, DiffusionRjgqd, effects, extracat, forecast, ftsa, gdimap, geiger, ggthemes, gpairs, HH, IsotopeR, JBTools, mapStats, mcmcplots, metafolio, msr, munsell, NetOrigin, NMF, OpenRepGrid, plotKML, qgraph, rainbow, randomcoloR, RcmdrMisc, semPlot, seriation, SGP, shades, simPop, simsalapar, smacof, srd, subspace, TIMP, treemap, vcd, Wats
addreg, cem, cocoreg, CorrBin, DESnowball, DoE.base, isocir, klaR, label.switching, lllcrc, nettools, pcIRT, qualCI, Quor, ReliabilityTheory, rpcdsearch, sirt, TraMineRextras, treescape
gaston, gyriq, MDMR, MVLM, nonnest2, RVPedigree, seqMeta, shotGroups, tcgsaseq, varComp
apt, cds, copulaedas, PortRisk, strataG, tailDepFun, VineCopula
BinOrdNonNor, BMhyd, bootnet, cape, cate, corHMM, D2C, esaBcv, FADA, jackstraw, ldstatsHD, list, lymphclon, MCMCglmm, mixOmics, mlVAR, netassoc, NORTARA, OUwie, parma, pcalg, perARMA, qgraph, r4ss, relaimpo, RPANDA, semPlot, sparsediscrim, spduration, subselect, tileHMM, wux
CorReg, dynRB, fdcov, GoodmanKruskal, ModelMap, SafeQuant, uHMM
covr, desc, gmailr, lintr, rcmdcheck, testthat
ALTopt, calibrator, dbmss, downscale, ei, eiCompare, fMultivar, GB2, hyperdirichlet, inctools, MCMCglmm, np, planar, tailDepFun, tseriesEntropy, vines
abbyyR, addinslist, AzureML, brranching, captr, clarifai, crunch, curlconverter, dataRetrieval, ecb, elastic, FedData, federalregister, geoknife, GetHFData, GetTDData, githubinstall, googleway, GSODR, httr, magick, MTurkR, MTurkRGUI, nomadlist, OAIHarvester, osmplotr, random, rdian, rdomains, readr, request, rgho, rio, Rmonkey, rpdo, RPublica, rversions, sbtools, telegram, udapi, V8, W3CMarkupValidator, wrswoR.benchmark
AFM, alakazam, aLFQ, APSIM, bedr, benford.analysis, biomartr, blscrapeR, brainGraph, caretEnsemble, Causata, ChannelAttributionApp, chromer, clickstream, cooccurNet, DataCombine, datadr, DataExplorer, dataview, dtplyr, ecoengine, edeaR, eeptools, eiCompare, emil, emuR, extracat, FactoMineR, FAOSTAT, fbRads, FedData, Fgmutils, freqweights, gems, genderizeR, getlandsat, githubinstall, GSODR, gunsales, hisse, Hmisc, inbreedR, Information, IPtoCountry, ITGM, Kmisc, lar, ldamatch, livechatR, lllcrc, LogisticDx, Luminescence, mapview, metaMix, mlr, mregions, msmtools, mtconnectR, mvQuad, noncompliance, OptiQuantR, optiRum, originr, PAC, partialAR, pcrsim, PGRdup, polmineR, PopGenReport, PSF, pxweb, qdapTools, quanteda, R6Frame, RAM, rAmCharts, randomNames, rangeMapper, RAPIDR, rBayesianOptimization, RbioRXN, rdrop2, RecordLinkage, repmis, rerddap, retrosheet, rfisheries, rgbif, rio, ritis, rlist, RndTexExams, RNewsflow, rnpn, RxnSim, SafeQuant, SciencesPo, sdcTable, sentimentr, SetRank, SGP, shazam, simcausal, simPH, SocialMediaLab, solarius, SpaDES, SpATS, spocc, squid, statar, StatMeasures, stdReg, strvalidator, survMisc, SWMPr, taxize, tcR, text2vec, TideCurves, TideTables, tmlenet, toxboot, traits, translateSPSS2R, treemap, trelliscope, TSTr, xgboost, yCrypticRNAs
archivist, BatchExperiments, BatchJobs, bigrquery, chunked, CITAN, DBItest, dplyr, emuR, etl, filehashSQLite, genomicper, imputeMulti, macleish, marmap, MetaIntegrator, MonetDBLite, MonetDB.R, poplite, postGIStools, redcapAPI, refGenome, RObsDat, RODBCDBI, RPresto, RQDA, SEERaBomb, sejmRP, smnet, snplist, sqldf, sqliter, tcpl, timeseriesdb, TScompare, TSdbi, TSfame, TSmisc, TSMySQL, TSodbc, TSPostgreSQL, TSsdmx, TSsql, TSSQLite, twitteR, UPMASK, vmsbase
cccd, MFHD, phonR, rLiDAR, SDraw, SEHmodel, spatstat, spdep, spsurvey
d3heatmap, factoextra, heatmaply, semiArtificial, seriation
BBEST, CEGO, covmat, FuzzyStatProb, MSCMT
asbio, AssetPricing, bdynsys, bioinactivation, capm, CollocInfer, DAISIE, diversitree, dynatopmodel, EpiDynamics, flexsurv, geiger, gpDDE, HomoPolymer, httk, hypergeo, mkin, nLTT, PBD, pomp, RLumModel, rodeo, RPANDA, spdynmod, stagePop, TIMP
addinslist, bisectr, BrailleR, creditr, demi, easypackages, FedData, githubinstall, IPtoCountry, opencpu, pacman, prodigenr, wru
ahp, data.tree, gSEM, HydeNet, muir, SpaDES, umx
aqp, archivist, archivist.github, aws.signature, BatchJobs, BetaBit, boxr, caretEnsemble, CorrectOverloadedPeaks, Crossover, datadr, datapack, devtools, distcomp, downloader, dplR, dpmr, ecd, ezsim, fbRads, FeatureHashing, FSelector, fulltext, future, geiger, geoparser, ggmap, ggplot2, glmbb, harvestr, htmltools, httpcache, knitcitations, knitr, kzfs, lazyrmd, lintr, MALDIquantForeign, memoise, MonetDBLite, MonetDB.R, MTurkR, nat, nat.templatebrains, NMF, OpasnetUtils, optmatch, pander, pkgmaker, PKNCA, placement, plotly, pomp, prettymapr, proton, qmethod, R2MLwiN, Rbitcoin, rbokeh, R.cache, RCMIP5, RcppOctave, readMzXmlData, repmis, repo, rerddap, Rexperigen, R.filesets, RMixpanel, rngtools, ROAuth, rosm, roxygen2, rrepast, rsconnect, RSiteCatalyst, scatterD3, scidb, sharpshootR, shiny, shinyjs, simpleRCache, sisal, SpaDES, stashR, storr, swirl, testthat, text2vec, textreuse, trelliscope, UNF, vegalite
biomod2, ecospat, GSIF, plotKML, PopGenReport, red, sdm, SDMPlay, SSDM, virtualspecies, zoon
distrDoc, logcondens.mode, meteR, miCoPTCM, RobLox, RobLoxBioC, ROptRegTS
MIPHENO, PKNCA, Rphylopars, SensMixed, synbreed, wCorr
abcrf, admixturegraph, ApacheLogProcessor, BayesBinMix, bcRep, bdots, BDWreg, bingat, bnspatial, breakpoint, BSGW, bst, BTR, cape, CFC, cffdrs, Compositional, condSURV, corr2D, covmat, CovSelHigh, Directional, DNMF, EasyMARK, ecospat, EFDR, ENMeval, enpls, EnsembleBase, EpiModel, fdasrvf, fuzzyforest, GENLIB, gimme, gimms, grpss, GSODR, GWLelast, GWRM, hbm, HMP, HMPTrees, hybridModels, hyperSMURF, iLaplace, Information, kergp, LANDD, LPR, Mediana, metaheur, metricTester, minimaxdesign, mistral, MNS, Morpho, mpath, mplot, MXM, myTAI, NMF, npregfast, opentraj, paleoTS, parallelML, parallelSVM, parboost, ParetoPosStable, PARSE, penDvine, performanceEstimation, phylocurve, preprocomb, preprosim, prozor, QuantumClone, R2MLwiN, randomUniformForest, rBayesianOptimization, regRSM, reval, RKEEL, RobustEM, robustrao, rprev, RRreg, RStoolbox, semsfa, SGP, shazam, SHLR, simPop, Smisc, sparsevar, spatial.tools, StAMPP, SurvRank, tigger, timeSeq, VineCopula, VSURF, warbleR, WGCNA
abcrf, bdots, condSURV, CovSelHigh, fuzzyforest, Mediana, RSNPset, SGP
biomartr, dataonderivatives, PharmacoGx, RKEELjars, stationaRy
drfit, ezec, IncucyteDRC, phylocurve, synergyfinder, VDAP
addinslist, ddpcr, eAnalytics, explor, ggraptR, heemod, IncucyteDRC, machina, merTools, MetaAnalyser, polmineR, RtutoR, shinystan, SpaDES, wppExplorer
dtwSat, mtconnectR, nettools, phylocurve, TSclust, TSdist, warbleR
bindata, Biocomb, blkbox, cati, chemometrics, classInt, clusterfly, clusterSim, cocoreg, Deducer, dpcR, dprep, DrugClust, EnsembleBase, fungible, gencve, gld, hda, hybridEnsemble, hydroTSM, IntClust, lfl, LOGIT, LOST, MetaLandSim, mistral, MixGHD, mlearning, msr, MXM, NoiseFiltersR, nproc, optBiomarker, PASWR2, ppiPre, preprocomb, preprosim, quantable, rasclass, RcmdrMisc, RecordLinkage, REndo, rminer, robCompositions, RObsDat, RobustEM, RTextTools, sdcMicro, simPop, SixSigma, sprint, SSDM, SSL, StatDA, stylo, SwarmSVM, symbolicDA, tableone, translateSPSS2R, TTAinterfaceTrendAnalysis, VIM, xseq
bujar, CorReg, epoc, LINselect, smart, sparseLDA
Bchron, convoSPAT, corregp, ei, eiCompare, FactoMineR, flexCWM, IsotopeR, lessR, mcmcse, metaSEM, mixOmics, MNM, MotilityLab, NPflow, pca3d, qgraph, RobustEM, scatterD3, SciViews, soc.ca, specmine
antitrust, cape, climwin, extremeStat, intamap, ldstatsHD, mev, mvPot, RecordLinkage, rtdists, SimCorMultRes
BinaryEPPM, carcass, CEGO, complexplus, corHMM, CountsEPPM, ctmcd, ctmm, DAMOCLES, evolqg, lymphclon, madness, marked, markovchain, MCL, msm, MultiMeta, OUwie, popdemo, powerplus, rags2ridges, ragt2ridges, rugarch, SCGLR, switchnpreg, TKF, VariableScreening
denoiseR, EMA, freqweights, GDAtools, HistDAWass, IntClust, IRTpp, missMDA, pcaBootPlot, RSDA, RVAideMemoire, SHLR, uHMM
freqweights, heatmap3, hypervolume, MetProc, NPflow, SpatialVx
metaplus, mixAK, MultiGHQuad, randomLCA, rstpm2
ffbase, icd9, landscapeR, phangorn, RSNPset
BLCOP, iClick, lefse, StableEstim, userfriendlyscience
BioGeoBEARS, cati, CluMix, ecospace, pez, RAM, STEPCAM
anacor, Ecfun, flars, ftsa, funcy, hisemi, iWISA, PerFit, refund, trackeR
cape, CosW, ERP, LANDD, lmem.gwaser, nlnet, qgraph, rags2ridges, ragt2ridges, SecKW, SimSeq, SinIW, TanB
bootSVD, Cyclops, IsoGene, rmgarch, SpaDES, Stack
accrual, ENiRG, fbati, IsotopeR, MetaLandSim
ADPclust, astrochron, autoimage, BayesLCA, bayesPop, bipartite, biwavelet, bkmr, BPEC, CARrampsOcl, chillR, Compositional, convoSPAT, cope, corr2D, earlywarnings, eemR, EGRET, etasFLP, fdasrvf, funcy, funData, gapfill, GeoLight, GEOmap, geospt, goeveg, hglasso, hht, letsR, lgcp, LICORS, LMERConvenienceFunctions, ltsk, mclcar, ModelMap, OptimaRegion, popsom, prevR, qat, qlcVisualize, ramps, RNCEP, rNOMADS, RsimMosaic, rworldmap, SEHmodel, smerc, sparseBC, SpatialExtremes, SpatMCA, SpATS, spatsurv, spBayesSurv, SpectralMap, StMoMo, stocc, subspaceMOA, SurvCorr, TED, TideCurves, topologyGSA, treescape, vmsbase
Anthropometry, bapred, cccd, customizedTraining, dprep, evclass, evclust, gstat, hextri, HighDimOut, hybridEnsemble, LICORS, mateable, TDA, unbalanced, xkcdcolors
abcrf, admixturegraph, ApacheLogProcessor, bastah, BayesBinMix, bayou, bcRep, bdots, BDWreg, bingat, biwavelet, bnspatial, boostr, boxoffice, brainGraph, breakpoint, BSGW, bst, BTR, calibrar, cape, caret, Causata, CFC, Compositional, condSURV, cooccurNet, corr2D, covmat, CovSelHigh, D2C, dCovTS, Directional, dtwclust, EasyMARK, ecospat, EFDR, ei, ENMeval, enpls, EnsembleBase, EpiModel, exifr, ezsim, fdasrvf, funData, fuzzyforest, gapfill, gdalUtils, GENLIB, gimme, gimms, grpss, GSODR, GWLelast, GWRM, harvestr, hbm, hdnom, HighDimOut, HMP, HMPTrees, hybridModels, hyperSMURF, icenReg, iLaplace, inctools, Information, intercure, JBTools, LANDD, ldamatch, lfl, LPR, mbest, Mediana, metaheur, metricTester, MFPCA, minimaxdesign, mistral, modellingTools, Morpho, mpath, mplot, mvcwt, MXM, myTAI, NetRep, NMF, npregfast, OmicKriging, opentraj, paleoTS, parallelML, parallelSVM, ParetoPosStable, PARSE, pec, performanceEstimation, phenex, phylocurve, polmineR, polywog, preprocomb, preprosim, prettymapr, primerTree, prospectr, proteomics, prozor, R2MLwiN, randomUniformForest, rangeMapper, rBayesianOptimization, regRSM, resemble, reval, RKEEL, RobustEM, robustrao, rosm, rprev, RRreg, RSNPset, RStoolbox, rusda, semsfa, SGP, shazam, SHLR, SimDesign, simPop, siRSM, spacom, spectral.methods, sperich, ss3sim, StAMPP, taxize, TED, text2vec, tigger, timeSeq, toaster, tsDyn, TSMining, TSP, vardpoor, VineCopula, VSURF, warbleR, WGCNA, YaleToolkit, ykmeans
AEDForecasting, bfast, cricketr, gpDDE, iClick, imputeTS, lfl, midasr, msltrend, PredictTestbench, PSF, tsDyn, tsoutliers
acmeR, Amelia, AmostraBrasil, AzureML, DDIwR, Deducer, DescTools, EffectLiteR, expss, fSRM, Hmisc, intsvy, lessR, maptools, miceadds, pmg, prevR, R2MLwiN, RcmdrPlugin.BCA, read.dbc, retistruct, rio, rsatscan, RStata, SchemaOnRead, sdcMicroGUI, Sofi, spsurvey, synthpop, translateSPSS2R, userfriendlyscience, VIMGUI, vmsbase
curlconverter, ggThemeAssist, knitr, Rd2roxygen, RFormatter, Rz
AER, bdynsys, betareg, bife, BinaryEPPM, cdfquantreg, Countr, CountsEPPM, crch, ExtremeBounds, fdaMixed, frontier, gcmr, glmx, greport, growcurves, HBglm, hdm, inferference, ivfixed, ivmodel, ivpanel, jmcm, LARF, lfe, mnlogit, moult, npmv, oaxaca, partykit, plsRbeta, polywog, PResiduals, psychomix, psychotree, rddtools, sampleSelection, SCGLR, thsls, tosls, varian
dendextend, MEGENA, nullabor, robCompositions, RPANDA, semiArtificial, stream, tspmeta
DeLorean, discSurv, gitlabr, hpoPlot, manifestoR, networkreporting, ontologyPlot, saeSim, sqliter, translate
darch, deeplearning, fbRads, futile.matrix, ggraptR, ISOpureR, tawny, tawny.types
aroma.affymetrix, aroma.core, fiery, PSCBS, R.filesets
biomod2, bujar, EnsembleBase, fitcoach, inTrees, mvtboost, SDMPlay, SSDM
BioGeoBEARS, comato, DAMisc, Dominance, drLumi, Ecfun, ENiRG, fheatmap, gmodels, gplots, likeLTD, lmms, LOST, MIPHENO, NetComp, polySegratio, powerbydesign, qat, qdap, QTLRel, rAvis, RbioRXN, rioja, RKEEL, rtematres, simSummary, sisus, sp500SlidingWindow, TSmisc, vardpoor, wux
aftgee, CorrBin, Cprob, ipw, MethylCapSig, SHLR, Zelig
BMhyd, entropart, evobiR, geomorph, lefse, metricTester, phylocurve, pmc, RADami, Rphylopars, treeplyr
geophys, RFOC, rNOMADS, Rquake, RTOMO, s2dverification
betapart, blackbox, cati, curvHDR, DepthProc, gdimap, hypervolume, imPois, Infusion, Momocs, pavo, pdfCluster, restlos, retistruct, rLiDAR, spaMM, STEPCAM, tmle.npvi
convoSPAT, gcmr, reportRx, spTest, TED, UncerIn2
birdring, ClimClass, crimelinkage, diveMove, fuzzyjoin, gfcanalysis, ggmap, GWLelast, lakemorpho, letsR, marmap, rbgm, red, RStoolbox, stplanr, tmap
DescribeDisplay, ggmcmc, imageData, LANDD, MissingDataGUI, PopGenReport, robCompositions, rwty, specmine, svdvis, toaster, userfriendlyscience, vdmR
hierarchicalSets, mosaic, preproviz, rwty, specmine
causaleffect, geneNetBP, MXM, osmplotr, pcalg, piecewiseSEM, qgraph, simPATHy, stablespec
choroplethr, moveHMM, OutbreakTools, RAM, rnrfa, SensusR, sidier, spoccutils, SWMPr, toaster, trackeR, tweet2r
corrr, factoextra, ggnetwork, ggpubr, qicharts, soc.ca
CosmoPhotoz, eechidna, futureheatwaves, PSAboot, RcmdrPlugin.KMggplot2, RtutoR, toaster
graphicalVAR, NHMSAR, pgraph, qgraph, scout, SelvarMix, shock, SparseTSCGM
anoint, bastah, blkbox, c060, Causata, cocoreg, ComICS, CorReg, CovSelHigh, customizedTraining, EnsembleBase, EnsemblePenReg, FADA, gencve, graphicalVAR, GWLelast, hdi, hdm, hdnom, hit, hybridEnsemble, IsingFit, kernDeepStackNet, knockoff, LPR, MESS, metafuse, mgm, MPAgenomics, mpath, mplot, msr, nproc, pact, parboost, pgraph, polywog, RCPmod, rdomains, RPtests, RSDA, rsig, RTextTools, SIS, sparsereg, sparsevar, stm, SurvRank, TANDEM, XMRF
CommEcol, cooccur, CryptRndTest, dplR, homomorpheR, iterpc, kantorovich, ldamatch, mvPot, partitions, pcalg, robustrao
bayesPop, eAnalytics, gtrendsR, MetaLandSim, mplot, RLumShiny, wppExplorer
Compind, mirt, OpenRepGrid, qmethod, TAM, traj, userfriendlyscience
asymmetry, BAMMtools, bcRep, bingat, bioplots, blackbox, cancerTiming, CluMix, condformat, corregp, DNMF, fheatmap, FLLat, FSA, GMD, HMP, IntClust, ionr, JBTools, lmms, matie, MenuCollection, MetaIntegrator, MetProc, momr, monogeneaGM, msarc, MultiPhen, NCA, NPflow, optCluster, PARSE, plotMCMC, qat, quantable, r4ss, RAM, RcmdrPlugin.BiclustGUI, r.jive, RPPanalyzer, SafeQuant, seriation, sesem, shapeR, smart, SSDM, SurvRank, synergyfinder, TcGSA, TIMP, TLdating, TopKLists, TROM, xhmmScripts
bnspatial, D2C, HydeNet, simPATHy, topologyGSA
NMF, playwith, seqHMM, SGP, sidier, simsalapar, SpaDES, synergyfinder, treemap
AFM, bamdit, BioPET, brms, bsam, caretEnsemble, ChaosGame, cocoreg, CommT, CosmoPhotoz, covmat, crmPack, DataExplorer, dynsim, ecr, episensr, fSRM, funModeling, gdimap, ggfortify, ggtern, granovaGG, hdnom, Hmisc, IGM.MEA, IntClust, likert, lmms, lsbclust, metaplotr, miscset, morse, mosaic, nima, npregfast, patPRO, PGRdup, Phxnlme, pointRes, prcbench, precrec, preproviz, qdap, QuantumClone, RAM, rangeMapper, RDS, refund.shiny, remote, reproducer, rfPermute, rrepast, RSPS, rstan, ShinyItemAnalysis, shinystan, simPH, snht, soc.ca, sparsereg, spikeSlabGAM, statebins, strvalidator, subspaceMOA, survminer, survMisc, svdvis, SWMPr, TELP, trackeR, TriMatch, UpSetR, userfriendlyscience, varian, vdg, viridis, waffle, yorkr
artfima, brr, copula, dti, ecd, gdimap, geospt, geosptdb, mbbefd, MBESS, rtdists
AFM, automap, EFDR, GSIF, hydroTSM, intamap, intamapInteractive, ltsk, meteo, oXim, plotKML, prevR, psgp, rtop
datamart, ITGM, MplusAutomation, smbinning, SpecHelpers, vmsbase
cowplot, GGally, ggalt, ggExtra, ggplot2, ggtern, gridExtra, hierarchicalSets, Hmisc, multipanelfigure, ncappc, pheatmap, strvalidator, tcR, trackeR, waffle
apmsWAPP, AutoModel, BayesFactor, blkbox, bootnet, BradleyTerry2, CoClust, CoImp, conting, cooptrees, datautils, drc, ecospat, eiwild, gdata, GGMselect, gplots, gwdegree, hierfstat, HKprocess, IGM.MEA, imputeMulti, IntClust, kamila, LINselect, LogicForest, MarkowitzR, metaMix, minimaxdesign, mixedMem, MuViCP, NSM3, paleobioDB, Pasha, pipe.design, PolyPatEx, polySegratioMM, qgraph, r4ss, randomUniformForest, RankAggreg, RCPmod, reservoir, RevEcoR, rmetasim, SGP, shinystan, sirt, sisus, smart, sourceR, ss3sim, STEPCAM, supcluster, svs, TcGSA, TROM, vqtl
extremevalues, gimme, GrammR, maGUI, metagear, pcrsim, playwith, plfMA, QVM, R2STATS, relMix, RQDA, RSCABS, SeqGrapheR, strvalidator, TR8, vmsbase
GrammR, maGUI, metagear, PKgraph, plfMA, R2STATS, RSCABS, SeqGrapheR, strvalidator, vmsbase
CITAN, dataone, datapack, medicalrisk, rankdist
ImportExport, mitml, rio, SchemaOnRead, sjmisc, tadaatoolbox, webuse
datadr, extracat, hextri, openair, pitchRx, plotly, rasterVis, rbokeh, trelliscope
aqp, BaBooN, bdynsys, brainGraph, CANSIM2R, caschrono, choroplethr, CluMix, Compind, datacheck, DeducerSpatial, drLumi, fdapace, FedData, FSA, Gmisc, Greg, heuristica, HH, HistogramTools, hydroPSO, imageData, intsvy, kehra, lazyWeave, lmerTest, mapStats, MatchLinReg, matchMulti, mediation, microplot, momr, MXM, nbpMatching, ndl, NetOrigin, nhanesA, nlrr, NSM3, PerFit, pixiedust, progenyClust, qgraph, rags2ridges, RcmdrMisc, redcapAPI, remix, rmngb, RPPanalyzer, SASxport, scape, sdcMicroGUI, SDD, SensMixed, sharpshootR, smacof, SocialMediaLab, soilDB, spsurvey, strataG, SvyNom, tigerhitteR, TopKLists, TraMineR, translateSPSS2R, VIMGUI, WGCNA, wppExplorer, wux, x12GUI, xkcd, xpose4
bookdown, colourpicker, DT, dygraphs, flexdashboard, formattable, ggiraph, ggvis, highcharter, htmlwidgets, lazyrmd, leaflet, mapview, metricsgraphics, miniUI, papayar, pixiedust, questionr, radarchart, rAmCharts, rglwidget, rmarkdown, rmdformats, SciencesPo, shiny, shinybootstrap2, shinyBS, shinydashboard, shinyDND, shinyFiles, shinyjs, shinyTime, tableHTML, timevis, tmap, tufte, vegalite, vembedr, visNetwork
colourpicker, d3heatmap, DiagrammeR, diffr, DT, dygraphs, edgebundleR, flexdashboard, formattable, ggiraph, gSEM, highcharter, lazyrmd, leaflet, listviewer, mapview, metricsgraphics, networkD3, pairsD3, plotly, profvis, qrage, qtlcharts, radarchart, rAmCharts, rbokeh, rchess, rglwidget, rhandsontable, rpivotTable, scatterD3, simPATHy, svgPanZoom, threejs, timevis, tmap, treescape, trelliscope, vegalite, visNetwork, wordcloud2
boxr, emuR, fiery, jug, opencpu, plumber, rfigshare, servr, shiny, SocialMediaLab, spectrino, switchrGist, tabplotd3
adegenet, AFM, alakazam, aop, arulesViz, BacArena, backShift, BANFF, betalink, bipartite, bnstruct, BoolNet, btergm, BTR, cancerGI, cape, causaleffect, CausalFX, CDVine, CIDnetworks, comato, compete, cooccurNet, crimelinkage, DCGL, degreenet, DiagrammeR, diffusionMap, dnc, Dominance, DSviaDRM, edgebundleR, erah, fbRanks, FCMapper, FedData, flows, FrF2, gemtc, geneNetBP, GERGM, ggenealogy, gimme, gmum.r, gRain, graphTweets, gRbase, gRim, gromovlab, hierformR, highcharter, igraphinshiny, influenceR, intergraph, keyplayer, kinn, kknn, LANDD, ldstatsHD, lexRankr, lintr, lvm4net, markovchain, MatchingFrontier, matie, mixOmics, MRS, nat, nat.templatebrains, netClass, netdiffuseR, netgen, NetOrigin, nets, nettools, networkD3, networkTomography, nlnet, osmplotr, outbreaker, pcalg, PGRdup, phangorn, phylosignal, phyloTop, pop, poplite, poppr, ppiPre, qdap, qgraph, QuACN, rags2ridges, RcmdrPlugin.RMTCJags, RDS, red, RedditExtractoR, restlos, RevEcoR, rmcfs, robustrao, RPANDA, rPref, RQDA, semPlot, SeqGrapheR, seqHMM, SetRank, sharpshootR, shazam, shock, SID, sidier, simcausal, simPATHy, sirt, smart, smerc, smnet, snowboot, SNscan, SocialMediaLab, SpaDES, SSN, stplanr, stringgaussnet, structSSI, synbreed, TDA, tnam, treemap, VertexSimilarity, VSE, WikiSocio, XMRF
mlearning, optBiomarker, RecordLinkage, RTextTools, SurvRank
bigpca, denoiseR, gyriq, igraph, MFPCA, OmicKriging, recommenderlab
BOIN, GSSE, hisemi, ORCME, orderedLasso, pi0
boostr, doRNG, ecospat, foreach, GSODR, hyperSMURF, iLaplace, Information, intercure, iterpc, itertools2, ldamatch, lgcp, LPR, mistral, neuroim, paleoTS, polywog, prospectr, randomUniformForest, rcdk, resemble, scidb, semsfa, SGP, shazam, simr, spacom, spatsurv, ssa, text2vec, tigger, turboEM, YaleToolkit
Ecfun, gazepath, geomorph, gglogo, ggmap, gitter, HiveR, imager, imguR, Momocs, multipanelfigure, OpenImageR, qgraph, rcicr, readbitmap, rosm, RsimMosaic, shapeR, StereoMorph, zooimage
BKPC, DeLorean, fpc, fPortfolio, funcy, gkmSVM, kernelFactory, LinearizedSVR, pi0, plsRcox, qrjoint, rminer, robCompositions, ROI.plugin.ipop, SwarmSVM, Synth
adegraphics, BiplotGUI, condSURV, curvHDR, diveMove, DVHmetrics, earlywarnings, gamclass, GeoXp, ggalt, gplots, hdrcde, kamila, MSBVAR, NCA, prodlim, r2d2, rddtools, SCBmeanfd, SensoMineR, shotGroups, soil.spec, spd, synRNASeqNet, tmap, TSclust, TSdist
dcmr, dlmodeler, MARSS, networkTomography, tsPI
fat2Lpoly, GENLIB, MESS, optiSel, RVFam, RVPedigree, RVsharing, SHLR
ADPclust, assertive, BEQI2, blkbox, bookdown, compareGroups, condformat, confidence, cystiSim, easyformatr, ezknitr, FactoMineR, flexdashboard, formattable, gistr, Gmisc, Greg, gSEM, htmlTable, interAdapt, kfigr, Kmisc, knitLatex, knitrBootstrap, lazyrmd, liftr, lintr, multisensi, ncappc, opencpu, optiRum, pixiedust, PreKnitPostHTMLRender, PSF, qmethod, qwraps2, rAmCharts, rchallenge, RcppFaddeeva, ReporteRs, rglwidget, rite, rleafmap, rmarkdown, rmdformats, rNMF, rtable, rticles, survMisc, tufte, tutorial, ucbthesis, umx, userfriendlyscience, wq
birdring, cdcsis, curvHDR, feature, GPareto, hdrcde, hypervolume, logcondens, rainbow, rugarch, RVPedigree, semiArtificial
futile.logger, futile.matrix, lambda.tools, tawny, tawny.types
bastah, chemometrics, CorReg, gencve, GGMselect, gpDDE, NHMSAR, plsRcox
ade4TkGUI, adegraphics, adespatial, agridat, AICcmodavg, aLFQ, ALTopt, analogue, apc, ape, aqp, asbio, automap, BayesianNetwork, bbmle, bdvis, BigVAR, blackbox, boolean3, c060, caretEnsemble, CDM, cg, ChainLadder, classify, coda, comato, copula, Cprob, cvTools, daewr, DAMisc, DBKGrad, dcmle, DepthProc, desplot, DOBAD, dplR, effects, eiwild, emdbook, EQL, eRm, etm, FactoMineR, faoutlier, fastR, FitAR, fungible, gamclass, gear, GENLIB, ggtern, Giza, GLMMRR, Gmisc, gpairs, GPfit, greport, gstat, hexbin, hydroPSO, IGM.MEA, influence.ME, intubate, isa2, kdecopula, Kmisc, ldbounds, lga, lme4, lmem.gwaser, lmem.qtler, locfit, LPR, lulcc, maptools, mapview, Matrix, mboost, MCMCpack, mice, mirtCAT, mixPHM, MixSIAR, mountainplot, MplusAutomation, mptools, MSBVAR, msSurv, mvna, mycor, nlme, npROCRegression, openair, paleofire, pamm, pedometrics, Phxnlme, PKNCA, plm, plotGoogleMaps, plotMCMC, polySegratioMM, PopGenReport, predictmeans, psychomix, qicharts, qrmtools, QTLRel, R2admb, R2STATS, RAM, rangeMapper, rankFD, RcmdrPlugin.HH, refund, RGraphics, rioja, rminer, RobLox, RobLoxBioC, robustlmm, RPPanalyzer, rrcov, rrcovNA, rSARP, RSPS, Rssa, runjags, scape, sharpshootR, sisal, SixSigma, slfm, sp, spacetime, SPreFuGED, SSN, stlplus, stressr, stylo, Surrogate, survey, synbreed, synergyfinder, TAM, TestingSimilarity, tiger, tigerstats, timeSeq, trajectories, trelliscope, tripEstimation, varbvs, VBmix, VineCopula, visreg, waterData, x12GUI, zoo
DAAG, gamclass, greport, Hmisc, hyperSpec, lfstat, mapview, mosaic, mptools, openair, pedometrics, pems.utils, penDvine, qicharts, R2STATS, RcmdrPlugin.temis, remote, sharpshootR, stressr, Surrogate, varbvs, waterData
faoutlier, gimme, lavaan.shiny, lsl, matrixpls, MBESS, NlsyLinks, nonnest2, piecewiseSEM, pscore, psytabs, qgraph, semPlot, sesem, sirt, TAM, userfriendlyscience
alakazam, assertr, binomen, bioinactivation, carpenter, chunked, cofeatureR, condformat, corrr, datastepr, ddpcr, dplyr, dtplyr, easyformatr, emil, EpiModel, eyetrackingR, forestmodel, funModeling, geoparser, ggvis, gutenbergr, heemod, IAT, jqr, loopr, markmyassignment, mason, mosaic, ncappc, networkreporting, openair, photobiologyInOut, platetools, poplite, purrr, R6Frame, rbokeh, request, rex, rfishbase, rgho, riem, RmarineHeatWaves, RNeXML, ropenaq, rprev, rscorecard, scrubr, shazam, simPH, SpaDES, spdplyr, srvyr, statar, tadaatoolbox, tibble, tidyr, treeplyr, wrswoR.benchmark
eAnalytics, mapr, stationaRy, stplanr, tmap, trackeR
FactoMineR, FitAR, HH, intubate, lessR, meifly, mixlm, mplot
covmat, DoE.wrapper, EasyABC, GPfit, hydroPSO, kernDeepStackNet, metagen, plspolychaos, polychaosbasics, rrepast
cds, evclust, geospt, geosptdb, gpDDE, IntegratedMRF, networkTomography, pi0, restlos, walkr
aroma.affymetrix, aroma.core, future, PSCBS, R.filesets
ARTool, blmeco, brms, climwin, clusterPower, effects, ez, faraway, glmmsr, inferference, lmem.gwaser, lmem.qtler, LMERConvenienceFunctions, lmSupport, mbest, mediation, metaplus, miceadds, mixlm, MixMAP, mlVAR, multiDimBio, MultiRR, MXM, omics, pamm, PBImisc, piecewiseSEM, powerbydesign, R2STATS, refund, refund.shiny, reproducer, RLRsim, rockchalk, RRreg, rstanarm, RVAideMemoire, RVFam, SensMixed, sjmisc, sjPlot, sjstats, SoyNAM, spacom, SPreFuGED, squid, StroupGLMM, Surrogate, TcGSA, tnam, VCA, VetResearchLMM
AutoModel, betareg, chipPCR, clusterSEs, dynlm, earlywarnings, fRegression, gcmr, georob, glmx, mlogit, mnlogit, MRMR, pdR, plm, rddtools, termstrc, treeclim, vcd
CoImp, hdrcde, KATforDCEMRI, kdecopula, LICORS, paleofire
bmrm, Compind, ergm, hdpca, kantorovich, label.switching, limSolve, mediation, MoTBFs, MSCMT, netgen, QCAGUI, QCApro, sampling, systemicrisk
aemo, alm, aoristic, APSIM, apsimr, archivist, Biograph, boxoffice, cardioModel, clifro, climwin, countytimezones, cricketr, cruts, dataonderivatives, dataRetrieval, drsmooth, dtwSat, dynatopmodel, ecoengine, edeaR, EGRET, EGRETci, etl, feedeR, GetHFData, ggpmisc, ggspectra, GSODR, highcharter, iClick, ie2misc, iki.dataclim, machina, macleish, openair, OptiQuantR, pdfetch, photobiology, photobiologyInOut, PhysActBedRest, plusser, primerTree, RefManageR, respirometry, RGA, riem, RmarineHeatWaves, rnoaa, ropenaq, rpdo, rplos, RSQLServer, SciencesPo, SensusR, sp500SlidingWindow, SpaDES, spatsurv, spocc, ss3sim, stationaRy, stplanr, sweidnumbr, timelineS, TropFishR, TTAinterfaceTrendAnalysis, vetools, Wats
bgeva, GFD, GMMBoost, list, MANOVA.RM, MCPAN, netmeta, permutations, refund, rr, SemiParBIVProbit, SemiParSampleSel, spray
analogsea, aoos, apa, archivist, ARTool, bkmr, blkbox, blscrapeR, bpa, carpenter, ckanr, clusternomics, corrr, curlconverter, cystiSim, datacheckr, datadr, datastepr, ddpcr, dendextend, dlstats, dplyr, dpmr, DT, dygraphs, easyformatr, ecoengine, electionsBR, emil, engsoccerdata, eyelinker, FeatureHashing, fulltext, genderizeR, geojsonio, gglogo, ggvis, gistr, gmailr, Gmisc, googleAnalyticsR, Greg, gsheet, heatmaply, highcharter, hpoPlot, htmlTable, httping, HydeNet, icd, igraph, IncucyteDRC, intubate, IsingSampler, jqr, latex2exp, lawn, lazysql, leaflet, lexRankr, lightsout, linear.tools, listless, livechatR, loopr, MakefileR, manhattanly, manifestoR, mason, metricsgraphics, modellingTools, Momocs, mtconnectR, multipanelfigure, networkD3, nhanesA, NNTbiomarker, ontologyPlot, optigrab, pixiedust, plotly, poppr, prettyunits, purrr, rangeMapper, rattle, rBayesianOptimization, rbokeh, rdrop2, request, RevEcoR, rex, rgbif, rgho, rglwidget, rhandsontable, RmarineHeatWaves, rpdo, rpinterest, rprev, rscorecard, rslp, rvest, saeRobust, scrubr, searchable, simmer, simulator, sjPlot, spark, srvyr, ss3sim, stplanr, stringr, subspaceMOA, survminer, taber, tableHTML, testthat, text2vec, tidyr, tigris, timelineS, useful, vcfR, vegalite, vembedr, visNetwork, webshot, wellknown, wfindr, wordbankr, xgboost
autoimage, ggmap, openair, pavo, perspectev, rbison, s2dverification
bdvis, etasFLP, ggalt, hyfo, IPtoCountry, OIdata, qlcVisualize, r4ss, rbokeh, rinat, rvertnet, smerc, SpatialExtremes, SpatialVx, swfscMisc
aoristic, BayesX, biogeo, BPEC, capm, dynatopmodel, ecospat, eeptools, EMbC, geojsonio, ggsn, hyfo, letsR, lgcp, magclass, MapGAM, MetaLandSim, openadds, opentraj, pgirmess, plotGoogleMaps, prevR, qlcVisualize, rangeMapper, rAvis, red, rworldmap, secrlinear, SpatialEpi, SSN, stplanr, SWMPr, tigris, trip, tweet2r, vetools, vmsbase
BEQI2, confidence, datamart, DVHmetrics, ezknitr, Kmisc, knitr, knitrBootstrap, leaflet, mirtCAT, rite, shinystan, tutorial
cwm, expands, fdcov, KATforDCEMRI, markovchain, NPC, perARMA, rcicr, rwt
backShift, BEDASSLE, CARBayes, CARBayesST, COUSCOus, evolqg, face, fdasrvf, geesmv, ICsurv, madness, MarkowitzR, matrixpls, mgm, PCDSpline, qrLMM, qrNLMM, RMark, rodd, sem, SharpeR, Skillings.Mack, stablespec
ACNE, aroma.affymetrix, aroma.cn, aroma.core, bdynsys, bingat, calmate, carx, cointmonitoR, cointReg, dplR, FADA, fslr, loo, Luminescence, MFHD, mmtfa, peakPick, PSCBS, randomizationInference, SemiParBIVProbit, SemiParSampleSel, SGP, sizeMat, statar, stm, WGCNA
DirichletReg, DWreg, HiDimMaxStable, mclcar, paramlink, rDEA, splm, Zelig
GEOmap, rNOMADS, Rquake, RSurvey, StatDA
apaTables, auRoc, predictionInterval, replicationInterval, userfriendlyscience
AdaptGauss, BANFF, Bchron, Bclim, chemometrics, clustMD, CONDOP, ContaminatedMixt, CorReg, expands, flexCWM, fpc, kamila, kinn, KScorrect, optCluster, robCompositions, semiArtificial, TipDatingBeast, VBLPCM, vscc, yCrypticRNAs
BayesLCA, BayesSingleSub, blavaan, CARBayes, coarseDataTools, dnc, evolqg, fdrDiscreteNull, HKprocess, HWEBayes, MCPAN, miscF, mvst, NSUM, PANICr, PortRisk, sirt, SizeEstimation, sizeMat, sparsereg, spikeSlabGAM, Zelig, ZeligEI
BWStest, covr, DeLorean, devtools, heemod, opencage, prcbench, rgho, saeRobust, toaster
MAVIS, metagear, metagen, metaplus, NSM3, RcmdrPlugin.MA, reproducer, xmeta
AdaptFitOS, analogue, apsimr, brms, car, causaldrf, cSFM, demography, discSurv, dlnm, drsmooth, DSpat, dtwSat, ez, FCGR, FDboost, fRegression, funreg, FWDselect, gamclass, groc, gsg, Haplin, HLMdiag, iRegression, landsat, LMERConvenienceFunctions, loa, LW1949, MFPCA, MHTrajectoryR, mirt, ModelMap, mrds, MvBinary, npregfast, openair, palaeoSig, pitchRx, QRM, QuasiSeq, RcmdrPlugin.HH, refund, reldist, rioja, RLRsim, rstpm2, secr, SEERaBomb, sesem, simPH, sisal, slp, snht, spatstat, spsmooth, SSDM, StatDA, tripEstimation, tsDyn, vegan, vows, VWPre, WhiteStripe, zetadiv
BaM, cati, missMDA, PathSelectMP, Qtools
boxr, gmailr, httr, jug, markdown, RSocrata, servr, shiny
addinslist, bookdown, Cite, citr, colourpicker, ggExtra, ggThemeAssist, questionr, shinyjs
cdom, DBKGrad, downscale, drLumi, FatTailsR, FME, growthcurver, Luminescence, MetaLandSim, mixtox, MortHump, Rquake, semds, TIMP
cplm, geosptdb, glmmLasso, GMMBoost, GxM, lme4, optimx, simecol, VARsignR, wCorr
curvHDR, feature, multiDimBio, NPCirc, plot3D, prim
censReg, DIFlasso, frontier, LOST, MAINT.Data, micEcon, micEconAids, micEconCES, micEconSNQP, mvProbit, sampleSelection, yhat
BIFIEsurvey, Conigrave, kmi, miceadds, missDeaths
Compositional, ContaminatedMixt, flexCWM, MixGHD, pmcgd
bapred, BayesCR, bayou, blavaan, CensMixReg, ContaminatedMixt, correctedAUC, cSFM, derivmkts, dma, EasyABC, ei, eiCompare, EMbC, ERP, FADA, flexCWM, HiDimMaxStable, highmean, lavaan, MBESS, mixAK, mvst, paleoTS, phytools, pmcgd, psych, SemiParBIVProbit, SIBER, sn, ssmn, tsDyn, VBmix, wCorr
betareg, bujar, coin, eaf, flexmix, PSAboot, psychomix, topicmodels
AFM, BrailleR, CorrToolBox, cSFM, ecd, expands, frontier, hyfo, mvdalab, MVN, nullabor, PDQutils, qat, royston, semsfa, ShinyItemAnalysis, sisus, ssmn, validann
ARCensReg, Biograph, breakpoint, bsam, CIDnetworks, clustMD, decisionSupport, drLumi, ei, eiCompare, gems, gmnl, httk, iBATCGH, msmtools, optBiomarker, parfm, phytools, Rchoice, RMark, rriskDistributions, rtdists, SizeEstimation, sparsereg, TAM, TropFishR
ANOM, cg, coin, Crossover, Deducer, dpcR, drc, drsmooth, factorplot, gMCP, lsmeans, MCPAN, mixlm, mutoss, rms, sensR, SimComp, TTAinterfaceTrendAnalysis, VetResearchLMM
ARCensReg, asbio, ASSISTant, BayesComm, BayesCR, BayesFactor, bayesGARCH, BayesMAMS, BayesSingleSub, bayesTFR, bcpmeta, bcrm, bindata, binMto, BinOrdNonNor, BMhyd, Bolstad, boolean3, bootnet, boral, BPEC, BSagri, CALIBERrfimpute, carx, CCTpack, CDVine, CensMixReg, CIDnetworks, clikcorr, clinfun, clusteval, clustMD, coin, conting, cope, copula, copulaedas, CorrBin, CorReg, CorrToolBox, CosmoPhotoz, covsep, crawl, crmPack, csn, decisionSupport, depth.plot, DescTools, DFIT, discSurv, ei, eiCompare, ETC, evolqg, fakeR, FastGP, fdasrvf, flexsurv, FMsmsnReg, fMultivar, fpc, freestats, fungible, funreg, geiger, gMCP, goric, graphicalVAR, growfunctions, gsg, gyriq, hierarchicalDS, hmmm, HWEBayes, hyperdirichlet, ic.infer, ifa, Infusion, intamap, interAdapt, iopsych, IRTpp, kernDeepStackNet, kernscr, latentnet, LICORS, LINselect, list, lrgs, lsmeans, MARSS, matchMulti, matie, maxstat, MCPAN, mcprofile, Mediana, merTools, MESS, miceadds, miscF, missMDA, mistral, MixGHD, mixpack, mlVAR, monomvn, mratios, MSBVAR, msm, MTS, multicon, multimark, MultiMeta, multivator, mvst, nonnest2, OPDOE, optismixture, pamm, PARSE, pcaPP, pez, phylometrics, PIGShift, plsRbeta, plsRglm, plsVarSel, pmhtutorial, pomp, PopED, Power2Stage, PowerTOST, protiq, qrLMM, qrNLMM, QVM, ragt2ridges, random.polychor.pa, rase, rebmix, REndo, RobustEM, rpf, rrcov, sampleSelection, SEHmodel, sensitivity2x2xk, shock, SimComp, simexaft, simPATHy, sirt, SmoothHazard, sns, sortinghat, spaMM, sparsediscrim, SparseTSCGM, sparsevar, spikeSlabGAM, SPreFuGED, SQDA, supcluster, tailDepFun, TAM, tglm, timeROC, tsbridge, TTAinterfaceTrendAnalysis, umx, uniReg, varComp, VineCopula
cruts, erah, hyfo, lgcp, magclass, marmap, ncdf4.helpers, qat, rerddap, s2dverification, SchemaOnRead, SDMPlay
BANFF, bingat, btergm, degreenet, EpiModel, epinet, geomnet, ggnetwork, gwdegree, intergraph, SchemaOnRead, sidier, SparseTSCGM, statnet, tnam, toaster, VineCopula
dynsurv, frailtySurv, fungible, georob, LDPD, mclcar, meteR, miCoPTCM, PCDSpline, pim, synergyfinder
agricolae, AICcmodavg, ape, arm, BayesLCA, bkmr, boostmtree, broom, cardioModel, caret, carx, cem, cg, CLME, coxme, cplm, dlnm, dsm, easyanova, eba, faraway, FindMinIC, gcmr, geesmv, GeNetIt, georob, Greg, GxM, IntegratedJM, intubate, investr, lme4, lmms, lqmm, lsmeans, lucid, MARSS, MBESS, MultiSV, nlmeU, nlsem, OPDOE, piecewiseSEM, PKNCA, plm, PopED, psychometric, QVM, rareGE, refund, RLRsim, rms, robustlmm, rstanarm, secr, SemiPar, sjmisc, sjPlot, sjstats, SMPracticals, spacom, spaMM, spdep, sphet, splm, StroupGLMM, Surrogate, surveillance, tergm, TTAinterfaceTrendAnalysis, urca, varComp, vcrpart, VetResearchLMM
blackbox, ICAOD, lme4, minimaxdesign, nlshrink, OptimaRegion, optiSel, pomp, ptw, ROI.plugin.nloptr, rugarch, seqHMM, spaMM
NLPutils, openNLP, qdap, syuzhet, textreg, textreuse, tm.plugin.alceste, tm.plugin.dc, tm.plugin.europresse, tm.plugin.factiva, tm.plugin.lexisnexis, tm.plugin.mail, tm.plugin.webmining
BaBooN, BaM, BayesTree, Biocomb, biomod2, blkbox, car, chemometrics, CoImp, DAMisc, discretecdAlgorithm, dprep, EffectLiteR, effects, EnsembleBase, factorplot, flexmix, forecast, Frames2, fRegression, gencve, gnm, Hmisc, hybridEnsemble, intubate, ipred, ipw, IsingSampler, mice, mlearning, MXM, NeuralNetTools, NoiseFiltersR, oblique.tree, pvsR, rasclass, RcmdrPlugin.BCA, RecordLinkage, rminer, RTextTools, RVAideMemoire, semiArtificial, ShinyItemAnalysis, simPop, sparsebnUtils, spectral.methods, spls, SSDM, tsDyn, VIM
Anthropometry, erah, gpDDE, hybridEnsemble, isotone, mboost, osd, phangorn, rNMF, simest, smacof, TIMP
AID, BrailleR, earlywarnings, momr, moonBook, MVN, myTAI, NSM3, quickReg, royston, SixSigma, tadaatoolbox
eggCounts, mvPot, permutations, quhomology, vertexenum
antitrust, ARCensReg, bbmle, BinaryEPPM, blackbox, BMhyd, boolean3, CIDnetworks, condGEE, copula, corHMM, Countr, CountsEPPM, ctmcd, ctmm, DoubleExpSeq, dynr, ExtDist, fdapace, FDGcopulas, finiteruinprob, flexCWM, frailtySurv, GB2, geostatsp, gofCopula, GPvam, gsg, HAC, indelmiss, inferference, Infusion, IRTpp, kergp, lava, marked, markophylo, metaplus, metRology, mets, midasr, milr, mirt, MixGHD, mlt, mlt.docreg, mpath, MPTinR, mrds, optimr, optimx, OUwie, phytools, pi0, ProbitSpatial, pssm, Rcgmin, RealVAMS, Renext, robustloggamma, robustvarComp, rodd, rstpm2, rugarch, sdprisk, sensR, seqHMM, sn, sns, spfrontier, StableEstim, stochprofML, SurvRegCensCov, tcpl, ThreeArmedTrials, timereg, TKF, umx, VCA, vcrpart, xmeta
backblazer, base64, bcrypt, httr, opencpu
CLME, CUFF, ie2misc, mrMLM, reproducer, rio, stplanr, tigerhitteR, TROM
BioGeoBEARS, boolean3, calibrar, CatDyn, Countr, covmat, ecd, ExtDist, gear, invGauss, LifeHist, marked, mrds, MRS, MSCMT, rankdist, REndo, spfrontier, Synth
brainGraph, dti, gdimap, oasis, oro.dicom, oro.pet, papayar, spm12r, vows, WhiteStripe
basefun, mpoly, OPDOE, PDQutils, sadists
BrailleR, brr, carpenter, DecisionCurve, funModeling, MplusAutomation, mscstexta4r, mscsweblm4r, QVM, rapport, rapportools, SciencesPo, summarytools
HiDimMaxStable, matchingMarkets, mpoly, permutations, spray, untb
blkbox, EcoGenetics, EFS, mboost, multilevelPSA, PSAboot, RFinfer, rminer, simPop, synthpop
activity, BayesFactor, caretEnsemble, cdcfluview, easyVerification, extremeStat, longurl, predictionInterval, replicationInterval, ResourceSelection, RFinfer, warbleR, WikiSocio, zebu
CIDnetworks, ctmm, GPareto, lavaan, sirt
afex, car, lmSupport, piecewiseSEM, predictmeans, simr, StroupGLMM
chemometrics, copula, CosmoPhotoz, DetR, ftsa, lcopula, OutlierDM, rmgarch, rrcov, rrcovHD, smart, specmine, sprm
mmod, PopGenReport, poppr, rmetasim, strataG
apricom, DIFboost, DIFlasso, gpDDE, hdnom, mvdalab, pensim
bipartite, brainGraph, codyn, cwm, expands, NPC, pRF, RAM, randomizationInference, rankdist, VdgRsm
coalescentMCMC, CommT, corHMM, indelmiss, markophylo, OUwie, paleotree, phytools, poppr, RADami, RAM, recluster, rwty, SeqFeatR, strataG, timetree, TKF, treescape
adephylo, BMhyd, PCPS, phyext2, phylosignal, phyloTop, SigTree
BMhyd, BPEC, brranching, DDD, evobiR, hisse, monogeneaGM, OUwie, paleotree, PBD, phylocurve, PhySortR, RAM, recluster, RPANDA, Rphylopars, TKF, treeplyr
betapart, DAMOCLES, lefse, metricTester, nodiv, PCPS, pez, recluster
asbio, plotKML, shapeR, sparkTable, VBmix
ChaosGame, dnc, mixedsde, partialAR, smoof
deeplearning, eechidna, ggenealogy, manhattanly, RtutoR, smoof
ABCanalysis, aqp, asbio, BayesBD, bcRep, bdvis, BioGeoBEARS, cems, cncaGUI, convoSPAT, coreNLP, cricketr, drc, ei, eiCompare, FSA, GFD, gmnl, HTSCluster, IntClust, IsotopeR, JBTools, KernSmoothIRT, kineticF, LogicForest, LW1949, MANOVA.RM, marmap, MatrixCorrelation, metricTester, mutoss, ncdf.tools, NPCirc, phonR, phytools, plotKML, plotSEMM, PReMiuM, qdap, Rchoice, rminer, SAGA, simr, smacpod, vmsbase, xhmmScripts, yhat
chemometrics, chillR, cocoreg, EasyABC, enpls, groc, IntClust, intubate, LINselect, mixlm, plsRcox, rminer, rrcovHD, RVAideMemoire, soil.spec, specmine, spls, statTarget
AFM, colourlovers, d3heatmap, dplR, Fgmutils, ggmap, ggsn, HiveR, imager, imguR, iplots, leaflet, loa, mapview, monographaR, multipanelfigure, nasadata, OpenImageR, qgraph, rAltmetric, rcdk, readbitmap, ReporteRs, retistruct, RgoogleMaps, RMThreshold, rosm, StereoMorph, Thermimage, tikzDevice, trelliscope, zooimage
AssetPricing, basefun, ecd, ggpmisc, hwwntest, mpoly, OPDOE, partitions, preseqR, smacof, tolBasis, tsoutliers, untb
admixturegraph, AFM, batteryreduction, bdynsys, binsmooth, cdfquantreg, CosW, dpcR, eemR, EMSC, fdapace, GUILDS, iemisc, inctools, IRISMustangMetrics, IRISSeismic, MatrixCorrelation, mixlm, mousetrap, PEIP, QuasiSeq, rtdists, SecKW, SEHmodel, semds, SinIW, soundecology, TanB
Biocomb, biomod2, BioPET, blkbox, EFS, FAMILY, LogisticDx, LOGIT, mlDNA, quantable, randomUniformForest, SCGLR, statTarget
bnnSurvival, IntClust, ipred, ModelGood, SmoothHazard, SuperRanker
abbyyR, fuzzr, MatrixCorrelation, plsVarSel, stationaRy
bcRep, blackbox, cccd, dtwSat, HighDimOut, Infusion, LDAvis, lexRankr, mtconnectR, quanteda, spaMM, SSL, vdg
httping, kimisc, KSD, linear.tools, rbokeh, summarytools
copula, FCGR, GenWin, optiSel, phtt, RPANDA
broom, CCTpack, CDM, CorrMixed, CorrToolBox, CTTShiny, dtables, ionr, IRTShiny, lavaan.shiny, likert, lmSupport, lrmest, manifestoR, matrixpls, mousetrap, multilevelPSA, MVN, OpenRepGrid, prepdat, PSAboot, psytabs, qgraph, qmethod, qrLMM, qrNLMM, quickReg, QVM, sdmvspecies, sirt, sjPlot, TAM, traj, TriMatch, userfriendlyscience
apa, corrr, curlconverter, cymruservices, docxtractr, estatapi, fuzzr, fuzzyjoin, geoparser, gglogo, googlesheets, gutenbergr, highcharter, livechatR, milr, pollstR, RevEcoR, tidytext, uaparserjs, wand
bootnet, diveRsity, gimme, graphicalVAR, IATscores, IsingFit, mlVAR, semPlot, SparseLearner
lineup, lmem.gwaser, lmem.qtler, PopVar, qtlcharts
BB, CEGO, directlabels, dti, earlywarnings, expectreg, FinCovRegularization, flexsurv, fPortfolio, GENLIB, goric, gromovlab, hmmm, hybridEnsemble, ic.infer, lavaan, limSolve, list, mboost, mcprofile, mistral, MixtureInf, mlt, monomvn, MoTBFs, nodeHarvest, npbr, npsp, opera, orderedLasso, parma, penDvine, phangorn, pi0, pracma, robustrao, rodd, ROI.plugin.quadprog, ScreenClean, simPH, tseries, uniReg, varComp
bdrift, creditr, DMwR, highcharter, qrmtools, tawny, tawny.types, TSmisc
apTreeshape, car, chipPCR, cmprskQR, cobs, crs, diveMove, erah, gapfill, georob, MAVIS, MCMCpack, MXM, NCA, NSM3, opera, OutlierDM, pez, qrLMM, qrNLMM, Qtools, quantspec, rms, RPPanalyzer, SGP, sitar, TTCA, Zelig
clusterSim, psytabs, pubmed.mineR, RcmdrPlugin.temis, RenextGUI, RSCABS, umx
agRee, bamdit, boral, classify, MixSIAR, SeqFeatR
ASSISTant, bigrquery, choroplethr, coala, datastepr, data.tree, desc, distcomp, dplyr, fiery, fitcoach, glmmsr, googleAuthR, gsrc, homomorpheR, httr, jaatha, jug, loopr, mcparallelDo, mkin, pbdZMQ, plumber, polmineR, prcbench, progress, PythonInR, R6Frame, rchess, rcrossref, RDML, readr, request, RKEEL, rstack, rtson, shiny, shopifyr, simcausal, simmer, storr, telegram, testthat, tmlenet, vmsbase
constrainedKriging, geoR, georob, lgcp, SpaDES, spatsurv
abcrf, aCRM, aLFQ, bagRboostR, Biocomb, biomod2, blkbox, CALIBERrfimpute, cem, CONDOP, conformal, CovSelHigh, ecospat, EFS, EnsembleBase, FSelector, fuzzyforest, gamclass, gencve, ggRandomForests, hybridEnsemble, hyperSMURF, imputeMissings, kernelFactory, LINselect, mlearning, NAM, nodeHarvest, NoiseFiltersR, nproc, optBiomarker, OTE, preprocomb, preproviz, pRF, randomForest.ddR, rasclass, REPTILE, RFmarkerDetector, rfUtilities, rminer, RPtests, RTextTools, SPOT, SSDM, statTarget, synthpop, TLBC, vita, VSURF, zoon
boostmtree, ggRandomForests, riskRegression, sprinter, SurvRank
cda, cepp, copBasic, FDGcopulas, GPareto, mcGlobaloptim, minimaxdesign
addinslist, getlandsat, mregions, nat.templatebrains, openadds, packagetrackr, pangaear, tigris, TR8, wand
bfast, biogeo, birdring, bnspatial, cartography, cdlTools, clhs, cruts, ctmm, DiversityOccupancy, dynatopmodel, EcoGenetics, ecospat, ENMeval, FedData, gdalUtils, GeNetIt, graticule, GSIF, GSODR, hddtools, ipdw, kehra, lakemorpho, landscapeR, leaflet, lgcp, Luminescence, mapview, marmap, MaxentVariableSelection, memgene, MetaLandSim, meteo, mkde, monographaR, mptools, ncdf.tools, nodiv, OpenStreetMap, opentraj, osrm, paleofire, platetools, plotGoogleMaps, plotKML, prism, qlcVisualize, quadmesh, quickmapr, rangeMapper, rasterKernelEstimates, rAvis, red, rleafmap, rLiDAR, RmarineHeatWaves, rpostgis, RQGIS, rSPACE, RStoolbox, sdm, SDMPlay, sdmvspecies, secr, SEHmodel, sirad, SpaDES, spatialEco, spatsurv, speciesgeocodeR, spectral.methods, SSDM, stplanr, tmap, trackeR, trip, unmarked, wrspathrow
biomod2, cati, gfcanalysis, lulcc, mptools
aroma.affymetrix, aroma.cn, aroma.core, fulltext, PSCBS, repmis, R.filesets, R.rsp, scholar
betapart, blackbox, CausalFX, hitandrun, Infusion, kantorovich, pavo, sisus
BCA, BiodiversityR, learnstats, RcmdrPlugin.BiclustGUI, RcmdrPlugin.DoE, RcmdrPlugin.EACSPIR, RcmdrPlugin.EZR, RcmdrPlugin.FactoMineR, RcmdrPlugin.GWRM, RcmdrPlugin.HH, RcmdrPlugin.IPSUR, RcmdrPlugin.lfstat, RcmdrPlugin.MA, RcmdrPlugin.NMBU, RcmdrPlugin.orloca, RcmdrPlugin.qual, RcmdrPlugin.RMTCJags, RcmdrPlugin.sampling, RcmdrPlugin.SCDA, RcmdrPlugin.SLC, RcmdrPlugin.sos, RcmdrPlugin.survival, RcmdrPlugin.TeachingDemos, RcmdrPlugin.temis, REST
adegraphics, aoristic, aqp, aroma.core, bioplots, cape, clifro, dtwSat, edgar, EMbC, EpiModel, ergm.ego, fheatmap, ggalt, granovaGG, HH, hierarchicalSets, HiveR, imageData, inpdfr, iprior, LambertW, leaflet, LICORS, loa, LogisticDx, lpbrim, LPStimeSeries, lvplot, mapr, mapStats, mcPAFit, micromapST, mixOmics, MixSIAR, MKmisc, Mondrian, MortHump, mousetrap, msarc, MSG, msr, mstate, multiDimBio, MultiPhen, mvcwt, mvtboost, myTAI, ncdf.tools, NetRep, NMF, oaColors, openair, opera, OutbreakTools, PAFit, patPRO, pcaBootPlot, pems.utils, PharmacoGx, pheatmap, platetools, plotKML, pqantimalarials, psd, PubMedWordcloud, quantable, rafalib, RAM, rangeMapper, rasterVis, rbefdata, RcmdrPlugin.KMggplot2, RcmdrPlugin.temis, RNCEP, RobLox, RobLoxBioC, RSA, scales, sharpshootR, SigTree, sisus, smoof, solaR, SOMbrero, sorvi, SpaDES, spatsurv, specmine, spectral.methods, spoccutils, statebins, statnetWeb, StMoMo, strataG, svdvis, SWMPr, tagcloud, tcpl, tdr, TELP, TippingPoint, tmap, toaster, TraMineR, treemap, TROM, vqtl, waffle, Wats, WeightedCluster, xseq
bfa, DiffusionRgqd, DiffusionRimp, DiffusionRjgqd, TED
Cyclops, dbmss, FLSSS, GERGM, markovchain, microclass, MultiBD, roll, rPref, SpatMCA, SpatPCA, text2vec
acs, AmostraBrasil, archivist, atsd, bigml, biomartr, blsAPI, Causata, cdlTools, clifro, creditr, dams, datamart, dbhydroR, demography, dvn, easyVerification, Ecfun, fbRads, feedeR, FinCal, finreportr, GetHFData, GetTDData, gfcanalysis, gmapsdistance, gProfileR, GuardianR, h2o, hddtools, HierO, HMDHFDplus, icesDatras, icesSAG, interAdapt, IRISMustangMetrics, IRISSeismic, MODISTools, nhlscrapr, Ohmage, OIdata, OpasnetUtils, osrm, OutbreakTools, paleobioDB, phylosignal, pinnacle.API, placement, plusser, polidata, pubmed.mineR, PubMedWordcloud, qdap, qdapTools, RAdwords, rainfreq, rAltmetric, rAvis, rbefdata, RbioRXN, Rbitcoin, rClinicalCodes, RCriteo, RCryptsy, rdatamarket, rdefra, rDVR, rechonest, RefManageR, Reol, retrosheet, reutils, Rexperigen, RForcecom, rglobi, rite, RKlout, RMixpanel, rNOMADS, rnrfa, ROAuth, ROpenWeatherMap, RPresto, RProtoBuf, rpubchem, RQGIS, rsconnect, rsdmx, RSmartlyIO, rsnps, RStripe, rtematres, rusda, RYandexTranslate, rYoutheria, scidb, seeclickfixr, SocialMediaLab, SocialMediaMineR, sophisthse, spatialEco, stplanr, stringgaussnet, swirl, Thinknum, tm.plugin.webmining, TR8, translate, translateR, treebase, ukgasapi, umx, uptimeRobot, warbleR, webchem, WikiSocio, XML2R, ZillowR, zoon
abbyyR, biomartr, dataonderivatives, dataRetrieval, ddpcr, eemR, estatapi, eyelinker, geojsonio, GetHFData, getlandsat, googlesheets, GSODR, gunsales, gutenbergr, macleish, mosaic, myTAI, ncappc, neuroim, openadds, photobiologyInOut, pollstR, readODS, rgho, riem, rio, rmapshaper, rpdo, rrefine, stationaRy, stplanr, traits, webreadr
chillR, DLMtool, dpcR, GetTDData, ie2misc, lessR, Luminescence, popprxl, RcmdrMisc, rio, SchemaOnRead, TR8
alm, aqp, automap, benchmark, Biograph, blkbox, bold, climwin, cocoreg, CommT, contoureR, DecisionCurve, drLumi, dynsurv, ezsim, GGally, imageData, intsvy, kobe, LOGIT, MEGENA, MetaIntegrator, Methplot, MissingDataGUI, MixSIAR, multilevelPSA, MultiSV, opentraj, PopGenReport, rags2ridges, RAM, simTool, spikeSlabGAM, SurvRank, timeSeq, TR8, TTAinterfaceTrendAnalysis, WRS2
AmostraBrasil, aoristic, birdring, camtrapR, capm, cdlTools, ctmm, dtwSat, dynatopmodel, EcoGenetics, FedData, gdalUtils, geojsonio, geotopbricks, gfcanalysis, GSIF, GSODR, hddtools, hyfo, lakemorpho, landsat8, letsR, mapview, MazamaSpatialUtils, meteo, OasisR, OpasnetUtils, OpenStreetMap, opentraj, paleofire, pgirmess, plotGoogleMaps, plotKML, PopGenReport, postGIStools, prettymapr, quickmapr, rangeMapper, rAvis, rcanvec, red, riverdist, rmapshaper, rnrfa, rosm, RQGIS, rWBclimate, SDMPlay, SEHmodel, SpatialPosition, sperich, stplanr, tigris, tmap, tripEstimation, tweet2r, wrspathrow, wux
birdring, cartography, constrainedKriging, DSpat, dynatopmodel, FedData, GeNetIt, geoaxe, geojsonio, GeoXp, gfcanalysis, hierarchicalDS, hyfo, lakemorpho, letsR, lgcp, MazamaSpatialUtils, MetaLandSim, OasisR, osmplotr, osrm, pgirmess, postGIStools, quickmapr, rangeBuilder, rangeMapper, red, rpostgis, RStoolbox, RSurvey, SDraw, SEHmodel, spatialEco, SpatialPosition, spatsurv, spsurvey, stplanr, tigris, tmap, wildlifeDI, wrspathrow, wux
AFM, anacor, analogueExtra, Anthropometry, Biocomb, biplotbootGUI, cems, ChemoSpec, clusterSim, cncaGUI, corr2D, crs, curvHDR, DiffusionRgqd, DiffusionRimp, DiffusionRjgqd, dprep, feature, forestFloor, GrammR, graphscan, homals, HUM, imPois, KernSmoothIRT, LMERConvenienceFunctions, matlib, mixOmics, monogeneaGM, Morpho, msir, MSQC, msr, multibiplotGUI, nanop, netmeta, neuroim, NPCirc, OceanView, OpenRepGrid, pca3d, phylocurve, pi0, prim, QuantumClone, rase, restlos, retistruct, rglwidget, rLiDAR, RnavGraph, RockFab, Rquake, rsml, SDD, SEERaBomb, shapes, shinyRGL, Sim.DiffProc, sparr, spatgraphs, spatsurv, specmine, StatDA, Surrogate, symbolicDA, termstrc, tolerance, treescape, vegan3d
CRF, fPortfolio, gemtc, HotDeckImputation, kantorovich, MCDA, MultAlloc, networkTomography, npbr, parma, ROI.plugin.glpk
choroplethr, energyr, ggmap, loa, openair, PopGenReport, RAM, stplanr
bayesDem, clusterfly, GrammR, inpdfr, maGUI, mrMLM, PKgraph, playwith, rattle, rggobi, RQDA, RSCABS, Rz, strvalidator, VIMGUI, WMCapacity, x12GUI
BACCT, bamdit, bayescount, bayesmix, bdpopt, BTSPAS, CCTpack, crmPack, dclone, EasyMARK, gemtc, jagsUI, MixSIAR, morse, RcmdrPlugin.RMTCJags, SIBER, StatMethRank
asymmetry, BACA, blkbox, boilerpipeR, coreNLP, Deducer, DeducerExtras, expands, G2Sd, hive, llama, mailR, mutossGUI, Myrrix, Myrrixjars, NoiseFiltersR, openNLP, openNLPdata, OpenStreetMap, PortfolioEffectEstim, PortfolioEffectHFT, prcbench, rcdk, red, ReporteRs, ReporteRsjars, RFreak, RKEA, RKEAjars, RMOAjars, RSQLServer, RWeka, RWekajars, RxnSim, SqlRender, subspace, subspaceMOA, TSsdmx, wordnet, XLConnect, XLConnectJars
AntWeb, aop, argparse, blsAPI, Causata, d3Network, edgebundleR, geonames, GetoptLong, ggmap, helsinki, james.analysis, nhlscrapr, OpasnetUtils, OutbreakTools, paleobioDB, pinnacle.API, prettymapr, RAdwords, rbefdata, rClinicalCodes, rethinker, rfisheries, rglobi, rnrfa, rosm, rpinterest, SmarterPoland, SocialMediaLab, solr, sotkanet, StereoMorph, stmBrowser, structSSI, tutorial, twitteR, uptimeRobot, vdmR, warbleR, yhatr
AmostraBrasil, bigml, biom, datamart, FAOSTAT, gridSVG, GuardianR, knockoff, LDAvis, OData, Ohmage, PAC, plusser, pxweb, rAltmetric, Rbitcoin, RCryptsy, rdatamarket, RedditExtractoR, RefManageR, rfigshare, RgoogleMaps, rpubchem, RPushbullet, rsconnect, RSDA, rYoutheria, shinyFiles, shopifyr, stringgaussnet, switchrGist, tabplotd3, Thinknum, timeseriesdb, tm.plugin.webmining, translate, translateR, WaterML
eemR, highcharter, PATHChange, rAmCharts, RDML, rrefine
HLMdiag, lmeresampler, refund, simr, varComp, vows
addinslist, apa, blkbox, bookdown, BrailleR, caRpools, compareGroups, condformat, DataExplorer, flexdashboard, formattable, gistr, Gmisc, knitrBootstrap, lazyrmd, liftr, monographaR, PreKnitPostHTMLRender, prereg, prettydoc, rchallenge, resumer, revealjs, rmdformats, rmdshower, rticles, RtutoR, swirlify, timevis, tufte
eemR, KATforDCEMRI, oXim, retistruct, sisal
ACNE, aroma.affymetrix, aroma.apd, aroma.cn, aroma.core, calmate, cgdsr, NPCD, PSCBS, R.cache, R.devices, R.filesets, R.huge, R.matlab, R.rsp, rtf, R.utils, sisal, tmle.npvi
downscale, ecd, HH, ldatuning, OUwie, SemiParBIVProbit, SNscan
apricom, bujar, cg, Daim, ecospat, glmBfp, Greg, greport, haplo.stats, hdnom, lodGWAS, LogisticDx, mztwinreg, nlrr, pec, plsRcox, PResiduals, riskRegression, rprev, shrink, spatialEco, Surrogate, SvyNom, VizOR
Causata, MetaIntegrator, tcpl, TSMySQL, wordbankr
betas, covmat, groc, qqtest, robustvarComp
CerioliOutlierDetection, chemometrics, chipPCR, complmrob, covmat, cvTools, DetR, ergm, fAssets, fpc, fPortfolio, georob, GeoXp, Gmedian, groc, ldstatsHD, MKmisc, MVN, mvoutlier, pcalg, roahd, robreg3S, robustlmm, robustloggamma, robustvarComp, sdcMicro, semiArtificial, shotGroups, sprm, StatDA, tergm, VIM
aLFQ, AutoModel, Biocomb, btergm, DMwR, DRaWR, DrugClust, EFS, EMP, funModeling, gkmSVM, hybridEnsemble, lulcc, mlDNA, MLmetrics, NEArender, netClass, OmicKriging, prcbench, RFmarkerDetector
FuzzyLP, ROI.plugin.cplex, ROI.plugin.ecos, ROI.plugin.glpk, ROI.plugin.ipop, ROI.plugin.nloptr, ROI.plugin.quadprog, ROI.plugin.scs, ROI.plugin.symphony
ACNE, aroma.affymetrix, aroma.apd, aroma.cn, aroma.core, calmate, cgdsr, PSCBS, R.cache, R.devices, R.huge, R.matlab, R.rsp, rtf, tmle.npvi
addhazard, BayesCR, BivUnifBin, bvpSolve, condGEE, drLumi, fbati, givitiR, nettools, RadTran, rodd, sdprisk, StMoMo
BCA, Biocomb, biomod2, bst, CORElearn, CorReg, DMwR, dprep, fastAdaboost, FFTrees, gamclass, gencve, Harvest.Tree, Hmisc, hybridEnsemble, ibmdbR, intubate, ipred, LTRCtrees, MergeGUI, mice, NoiseFiltersR, PSAboot, RcmdrPlugin.BCA, RecordLinkage, rminer, rms, rotationForest, SPOT, SSDM, supclust, SurvRank, synthpop, vcrpart, VSURF
DStree, ibmdbR, RcmdrPlugin.BCA, regclass, yorkr
GEOmap, geophys, ProfessR, RFOC, Rquake, RSEIS, RTOMO
megaptera, postGIStools, sejmRP, TSPostgreSQL, tweet2r
ACDm, clickstream, fPortfolio, GofKmt, guess, ICAOD, mrds, QFASA, rmgarch, rugarch, TBSSurvival, wqs
APSIM, archivist, BatchExperiments, BatchJobs, CollapsABEL, ecd, emuR, imputeMulti, maGUI, marmap, MetaIntegrator, poplite, rangeMapper, SEERaBomb, SGP, smnet, sqliter, tcpl, trackeR, TSSQLite, tweet2r, UPMASK, vmsbase
beanz, DeLorean, dfpk, DrBats, edstan, rstanarm, shinystan
Cite, citr, devtools, DiagrammeR, getPass, ggThemeAssist, GUIProfiler, lintr, MetaAnalyser, questionr, RNeo4j, rsconnect, SciencesPo, spAddins, summarytools
ACNE, alphahull, aroma.apd, bedr, Causata, CollapsABEL, demi, dplR, edgar, EEM, eiCompare, evclust, ezknitr, fslr, future.BatchJobs, gdalUtils, hoardeR, LSPFP, mailR, mcparallelDo, MPAgenomics, PopGenReport, PSCBS, qrcode, R.cache, R.devices, ReporteRs, R.filesets, R.huge, R.matlab, R.rsp, rvg, SDMTools, simPATHy, snplist, SpaDES, spm12r, stplanr, TBSSurvival
addinslist, banxicoR, boxoffice, finreportr, gesis, googleformr, gtrendsR, gutenbergr, MazamaSpatialUtils, nhanesA, rslp, rUnemploymentData, scholar, sejmRP, traits, webchem, wikipediatrend
bayesPop, birdring, mapr, spoccutils, virtualspecies, wux
Frames2, popgraph, RRTCS, Sofi, SurvRank
betareg, censReg, clusterSEs, fxregime, gcmr, glmx, glogis, Greg, lfe, MarkowitzR, maxLik, medflex, mlt, multcomp, multiwayvcov, nonnest2, party, pdR, plm, rddtools, ssym, systemfit, termstrc, vcrpart, Zelig
alakazam, aqp, backtestGraphics, bdrift, bdscale, benchmark, brainGraph, choroplethr, clhs, clifro, complmrob, condformat, covmat, ctmm, d3heatmap, DataExplorer, Deducer, DescribeDisplay, DiagrammeR, drc, dtwSat, EasyHTMLReport, EpiBayes, extracat, ez, FAOSTAT, fslr, fSRM, funModeling, gazepath, geneNetBP, GERGM, ggalt, ggfortify, ggmap, ggplot2, ggsci, ggspectra, ggtern, ggthemes, gmwm, GSIF, gwdegree, heatmaply, hierarchicalSets, IPtoCountry, ldatuning, leaflet, linear.tools, mapview, modellingTools, mousetrap, mplot, ncappc, NeuralNetTools, optiRum, OutbreakTools, paleobioDB, pheatmap, plotKML, plotly, primerTree, pwr, qdap, qicharts, quadrupen, quantable, RADanalysis, RAM, rAvis, rbokeh, rcicr, RcmdrPlugin.KMggplot2, RDS, remote, RNewsflow, rnoaa, roahd, SCGLR, SEERaBomb, SeqFeatR, sharpshootR, shazam, SixSigma, sjPlot, spikeSlabGAM, starma, statebins, strvalidator, survminer, svdvis, tcR, TDA, toaster, UpSetR, useful, vetools, vqtl
anacor, arulesViz, asbio, caRpools, cricketr, diffusionMap, FactoMineR, fractal, FrF2, homals, MagneticMap, matrixLaplacian, PharmPow, phytools, pi0, RSDA, shapes, Sim.DiffProc, SOMbrero, specmine, SpectralMap, vegan3d
Actigraphy, gazepath, lefse, NORRRM, raincpc, rainfreq, SDMPlay, shazam, spatialEco, sperich, SSDM, zoon
adegenet, alakazam, aLFQ, AlignStat, apmsWAPP, caRpools, CONDOP, cooccurNet, evobiR, gkmSVM, gquad, megaptera, prozor, SafeQuant, shazam, signalHsmm, sivipm
arulesViz, corrgram, corrr, DeLorean, matie, pergola, qlcVisualize
FindMinIC, intReg, NIPTeR, relations, sdcMicro
CDM, distrMod, FCGR, FrF2, lokern, mcmcplots, mirt, npregfast, pcalg, RADanalysis, rags2ridges, random.polychor.pa, ReliabilityTheory, simsalapar, sirt, TAM, umx, xseq
cape, circlize, diffEq, EpiBayes, Luminescence, marmap, NPCirc, OceanView, plspm, RBPcurve, rmgarch, SSRA, vows
Anthropometry, biplotbootGUI, cncaGUI, LOST, multibiplotGUI, symbolicDA
AdaptGauss, addinslist, adegenet, adespatial, AFM, backtestGraphics, BayesianNetwork, BBEST, blkbox, capm, ChannelAttributionApp, chipPCR, Cite, citr, colourpicker, cosinor, CosmoPhotoz, crawl, CTTShiny, datacheck, ddpcr, detzrcr, distcomp, diveRsity, dpcR, dropR, DVHmetrics, DynNom, eAnalytics, edgebundleR, eechidna, EffectLiteR, EMSaov, evobiR, explor, flexdashboard, flora, FreqProf, G2Sd, gazepath, ggExtra, ggraptR, ggThemeAssist, ggvis, googleAnalyticsR, HH, igraphinshiny, IMP, IncucyteDRC, interAdapt, irtDemo, IRTShiny, lavaan.shiny, learnstats, lightsout, MAVIS, merTools, miniUI, mldr, mlr, mplot, mwaved, NNTbiomarker, npregfast, OpenImageR, pairsD3, plotROC, poppr, pqantimalarials, QCAGUI, questionr, refund.shiny, ReporteRs, rglwidget, rgpui, RLumShiny, rtable, RtutoR, SciencesPo, SensMixed, SHELF, shinyAce, shinybootstrap2, shinyBS, shinydashboard, shinyDND, shinyFiles, ShinyItemAnalysis, shinyjs, shinyRGL, shinythemes, shinyTime, shinytoastr, shinyTree, signalHsmm, simPATHy, soc.ca, SOMbrero, SpaDES, squid, SSDM, StereoMorph, subspaceMOA, swirlify, tableHTML, timeseriesdb, timevis, treemap, treescape, trelliscope, VWPre, wppExplorer
CTTShiny, IRTShiny, lavaan.shiny, MAVIS, ShinyItemAnalysis, swirlify
explor, MAVIS, RtutoR, SensMixed, treescape
BayesianNetwork, eAnalytics, irtDemo, mplot, RtutoR, simPATHy, SSDM
addinslist, AFM, blkbox, colourpicker, ddpcr, eechidna, ggExtra, lightsout, npregfast, RtutoR, shinystan, wppExplorer
AEDForecasting, biosignalEMG, chipPCR, dpcR, erah, erp.easy, IRISMustangMetrics, IRISSeismic, perARMA, psd, TLBC, tuneR
fPortfolio, ldatuning, lpmodeler, LPR, movMF, parma, polmineR, rDEA, relations, RNewsflow, ROI, ROI.plugin.cplex, ROI.plugin.ecos, ROI.plugin.ipop, ROI.plugin.quadprog, ROI.plugin.scs, ROI.plugin.symphony, skmeans, stm, textcat, tm, tm.plugin.dc, toaster, topicmodels, wordcloud
caRpools, DAMisc, DepthProc, funcy, MuViCP, rase, SDD, sirt
bssn, Compositional, fAssets, fMultivar, mateable, mvdalab, SGP, ssmn
btergm, compete, ftsspec, geomnet, ggnetwork, gwdegree, keyplayer, latentnet, netdiffuseR, OutbreakTools, qgraph, statnetWeb, tnam, VBLPCM
DeducerText, inpdfr, lexRankr, NLPutils, quanteda, stmCorrViz, textmineR, tokenizers
BaSTA, georob, meteo, quantspec, rags2ridges, XMRF
adegraphics, adespatial, AFM, akima, AmostraBrasil, aoristic, aqp, BayesX, bfast, biogeo, birdring, BPEC, bsam, btb, camtrapR, capm, CARBayes, CARBayesdata, CARBayesST, chillR, cleangeo, clhs, cruts, csrplus, ctmm, downscale, DSpat, dtwSat, dynatopmodel, EcoGenetics, EEM, EFDR, ei, EMbC, flows, gcmr, gdalUtils, gdistance, gear, GeNetIt, geoaxe, geoBayes, geojsonio, geoknife, geoR, geoRglm, gfcanalysis, graphscan, GSIF, GSODR, gstat, GWLelast, hddtools, helsinki, hydroPSO, hydroTSM, ipdw, kehra, Kernelheaping, kineticF, lakemorpho, landsat8, leaflet, letsR, lgcp, ltsk, magclass, mapr, mapStats, mapview, marmap, MazamaSpatialUtils, MetaLandSim, meteo, mkde, Momocs, monographaR, moveHMM, mptools, mregions, nodiv, OpasnetUtils, OpenStreetMap, opentraj, osmplotr, OSMscale, osrm, oXim, perspectev, pgirmess, plotKML, PopGenReport, popgraph, prettymapr, qlcVisualize, quickmapr, r2d2, rangeMapper, rasterVis, rAvis, rbison, red, redist, repijson, retistruct, rgeos, riverdist, rleafmap, rLiDAR, rmapshaper, RNCEP, rnrfa, RObsDat, rosm, rpostgis, RQGIS, rSPACE, RStoolbox, RSurvey, rWBclimate, SDMPlay, secr, SEHmodel, SensusR, sharpshootR, soilDB, soil.spec, soiltexture, spacetime, SpaDES, spatialEco, SpatialPosition, spatsurv, spbabel, spBayesSurv, spcosa, speciesgeocodeR, sperich, sphet, spoccutils, spsann, spTest, spTimer, SSDM, tigris, tmap, trajectories, tripEstimation, tweet2r, USAboundaries, vegclust, VIM, vmsbase, VTrack, wildlifeDI, wkb, wrspathrow
gstat, meteo, plotKML, RObsDat, trajectories, tweet2r, VTrack
CARBayes, CARBayesST, CollocInfer, earlywarnings, growfunctions, mclcar, mvMORPH, nat.nblast, OptimaRegion, SpATS, splm
baseline, cobs, DDD, DESP, expoRkit, gmum.r, netdiffuseR, nmfgpu4R, pawacc, PResiduals, SwarmSVM
ads, alphahull, dpcR, ecospat, ETAS, hht, highriskzone, intamapInteractive, lgcp, lqr, MetaLandSim, osmplotr, polyCub, qlcVisualize, radiomics, rase, replicatedpp2w, RImageJROI, rLiDAR, smacpod, spatialEco, spatsurv, surveillance, swfscMisc, trip, tweet2r
adegenet, adespatial, agricolae, CARBayes, CARBayesST, GeNetIt, HSAR, INLABMA, mclcar, OasisR, pgirmess, redist, saeRobust, saeSim, smerc, spacom, spatialEco, SpatialEpi, sphet, tmap
alphahull, ExceedanceTools, GEOmap, geoR, GeoXp, kineticF, pgirmess, phonR, PrevMap, RCALI, RFOC, RTOMO, seg, simLife, SpecHelpers, tspmeta, tweet2r
ggpmisc, ifultools, photobiology, sapa, wmtsa
distrDoc, distrEx, distrMod, distrRmetrics, distrSim, distrTeach, distrTEst, RandVar
Bclim, brms, cda, ChainLadder, cplm, dsm, equateIRT, flexCWM, glmBfp, hoa, LogisticDx, mexhaz, mlogit, multimark, mvabund, mvQuad, NetRep, npmlreg, PanelCount, pglm, planar, R2STATS, RVAideMemoire, x.ent
btergm, ergm.ego, ndtv, networkDynamic, statnet, tsna
bcRep, deductive, fuzzyjoin, lintr, PGRdup, qdap, sjmisc, tcR, TSTr
alakazam, assertive.strings, CITAN, curlconverter, dplR, easyformatr, Ecfun, eurostat, eyelinker, fiery, GetTDData, hyphenatr, ie2misc, inpdfr, mscstexta4r, optigrab, PGRdup, placement, plumber, qdapRegex, qlcData, quanteda, randstr, rangeBuilder, rattle, RcmdrPlugin.temis, retrosheet, RndTexExams, roxygen2, RPresto, rprime, rprintf, rslp, searchable, sejmRP, sentimentr, shazam, SpaDES, stplanr, stringr, tidyr, tokenizers, VarfromPDB, wakefield, wand
DDD, diskImageR, diversitree, geiger, GUILDS, pomp
brr, Haplin, NSM3, PHENIX, userfriendlyscience
capm, causaldrf, convey, EffectLiteR, GB2, ICS, rareGE, SemiParBIVProbit, sirt, srvyr, StroupGLMM, SvyNom, tab, tableone, Zelig
addhazard, aftgee, AICcmodavg, AIM, beanz, BGPhazard, binequality, Biograph, c060, cancerGI, CFC, cg, chngpt, cmprskQR, compareGroups, controlTest, coxphf, CP, DStree, DTR, DWreg, DynNom, EGRET, EMA, Epi, epoc, FHtest, fmrs, gamlss, ggRandomForests, glmBfp, greport, gyriq, hdnom, hoa, idem, ilc, intercure, intubate, ipred, ipw, landest, landpred, lodGWAS, LTRCtrees, mboost, Mediana, mets, mice, miCoPTCM, MIICD, mixPHM, mlr, mombf, moonBook, mpr, msm, msmtools, MST, muhaz, MXM, nima, pact, party, partykit, pec, plsRcox, pmml, popEpi, powerSurvEpi, prodlim, pseval, quickReg, rankhazard, RcmdrPlugin.KMggplot2, rem, reportRx, reReg, riskRegression, RItools, robustloggamma, RVFam, sensitivityPStrat, shrink, simexaft, SimHaz, simPH, SIS, smcfcs, SMPracticals, spanr, spatsurv, spBayesSurv, srd, SSRMST, stdReg, Surrogate, SurvCorr, survminer, SvyNom, tab, TBSSurvival, tranSurv, TwoPhaseInd, TwoStepCLogit, WCE, WGCNA, xpose4, Zelig
svHttp, svIDE, svSocket, svTools, svWidgets
cancerGI, ChainLadder, erer, micEconAids, micEconCES, micEconSNQP, sampleSelection
bdvis, brranching, camtrapR, myTAI, originr, RNeXML, rusda, TR8, traits
biplotbootGUI, cncaGUI, dynBiplotGUI, fSRM, HierO, LSPFP, multibiplotGUI, Rcmdr, RcmdrPlugin.KMggplot2, RcmdrPlugin.sos, RcmdrPlugin.temis, rite, rSPACE, stylo, TTAinterfaceTrendAnalysis, TTCA, uHMM
brr, Ecfun, geospt, hwriterPlus, palaeoSig, proportion, RBPcurve, TipDatingBeast
bedr, DBItest, eggCounts, googleCloudStorageR, lintr, ncappc, Phxnlme, rusda, SixSigma, stubthat, swirl, texmexseq, zoon
dse, EvalEst, TScompare, TSdbi, tsfa, TSfame, TSmisc, TSMySQL, TSodbc, TSPostgreSQL, TSsdmx, TSsql, TSSQLite
TSfame, TSmisc, TSodbc, TSPostgreSQL, TSsdmx, TSsql, TSSQLite
blkbox, cellranger, corrr, datastepr, docxtractr, dplyr, easyformatr, feather, getlandsat, ggpmisc, highcharter, mregions, openadds, pangaear, photobiology, photobiologyInOut, pollstR, randNames, rbgm, readr, rgbif, ritis, sjPlot, sjstats, spbabel, spdplyr, spocc, tidyr, wand
bkmr, blkbox, broom, carpenter, cdom, compareDF, corrr, easyformatr, edeaR, eechidna, EFDR, emil, engsoccerdata, etl, eurostat, explor, eyetrackingR, ezsummary, fuzzr, fuzzyjoin, geoparser, ggfortify, ggRandomForests, ggspectra, glycanr, googlesheets, gwdegree, heemod, highcharter, IMP, IncucyteDRC, lexRankr, listless, mason, mixOmics, mosaic, mpoly, mtconnectR, NeuralNetTools, pixiedust, PKNCA, plotly, pmc, qdap, RDML, rfishbase, rgho, RmarineHeatWaves, RNeXML, rnoaa, ropenaq, rpdo, rprev, rtable, shazam, SHELF, sjmisc, sjPlot, statar, SWMPr, textreuse, tidytext, tigger, translateSPSS2R, vcfR, VWPre, wand, wordbankr
gitter, multipanelfigure, OpenImageR, SchemaOnRead, StereoMorph, Thermimage
BLCOP, FatTailsR, GEVStableGarch, iClick, tframePlus
ade4TkGUI, biplotbootGUI, cncaGUI, dynBiplotGUI, FIACH, idendr0, Interatrix, MareyMap, multibiplotGUI, rriskDistributions, uHMM
edgar, fulltext, genderizeR, inpdfr, lexRankr, ngramrr, polmineR, PubMedWordcloud, qdap, rClinicalCodes, RKEA, RTextTools, scientoText, SocialMediaLab, stmCorrViz, TELP, textmineR, textreg, tm.plugin.alceste, tm.plugin.europresse, tm.plugin.factiva, tm.plugin.lexisnexis, tm.plugin.mail, tm.plugin.webmining, topicmodels
BayesCR, CARBayes, CARBayesST, ssmn, StatRank
bkmr, clustMD, copulaedas, EGRET, gemtc, gmnl, hierarchicalDS, marked, parma, PrevMap, r4ss, randstr, rDEA, Rsolnp, SparseFactorAnalysis, stocc, tglm
AID, conting, CryptRndTest, egcm, erer, forecast, lfl, msltrend, partialAR, PCA4TS, PortRisk, SDD, tsDyn, TSmisc
ei, eiCompare, NHMSAR, optimx, ordinal, vcrpart
apt, autovarCore, CommonTrend, egcm, erer, partialAR, termstrc, tsDyn
gutenbergr, HIBPwned, placement, rdomains, rio
AzureML, dataone, datapack, emuR, fiery, pinnacle.API, RMixpanel, RNeXML, rpg, tigris
curlconverter, daff, dagitty, DiagrammeRsvg, DOT, geojsonio, geojsonlint, js, jsonvalidate, lawn, minimist, randomcoloR, rchess, rgbif, rjade, rmapshaper, spocc, uaparserjs
arulesViz, DoE.base, eeptools, gpairs, HH, pcalg, sdcMicroGUI, STEPCAM, tadaatoolbox, VIM
adegenet, adespatial, bcRep, biogeo, cati, cems, DiversityOccupancy, dnc, entropart, evolqg, forams, gdm, GERGM, goeveg, lefse, memgene, netassoc, nodiv, paco, PCPS, pez, PopGenReport, poppr, rich, rioja, RVAideMemoire, shapeR, sharpshootR, soundecology, tnam, tspmeta, zetadiv
bedr, caRpools, PATHChange, RAM, stringgaussnet, TTCA, vmsbase
AICcmodavg, BioPET, cg, Countr, DAMisc, ExomeDepth, fakeR, HiDimMaxStable, ldstatsHD, list, lllcrc, PAFit, ph2bye, poweRlaw, sads, sampleSelection, SemiParBIVProbit, SemiParSampleSel, smcfcs, snowboot, SparseFactorAnalysis, sparsereg, staTools, Zelig, ZeligChoice
Infusion, mptools, platetools, plotly, RcmdrPlugin.BiclustGUI, rwty, SAGA, simmr
cbsodataR, d3Network, dendextend, devtools, ecoengine, flowr, fulltext, represtools, request, rgbif, rplos, rslurm, spocc, swirlify
edgar, inpdfr, Mobilize, msarc, PubMedWordcloud, qdap, quanteda, rbefdata, RNewsflow, SOMbrero, TELP, toaster
bayesDem, bayesLife, bayesPop, bayesTFR, wppExplorer
Dominance, googlePublicData, imageData, msarc, SEERaBomb, table1xls
caRpools, DataClean, G2Sd, lar, ODMconverter, psData, qdap, rpcdsearch, rrepast
abbyyR, archiDART, aRxiv, aws.alexa, belex, BIGDAWG, biomartr, BoolNet, causaleffect, Causata, cdlTools, chillR, clifro, colourlovers, comato, coreNLP, CorrectOverloadedPeaks, creditr, cricketr, DataClean, datamart, dataone, datapack, dataRetrieval, dbhydroR, DDIwR, dplR, dvn, Ecfun, edeaR, edgar, feedeR, FIT, geoknife, gmapsdistance, Gmisc, googlePublicData, graphicsQC, gridSVG, hddtools, HierO, hive, HMDHFDplus, hoardeR, htmltab, icesDatras, icesSAG, IncucyteDRC, inegiR, IRISMustangMetrics, IRISSeismic, letsR, Luminescence, MALDIquantForeign, megaptera, meteoForecast, miniCRAN, mldr, mlxR, MODISTools, mtconnectR, MTurkR, MTurkRGUI, myepisodes, OAIHarvester, OData, ODMconverter, OpenRepGrid, optiRum, osmplotr, PBSmodelling, pdfetch, pinnacle.API, plotKML, PreKnitPostHTMLRender, primerTree, pubmed.mineR, PubMedWordcloud, pvsR, qat, qdap, qdapTools, rAvis, rbefdata, rbhl, rClinicalCodes, rclinicaltrials, RCriteo, rdefra, RDML, rdomains, readMLData, readMzXmlData, RefManageR, rentrez, Reol, retrosheet, reutils, RevEcoR, rfigshare, rfml, RForcecom, RKEEL, rlist, RNeXML, rnoaa, rNOMADS, rpubchem, RQGIS, rsdmx, rsml, rsnps, RStoolbox, rtematres, rusda, Ryacas, Sabermetrics, sejmRP, selectr, semPlot, SetRank, soilDB, solr, solrium, sophisthse, sss, stressr, svIDE, SWMPr, TCGA2STAT, TFX, timetree, tmap, tmod, tm.plugin.europresse, tm.plugin.factiva, tm.plugin.lexisnexis, tm.plugin.webmining, TR8, trackeR, treebase, ukgasapi, ustyc, vegdata, waterData, WaterML, WikiSocio, WMCapacity, ZillowR
addinslist, banxicoR, bold, boxoffice, cdcfluview, cycleRtools, discgolf, docxtractr, ecb, edeaR, europepmc, finreportr, fulltext, gesis, getlandsat, ggiraph, googleformr, googlesheets, mregions, neotoma, nhanesA, oai, OECD, openadds, originr, pangaear, rcrossref, rdnb, rdryad, readODS, ReporteRs, rerddap, rgbif, rgho, rio, rNOMADS, rslp, rversions, rvg, SchemaOnRead, scholar, sejmRP, taxize, traits, W3CMarkupValidator, webchem, wikipediatrend
AICcmodavg, BEQI2, BioGeoBEARS, BrailleR, confidence, Correlplot, CovSelHigh, Crossover, CUFF, DAMisc, descr, dynr, EasyHTMLReport, EMA, hierarchicalDS, inTrees, IsoGene, lfe, lsmeans, MAMA, midrangeMCP, miscset, MplusAutomation, MSBVAR, ncappc, NNTbiomarker, OpasnetUtils, pipe.design, pkgmaker, PopGenReport, qmethod, RecordLinkage, reportRx, reproducer, RItools, robustlmm, SciencesPo, SensMixed, shiny, shinystan, SIMMS, SixSigma, sparkTable, spduration, StableEstim, stacomirtools, StatDA, summarytools, survMisc, userfriendlyscience, x.ent
backtestGraphics, blscrapeR, carx, covmat, creditr, DMwR, dygraphs, dynatopmodel, ecd, ggpmisc, highcharter, hydroGOF, kehra, machina, pdfetch, qrmdata, qrmtools, rmgarch, rnrfa, RObsDat, rugarch, shinystan, spacetime, stressr, tawny, tawny.types, timeseriesdb, TSdist, TSmisc, TTR, vetools
ahp, analogsea, bedr, bookdown, Causata, cbsodataR, citr, config, csvy, datarobot, ecd, htmlwidgets, knitr, liftr, nat, qlcData, rAmCharts, rapport, rfigshare, rio, rlist, rmarkdown, rmcfs, rsconnect, RSQLServer, rticles, swirl, swirlify, validate, yorkr
ACDm, acss, bfast, BigVAR, blscrapeR, carx, changepoint.np, covmat, creditr, DBEST, diskImageR, DMwR, dygraphs, dynatopmodel, ecd, eyetrackingR, FDboost, gazepath, ggpmisc, GSSE, gstat, gtrendsR, gunsales, hddtools, highcharter, hydroPSO, hyfo, iemisc, iki.dataclim, inegiR, kehra, lfl, lfstat, LICORS, Luminescence, manifestoR, mlogit, mptools, msltrend, nparACT, obAnalytics, partialAR, party, pdfetch, PerformanceAnalytics, plm, plotKML, PortRisk, preprocomb, psd, qrmtools, Quandl, quantspec, rasterVis, RmarineHeatWaves, rmgarch, RQuantLib, rugarch, sandwich, scidb, sirad, snht, sophisthse, spacetime, STI, survMisc, syuzhet, tableone, tawny, tawny.types, TED, termstrc, tigerhitteR, timeseriesdb, translateSPSS2R, trib, tripEstimation, TSdist, tseries, TSmisc, TSsql, TTR, vcrpart, Wats, wq
ACEt, beanz, BEDMatrix, bigalgebra, biganalytics, biglasso, bigmemory, bigtabulate, BMRV, Boom, BoomSpikeSlab, bsts, Cyclops, ddalpha, DDRTree, DescTools, dfcomb, dfmta, dfpk, dplyr, dynsurv, eggCounts, EPGLM, FeatureHashing, fts, FunChisq, GERGM, GiRaF, glmmsr, gmum.r, gpuR, hashmap, haven, iptools, jqr, LANDD, lsgl, MBA, MEGENA, MixedDataImpute, mixedMem, msgl, MultiBD, mvnfast, nabor, NetRep, odeintr, OpenMx, PACVB, pcalg, phonics, PReMiuM, purrr, Rblpapi, RcppBDT, RcppMLPACK, RcppParallel, RcppRedis, RcppShark, RcppStreams, readr, rootWishart, rstan, rstanarm, sgd, sglOptim, simmer, SSN, svglite, synchronicity, TDA, textreuse, TransferEntropy, xml2
bigalgebra, biganalytics, biglasso, bigtabulate, sgd
blkergm, ergm.count, ergm.graphlets, ergm.rank, ergm.userterms, tergm
ADMMnet, BacArena, BayesFactor, beanz, BigVAR, blackbox, btf, clere, CorReg, covafillr, Coxnet, cpgen, Cyclops, DDRTree, DetMCD, DetR, dfpk, discretecdAlgorithm, eggCounts, FastGP, FastHCS, FastPCS, FastRCS, fdapace, fdaPDE, FIT, flars, Funclustering, gaston, glmmsr, gpuR, gRain, gRbase, grpSLOPE, hts, ICAOD, icenReg, iprior, ISOpureR, kernDeepStackNet, lme4, MediaK, microclass, mmand, MPTinR, nabor, oapackage, OpenMx, perccal, plac, PReMiuM, ProbitSpatial, Rankcluster, Rclusterpp, RcppNumerical, RNiftyReg, RobustGaSP, rootWishart, rpf, RSNPset, RSpectra, rstan, rstanarm, Rvcg, saturnin, spaMM, sparseHessianFD, sparseLTSEigen, TDA, TMB, tmg, trustOptim, walkr
Cyclops, dbmss, FLSSS, gaston, GERGM, markovchain, microclass, MultiBD, roll, rPref, SpatMCA, SpatPCA, StMoSim, text2vec
CFC, cpgen, dfcomb, dfmta, DNAprofiles, GCPM, JAGUAR, lsgl, matchingMarkets, msgl, NNLM, sglOptim, textmineR, textreuse
beanz, dfpk, eggCounts, OpenMx, rstan, rstanarm
Anthropometry, autoimage, cpca, kyotil, multivator, paleomorph, plyr, RcmdrPlugin.EZR, RcmdrPlugin.IPSUR, RcmdrPlugin.NMBU, RcmdrPlugin.pointG, tableplot
fitdistrplus, GeneralizedHyperbolic, HyperbolicDist, IPSUR, PhaseType, raw
ChemometricsWithR, deepboost, fscaret, mlr, pmml, rattle
biomod2, explor, factoextra, funrar, Guerry, GUniFrac, MiSPU, polysat, RcmdrPlugin.pointG
EcoGenetics, HWxtest, memgene, polysat, vcfR
move, SiMRiv, spacetime, trajectories, trip
agridat, censReg, clubSandwich, glmx, gmnl, LinRegInteractive, lmtest, micEconCES, mlogit, mlt.docreg, partykit, plm, REEMtree, sandwich, sjmisc, sjstats, vcdExtra
agridat, paleofire, RGraphics, Sleuth2, Sleuth3
adegenet, asbio, BayesX, BiodiversityR, DiceEval, dynaTree, EDR, erpR, evd, fBasics, fdasrvf, fMultivar, fractal, gam, kobe, laGP, locfit, oce, ParamHelpers, plgp, portes, quantreg, R2BayesX, rgr, rioja, rpanel, sm, VdgRsm, vegdata
ChemoSpec, extracat, hamlet, kselection, pmml, rattle, REPPlab
EFDR, heplots, MSG, pitchRx, plotKML, RGraphics, ropenaq, surveillance
ade4, aqp, asnipe, data.tree, dcGOR, dendextend, enveomics.R, GLSME, hierfstat, HSAUR, HSAUR2, HSAUR3, igraph, MVA, netdiffuseR, ouch, paco, polysat, rncl, rphast, sand, scrm, speciesgeocodeR, structSSI, subniche, symmoments, vhica
fdapace, IPSUR, Rcmdr, RcmdrPlugin.EZR, UsingR
BayesFactor, brms, fscaret, medflex, optmatch, rstanarm, sjmisc, sjPlot, sjstats, subsemble, SuperLearner
nutshell, nutshell.audioscrobbler, pmml, rattle, rfml
dagitty, exams, matrixStats, plumber, repijson, R.rsp
broom, copula, primer, R2admb, SEERaBomb
bio3d, filematrix, matpow, mlDNA, nat.nblast, NetRep, NMF, polmineR, PopGenome, rsgcc, sgd
dcemriS4, devtools, GGIR, hashFunction, rattle, XML
BNDataGenerator, BTR, ParallelPC, rbmn, sparsebnUtils
abd, AER, aod, asbio, bayesboot, broom, CaDENCE, car, CARBayes, ChemometricsWithR, cond, crossReg, DAAG, doRedis, EffectsRelBaseline, ElemStatLearn, emplik, EnvStats, GEVcdn, gMCP, Greg, GSIF, gsubfn, harvestr, hoa, HSAUR, HSAUR2, HSAUR3, investr, IPSUR, ipw, jaatha, LambertW, lme4, logmult, marg, matrixpls, meboot, mirt, mistat, nlreg, npsm, optmatch, proftools, R2HTML, rms, robustbase, semGOF, semPLS, semTools, simTool, Wats
eechidna, GGally, ggsn, macleish, plotly, spbabel
bcrm, BTSPAS, dclone, MethComp, R2WinBUGS
aroma.core, ARTool, corclass, corrplot, dplR, ggmcmc, R2SWF, R.devices, repr, shiny, trelliscope
apt, gWidgets2RGtk2, mlDNA, ProgGUIinR, rattle, retistruct, Rz
abd, agridat, betareg, bglm, BIFIEsurvey, BiodiversityR, bnormnlr, clubSandwich, codingMatrices, compareGroups, coreSim, ctqr, datarobot, Ecdat, Ecfun, effects, fastR, fscaret, gmm, gmnl, gmum.r, GoodmanKruskal, HH, HistData, lmtest, lsmeans, McSpatial, meboot, mistat, mlogit, Morpho, multcomp, mvMORPH, NPC, pedometrics, perturb, pglm, polywog, pscl, R2MLwiN, Rchoice, RcmdrPlugin.EZR, RcmdrPlugin.IPSUR, RcmdrPlugin.pointG, rddtools, REdaS, sand, sandwich, SenSrivastava, sjPlot, sla, Sleuth2, Sleuth3, SMIR, strucchange, tableplot, vcdExtra, WRS2
AppliedPredictiveModeling, biomod2, Cubist, data.table, deepboost, discSurv, doParallel, doSNOW, emil, gmum.r, GSIF, Infusion, kernDeepStackNet, lulcc, mlr, NeuralNetTools, opera, subsemble, SuperLearner
caretEnsemble, fscaret, paleofire, roughrf, taRifx
FNN, gaselect, PLSbiplot1, plsRglm, rknn, soil.spec
FinTS, gsubfn, highfrequency, Hmisc, polmineR, xts, zoo
archdata, bcpa, move, picante, RGraphics
boostr, catdata, ChemometricsWithR, ElemStatLearn, frbs, FRESA.CAD, fscaret, hmeasure, mlr, RoughSets, soil.spec, SPreFuGED, subsemble, SuperLearner, TunePareto
HSAR, mapmisc, McSpatial, rworldmap, tabplot