Functions to simulate Poisson or Normally distributed responses relative to
a baseline and compute achieved significance level and powers for tests on the
simulated responses.
Kappa, ICC, Cronbach alpha, screeplot, mtmm
A general purpose toolbox for personality, psychometrics and experimental psychology.   Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using  factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multi-levels include within and between group statistics, including correlations and factor analysis.   Functions for simulating particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling.  Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometrics as well as publications in personality research. For more information, see the personality-project.org/r webpage.
Contains functions useful for correlation theory,
meta-analysis (validity-generalization), reliability, item
analysis, inter-rater reliability, and classical utility
Psychometric mixture models based on 'flexmix' infrastructure. At the moment Rasch mixture models
with different parameterizations of the score distribution (saturated vs. mean/variance specification)
and Bradley-Terry mixture models are implemented. Both mixture models can be estimated with or without
concomitant variables. See vignette('raschmix', package = 'psychomix') for details on the Rasch mixture
models.
Infrastructure for psychometric modeling such as data classes
(for item response data and paired comparisons), basic model fitting
functions (for Bradley-Terry, Rasch, partial credit, rating scale,
multinomial processing tree models), extractor functions for different types
of parameters (item, person, threshold, discrimination), unified inference
and visualizations, and various datasets for illustration. Intended as a
common lightweight and efficient toolbox for psychometric modeling and a
common building block for fitting psychometric mixture models in package
"psychomix" and psychometric tree models in package "psychotree".
Recursive partitioning based on psychometric models,
employing the general MOB algorithm (from package partykit) to obtain
Bradley-Terry trees, Rasch trees, rating scale and partial credit trees, and
MPT trees.
An assortment of functions that could be useful in analyzing data from psychophysical experiments. It includes functions for calculating d' from several different experimental designs, links for m-alternative forced-choice (mafc) data to be used with the binomial family in glm (and possibly other contexts) and self-Start functions for estimating gamma values for CRT screen calibrations.
Psytabs produces well-formatted tables in .rtf or .html,
which largely conform to "psychological style".
Implements (cumulative) prospect theory and other
theories of risky decision making. A practically unlimited number of
choices can be specified. The package allows for different probability
weighting functions and utility functions to be specified, as well as their
parameters. Other features include the ability to plot individual
probability weighting curves and families of these curves, as well as
individual utility function curves. Single-stage decision trees can be
drawn. The probability simplex can also be drawn. Certainty equivalents and
risk premiums can be plotted. Theoretical predictions for different risky
decision making theories can be compared against each other and empirical
data.
A multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions is also available. The package includes also some other multiway methods: PCAn (Tucker-n) and PARAFAC/CANDECOMP with these extensions.
A tool to draw inference in personalized medicine regimes
Function 'pip3d' tests whether a point in 3D space is
within, exactly on, or outside an enclosed surface defined by a triangular mesh.
Function 'pip2d' tests whether a point in 2D space is within, exactly on, or outside a polygon.
Fits and analyses time dependent marked point process models with an emphasis on earthquake modelling. For a more detailed introduction to the package, see the topic "PtProcess". A list of recent changes can be found in the topic "Change Log".
Parametric Time Warping aligns patterns, i.e. it aims to
put corresponding features at the same locations. The algorithm
searches for an optimal polynomial describing the warping. It
is possible to align one sample to a reference, several samples
to the same reference, or several samples to several
references. One can choose between calculating individual
warpings, or one global warping for a set of samples and one
reference. Two optimization criteria are implemented: RMS (Root
Mean Square error) and WCC (Weighted Cross Correlation). Both
warping of peak profiles and of peak lists are supported.
Text mining of PubMed Abstracts (text and XML) from http://www.ncbi.nlm.nih.gov/pubmed.
create a word cloud using the abstract of publications from PubMed
R interface to pullword service for Natural Language Processing
in Chinese. It enables users to extract valuable words from text by deep learning models.
For more details please visit the official site (in Chinese) http://pullword.com/.
R package to query and get data out of a Pumilio sound archive system (http://ljvillanueva.github.io/pumilio/).
PurBayes is an MCMC-based algorithm that uses
next-generation sequencing data to estimate tumor purity and
clonality for paired tumor-normal data.
A package for sending push notifications to mobile devices (iOS and
Android) and the desktop using Pushover
Likelihood based population viability analysis in the
presence of observation error and missing data.
The package can be used to fit, compare, predict,
and forecast various growth model types using data cloning.
The calculation of p-variation of the finite sample data
Computes nonparametric p-values for the potential class
memberships of new observations as well as cross-validated
p-values for the training data. The p-values are based on
permutation tests applied to an estimated Bayesian likelihood
ratio, using a plug-in statistic for the Gaussian model, 'k
nearest neighbors', 'weighted nearest neighbors' or
'penalized logistic regression'.
Additionally, it provides graphical displays and quantitative
analyses of the p-values.
An implementation of multiscale bootstrap resampling for
assessing the uncertainty in hierarchical cluster analysis.
It provides AU (approximately unbiased) p-value as well as
BP (bootstrap probability) value for each cluster in a dendrogram.
Computes rank correlations and their p-values with various options for tied ranks.
The pvsR package facilitates data retrieval from Project
Vote Smart's rich online data base on US politics via the Project Vote
Smart application programming interface (PVS API). The functions in this
package cover most PVS API classes and methods and return the
requested data in a data frame.
This R package contains open source implementations
of several p-value weighting methods, including Spjotvoll, exponential
and Bayes weights. These are methods for improving power in multiple testing
via the use of prior information.
Power analysis functions along the lines of Cohen (1988).
Tools the evaluation of interim analysis plans for sequentially
monitored trials on a survival endpoint; tools to construct efficacy and
futility boundaries, for deriving power of a sequential design at a specified
alternative, template for evaluating the performance of candidate plans at a
set of time varying alternatives.
The Penn World Table provides purchasing power parity and
national income accounts converted to international prices for
189 countries for some or all of the years 1950-2010.
The Penn World Table 8.x provides information on relative levels of
income, output, inputs, and productivity for 167 countries
between 1950 and 2011.
The pxR package provides a set of functions for reading and writing PC-Axis files, used by different statistical organizations around the globe for data dissemination.
Generic interface for the PX-Web/PC-Axis API. The PX-Web/PC-Axis
API is used by organizations such as Statistics Sweden and Statistics
Finland to disseminate data. The R package can interact with all
PX-Web/PC-Axis APIs to fetch information about the data hierarchy, extract
metadata and extract and parse statistics to R data.frame format. PX-Web is
a solution to disseminate PC-Axis data files in dynamic tables on the web.
Since 2013 PX-Web contains an API to disseminate PC-Axis files.
Given a SpatialPolygonsDataFrame and a set of populations for each polygon,
compute a population density estimate based on Tobler's pycnophylactic interpolation
algorithm. The result is a SpatialGridDataFrame.
Drawing population pyramid using (1) data.frame or (2) vectors.
The former is named as pyramid() and the latter pyramids(), as wrapper
function of pyramid().  pyramidf() is the function to draw population
pyramid within the specified frame.
String operations the Python way - a package for those of us who miss Python's string methods while we're working in R.
This package delivers some functions to provide a scientific quality assurance of meteorological data.
An extensive set of functions to perform Qualitative Comparative Analysis:
crisp sets (csQCA), temporal (tQCA), multi-value (mvQCA) and fuzzy sets (fsQCA).
QCA is a methodology that bridges the qualitative and quantitative divide
in social science research. It uses a boolean algorithm that results in a minimal
causal combination which explains a given phenomenon.
A set of functions for Qualitative Comparative Analysis (QCA). It can be used for various types of QCA (csQCA, mvQCA fsQCA and crip set TQCA  and time-serious QCA). It has methods for simplifying assumption, contradictory simplifying assumption.
Implements tests for Type I error in Qualitative Comparative Analysis (QCA) that take into account the multiple hypothesis tests inherent in the procedure. Tests can be carried out on three variants of QCA: crisp-set QCA (csQCA), multi-value QCA (mvQCA) and fuzzy-set QCA (fsQCA). For fsQCA, the fsQCApermTest() command implements a permutation test that provides 95% confidence intervals for the number of counterexamples and degree of consistency, respectively. The distributions of permuted values can be plotted against the observed values. For csQCA and mvQCA, simple binomial tests are implemented in csQCAbinTest() and mvQCAbinTest(), respectively.
QCAGUI is a graphical user interface (GUI) for the QCA
package, derived from R Commander.  Because QCA has little to
do with statistics, the menus from Rcmdr were stripped down to
the very basics.  In crisp sets QCA, data is binary therefore
it is fairly decent to treat it as categorical (1 - presence; 0
- absence).  In order to ease the primary analysis (e.g. tables
of frequencies) and the creation of basic graphs, this package
activates some menus that are not available in Rcmdr but for
factors. Users should be aware, however, that QCAGUI is not a
package for statistics; Rcmdr is better suited for this
purpose.
Helper functions for Qualitative Comparative Analysis: evaluate and plot Boolean formulae on fuzzy set score data, apply Boolean operations, compute consistency and coverage measures
Shewhart quality control charts for continuous, attribute and count data. Cusum and EWMA charts. Operating characteristic curves. Process capability analysis. Pareto chart and cause-and-effect chart. Multivariate control charts.
Tools for (automated and manual) quality control of
the results of Genome Wide Association Studies
Robust estimation of Gaussian mixture models fitted by modified EM algorithm, robust clustering and classification.
This package allows to generate Shewhart-type charts and to obtain
numerical results of interest to the quality control of a process
(involving  continuous, attribute or count data).
This package provides basic functionality for univariable and multivariable
quality control analysis, including: xbar, xbar-one, S, R, ewna, cusum,
mewna, mcusum  and T2 charts.
Automates many of the tasks associated with quantitative
discourse analysis of transcripts containing discourse
including frequency counts of sentence types, words, sentences,
turns of talk, syllables and other assorted analysis tasks. The
package provides parsing tools for preparing transcript data.
Many functions enable the user to aggregate data by any number
of grouping variables, providing analysis and seamless
integration with other R packages that undertake higher level
analysis and visualization of text.  This affords the user a
more efficient and targeted analysis.  'qdap' is designed for
transcript analysis, however, many functions are applicable to
other areas of Text Mining/Natural Language Processing.
A collection of dictionaries and word lists for use with
the 'qdap' package.
A collection of regular expression tools associated with
the 'qdap' package that may be useful outside of the context of
discourse analysis. Tools include
removal/extraction/replacement of abbreviations, dates, dollar
amounts, email addresses, hash tags, numbers, percentages,
citations, person tags, phone numbers, times, and zip codes.
A collection of tools associated with the qdap package that may be
useful outside of the context of text analysis.
This package provides different specifications of a Quadrilateral
Dissimilarity Model which can be used to fit same-different judgments
in order to get a predicted matrix that satisfies regular minimality
[Colonius & Dzhafarov, 2006, Measurement and representations of
sensations, Erlbaum]. From such a matrix, Fechnerian distances can be
computed.
Option pricing (financial derivatives) techniques mainly following textbook 'Options, Futures and Other Derivatives', 9ed by John C.Hull, 2014. Prentice Hall. Implementations are via binomial tree option model (BOPM), Black-Scholes model, Monte Carlo simulations, etc.
This package is a result of Quantitative Financial Risk Management course (STAT 449 and STAT 649) at Rice University, Houston, TX, USA, taught by Oleg Melnikov, statistics PhD student, as of Spring 2015.
The qgraph package can be used to visualize data as networks as well as provides an interface for visualizing weighted graphical models.
Two linear mixed model approaches: REML(restricted maximum likelihood) and MINQUE (minimum norm quadratic unbiased estimation) approaches and several resampling techniques are integrated for various quantitative genetics analyses. With these two types of approaches, various unbalanced data structures, missing data, and any irregular genetic  mating designs can be analyzed and statistically tested. This package also offers fast computations for many large data sets. Other functions will be added to this R tool in the future.
Functions for making run charts and  basic Shewhart control
charts for measure and count data.
The main function, qic(), creates run and control charts and has a
simple interface with a rich set of options to control data analysis
and plotting, including options for automatic data aggregation by
subgroups, easy analysis of before-and-after data, exclusion of one
or more data points from analysis, and splitting charts into
sequential time periods.
Missing values and empty subgroups are handled gracefully.
Open QIIME output files in R, compute statistics, and
create plots from the data.
Extension of the functionality of the Matrix package for using sparse matrices. Some of the functions are very general, while other are highly specific for special data format as used for quantitative language comparison (QLC).
Functions to implement Q-learning for estimating optimal
dynamic treatment regimes from two stage sequentially
randomized trials, and to perform inference via m-out-of-n
bootstrap for parameters indexing the optimal regime.
Empirical adjustment of the distribution of variables originating from (regional) climate model simulations using quantile mapping.
Analysis of Q methodology, used to identify distinct perspectives existing within a group. This methodology is used across social, health and environmental sciences to understand diversity of attitudes, discourses, or decision-making styles (for more information, see http://qmethod.org).
A single function runs the full analysis. Each step can be run separately using the corresponding functions: for automatic flagging of Q-sorts (manual flagging is optional), for statement scores, for distinguishing and consensus statements, and for general characteristics of the factors.
Additional functions are available to import and export data, to print and plot, to import raw data from individual *.CSV files, and to make printable cards.
The package uses principal components and it allows manual or automatic flagging, a number of mathematical methods for rotation, and a number of correlation coefficients for the initial correlation matrix.
See further details in the package documentation, and in the web pages below, which include a cookbook, guidelines for more advanced analysis (how to perform manual flagging or change the sign of factors), data management, and a beta graphical user interface for online and offline use.
Basic functions for building parsers, with an application to PC-AXIS format files.
To generate the scores of the EORTC QLQ-C30 questionnaire and supplementary modules and to determine the time to health-related quality of life score deterioration in longitudinal analysis.
Model fitting, optimal model selection and calculation of various features that are essential in the analysis of quantitative real-time polymerase chain reaction (qPCR).
use 2^ddCT methods calculate the relative gene expression,
data file can be export from bio-rad qpcr machine, the results
can be plot with errorbar. ver 1.1 add GroupPlot function, can
plot all the groups once.
Provides the function qqtest which incorporates uncertainty in its
qqplot display(s) so that the user might have a better sense of the
evidence against the specified distributional hypothesis.  qqtest draws a
quantile quantile plot for visually assessing whether the data come from a
test distribution that has been defined in one of many ways.  The vertical
axis plots the data quantiles, the horizontal those of a test distribution.
The default behaviour generates 1000 samples from the test distribution and
overlays the plot with shaded pointwise interval estimates for the ordered
quantiles from the test distribution.  A small number of independently
generated exemplar quantile plots can also be overlaid.  Both the interval
estimates and the exemplars provide different comparative information to
assess the evidence provided by the qqplot for or against the hypothesis
that the data come from the test distribution (default is normal or
gaussian).  Finally, a visual test of significance (a lineup plot) can also
be displayed to test the null hypothesis that the data come from the test
distribution.
Tools that create D3 JavaScript force directed graph from R. D3 JavaScript was created by Michael Bostock. See http://d3js.org/ and, more specifically for Force Directed Graph https://github.com/mbostock/d3/wiki/Force-Layout.
The qrfactor package simultaneously runs both Q and R  mode factor analyses. The package contains only one function called qrfactor() that can perform PCA, R-mode Factor Analysis, Q-mode Factor Analysis, Simultaneous R- and Q-mode Factor Analysis, Principal Coordinate Analysis, as wells as Multidimensional Scaling  (MDS). Loadings and scores can easily be computed from the  simulation.The plot.qrfactor() function offers several annotated  biplots for all possible combinations of eigenvectors, loadings, and scores. Input data includes shapefiles, tables and dataframe
Joint estimation of quantile specific intercept and slope parameters in a linear regression setting.
Quantile regression (QR) for Linear
Mixed-Effects Models via the asymmetric Laplace distribution (ALD).
It uses the Stochastic Approximation of the EM (SAEM) algorithm for
deriving exact maximum likelihood estimates and full inference results
for the fixed-effects and variance components.
It also provides graphical summaries for assessing the algorithm
convergence and fitting results.
This package is designed to accompany the book
Quantitative Risk Management: Concepts, Techniques and Tools by
Alexander J. McNeil, Rudiger Frey, and Paul Embrechts.
Functions and data sets for reproducing selected results from
the book "Quantitative Risk Management: Concepts, Techniques and Tools".
Furthermore, new developments and auxiliary functions for Quantitative
Risk Management practice.
Functionality for generating (randomized) quasi-random numbers in
high dimensions.
Quantile regression (QR) for Nonlinear
Mixed-Effects Models via the asymmetric Laplace distribution (ALD).
It uses the Stochastic Approximation of the EM (SAEM) algorithm for
deriving exact maximum likelihood estimates and full inference results
for the fixed-effects and variance components.
It also provides graphical summaries for assessing the algorithm
convergence and fitting results.
Fit a quantile regression neural network with optional
left censoring using a variant of the finite smoothing
algorithm.
Molecular descriptors and outcomes for several public domain data sets
Dynamic bindings to the Qt library for calling Qt
methods and extending Qt classes from R. Other packages build upon 'qtbase'
to provide special-purpose high-level interfaces to specific parts of Qt.
Provides several methods for computing the Quantile Treatment Effect (QTE) and Quantile Treatment Effect on the Treated (QTET).  The main cases covered are (i) Treatment is randomly assigned, (ii) Treatment is as good as randomly assigned after conditioning on some covariates (also called conditional independence or selection on observables), (iii) Identification is based on a Difference in Differences assumption (several varieties are available in the package).
Analysis of experimental crosses to identify genes
(called quantitative trait loci, QTLs) contributing to variation in
quantitative traits.
Datasets for the book, A Guide to QTL Mapping with R/qtl
Functions to infer co-mapping trait hotspots and causal models
This software provides tools for joint analysis of
multiple traits in a backcross (BC) or recombinant inbred lines
(RIL) population. It can be used to select an optimal subset of
traits for multiple-trait mapping, analyze multiple traits via
the SURE model, which can associate different QTL with
different traits, and perform multiple-trait composite
multiple-interval mapping.
Functions to Simultaneously Infer Causal Graphs and Genetic Architecture
This software provides tools for quantitative trait mapping in populations such as advanced intercross lines where relatedness among individuals should not be ignored. It can estimate background genetic variance components, impute missing genotypes, simulate genotypes, perform a genome scan for putative quantitative trait loci (QTL), and plot mapping results. It also has functions to calculate identity coefficients from pedigrees, especially suitable for pedigrees that consist of a large number of generations, or estimate identity coefficients from genotypic data in certain circumstances.
Low-level interface to functionality in Qt for efficiently
drawing dynamic graphics and handling basic user input.
Quantitative Analysis of Complex Networks. This package offers a set of topological network measures to analyze complex Networks structurally.
This package gives you the exact first four permutation moments for the most commonly used quadratic form statistics, which need not be positive definite. The extension of this work to quadratic forms greatly expands the utility of density approximations for these problems, including for high-dimensional applications, where the statistics must be extreme in order to exceed stringent testing thresholds. Approximate p-values are obtained by matching the exact moments to the Pearson family of distributions using the PearsonDS package.
This package contains routines and documentation for
solving quadratic programming problems.
This package fits classical sparse regression models with
efficient active set algorithms by solving quadratic problems. Also
provides a few methods for model selection purpose (cross-validation,
stability selection).
Exact one-sided p-values and confidence intervals for an outcome variable defined on an interval measurement scale with only qualitative and ordinal information available.
Used for testing for qualitative interactions between
treatment effects and patient subgroups. Here the term treatment effect
means a comparison result of two treatments within each patient subgroup.
Models included in this package are Gaussian, binomial and Cox models.
Methods included here are interval based graphical approach and Gail Simon
LRT.
This Package contains methods associated with the Define,
Measure, Analyze, Improve and Control (i.e. DMAIC) cycle of the
Six Sigma Quality Management methodology.It covers distribution
fitting, normal and non-normal process capability indices,
techniques for Measurement Systems Analysis especially gage
capability indices and Gage Repeatability (i.e Gage RR) and
Reproducibility studies, factorial and fractional factorial
designs as well as response surface methods including the use
of desirability functions. Improvement via Six Sigma is project
based strategy that covers 5 phases: Define - Pareto Chart;
Measure - Probability and Quantile-Quantile Plots, Process
Capability Indices for various distributions and Gage RR
Analyze i.e. Pareto Chart, Multi-Vari Chart, Dot Plot; Improve
- Full and fractional factorial, response surface and mixture
designs as well as the desirability approach for simultaneous
optimization of more than one response variable. Normal, Pareto
and Lenth Plot of effects as well as Interaction Plots; Control
- Quality Control Charts can be found in the qcc package. The
focus is on teaching the statistical methodology used in the
Quality Sciences.
Qualitative methods for the validation of models.
Implements indices of qualitative variation proposed by Wilcox (1973).
Functions for interacting directly with the Quandl API to offer data
in a number of formats usable in R, as well as the ability to search.
Methods which streamline the descriptive analysis of quantitative matrices.
Statistical evaluation of calibration curves by different
regression techniques: ordinary, weighted, robust (up to 4th
order polynomial).  Log-log and Box-Cox transform, estimation
of optimal power and weighting scheme. Tests for
heteroscedascity and normality of residuals. Different kinds of
plots commonly used in illustrating calibrations. Easy "inverse
prediction" of concentration by given responses and statistical
evaluation of results (comparison of precision and accuracy by
common tests).
A fast, flexible toolset for for the management, processing, and
quantitative analysis of textual data in R.
This package provides different functions for quantifying qualitative survey data. It supports the Carlson-Parkin method, the regression approach and the balance approach.
Estimation of conditional quantiles using optimal quantization.
Construction of an optimal grid of N quantizers, estimation of conditional
quantiles and data driven selection of the size N of the grid. Graphical
illustrations for the selection of N and of resulting estimated curves or
surfaces when the dimension of the covariate is one or two.
Specify, build, trade, and analyse quantitative financial trading strategies.
Contains functions useful for data screening, testing
moderation, mediation and estimating power.
Estimation and inference methods for models of conditional quantiles:
Linear and nonlinear parametric and non-parametric (total variation penalized) models
for conditional quantiles of a univariate response and several methods for handling
censored survival data.  Portfolio selection methods based on expected shortfall
risk are also included.
Quantile Regression Forests is a tree-based ensemble
method for estimation of conditional quantiles. It is
particularly well suited for high-dimensional data. Predictor
variables of mixed classes can be handled. The package is
dependent on the package randomForests, written by Andy Liaw.
Fits non-crossing regression quantiles as a function of linear covariates and a smooth terms via B-splines with difference penalties.
Methods to determine, smooth and plot quantile (i. e., Laplace or
copula) periodograms for univariate time series.
Using HTS data, clusters mutations in order to recreate putative clones from the data provided. It requires genotype at the location of the variant as well as the depth of coverage and number of reads supporting the mutation. Additional information may be provided, such as the contamination in the tumor sample. This package also provides a function QuantumCat() which simulates data obtained from tumor sequencing.
Identify differentially expressed genes in RNA-seq count data using quasi-Poisson or quasi-negative binomial models with 'QL', 'QLShrink' and 'QLSpline' methods (Lund, Nettleton, McCarthy, and Smyth, 2012).
Set of functions to make the processing and analysis of
surveys easier : interactive shiny apps for data recoding, contingency
tables, dataset metadata handling, and several convenience functions.
It provides versatile tools for analysis of birth and death based Markovian Queueing Models
and Single and Multiclass Product-Form Queueing Networks.
It implements M/M/1, M/M/c, M/M/Infinite, M/M/1/K, M/M/c/K, M/M/c/c, M/M/1/K/K, M/M/c/K/K, M/M/c/K/m, M/M/Infinite/K/K,
Multiple Channel Open Jackson Networks, Multiple Channel Closed Jackson Networks,
Single Channel Multiple Class Open Networks, Single Channel Multiple Class Closed Networks
and Single Channel Multiple Class Mixed Networks.
Also it provides a B-Erlang, C-Erlang and Engset calculators.
This work is dedicated to the memory of D. Sixto Rios Insua.
Use Newton's method and coordinate descent to solve the
regularized inverse covariance matrix estimation problem.
Please refer to: Sparse Inverse Covariance Matrix Estimation
Using Quadratic Approximation, Cho-Jui Hsieh, Matyas A. Sustik,
Inderjit S. Dhillon, Pradeep Ravikumar, Advances in Neural
Information Processing Systems 24, 2011, p. 2330--2338.
Quickly fits and plots psychometric functions (normal, logistic, Weibull or any or any function defined by the user) for multiple groups.
Grows a qualitative interaction tree. Quint is a tool for subgroup analysis, suitable for data from a two-arm randomized controlled trial.
Gene banks increasingly use molecular markers for routine
characterization of plant collections and farmer managed diversity. The
gene bank of the International Potato Center presently uses a
micro-satellite marker kit to produce molecular profiles for potato
accessions. We have been searching for a compact graphical representation
that shows both molecular diversity and accession characteristics - thus
permitting biologists and collection curators to have a simple way to
interpret molecular data. Inspired by the ancient Andean data recording
system we devised a graph that allows for standardized representation while
leaving room for updates of the marker kit and the collection of
accessions. The graph has been used in several catalogs of potatoes.
Functions to compute confidence statistics
for ordering population quantiles.
For a given data matrix A and cluster centers/prototypes collected in the matrix P, the functions described here select a subset of statistic variables Q that mostly explains/justifies P as prototypes. The functions are useful to reduce the data dimension for classification and to discard masking variables for clustering.
Functions to compute quasi variances and associated measures of approximation error
A collection of (wrapper) functions the creator found useful for
quickly placing data summaries and formatted regression results into .Rnw or
.Rmd files.  Functions for generating commonly used graphics, such as receiver
operating curves or Bland-Altman plots, are also provided by 'qwraps2'.
'qwraps2' is a updated version of a package 'qwraps'.  The original version
'qwraps' was never submitted to CRAN but can be found at
https://github.com/dewittpe/qwraps.  The implementation and limited scope of the
functions within 'qwraps2' (https://github.com/dewittpe/qwraps2) is fundamentally
different from 'qwraps'.
QZ package provides generalized eigenvalues and QZ
decomposition (generalized Schur form) for an N-by-N
non-symmetric matrix A or paired matrices (A,B) with
eigenvalues reordering mechanism. The package is mainly based
complex*16 and double precision of LAPACK library (version
3.4.2.)
Estimation of reproduction numbers for disease outbreak, based on
incidence data. The R0 package implements several documented methods. It is
therefore possible to compare estimations according to the methods used.
Depending on the methods requested by user, basic reproduction number
(commonly denoted as R0) or real-time reproduction number (referred to as
R(t)) is computed, along with a 95% Confidence Interval. Plotting outputs
will give different graphs depending on the methods requested : basic
reproductive number estimations will only show the epidemic curve
(collected data) and an adjusted model, whereas real-time methods will also
show the R(t) variations throughout the outbreak time period. Sensitivity
analysis tools are also provided, and allow for investigating effects of
varying Generation Time distribution or time window on estimates.
Utilities for sparse signal recovery suitable for compressed sensing. L1, L2 and TV penalties, DFT basis matrix, simple sparse signal generator, mutual cumulative coherence between two matrices and examples, Lp complex norm, scaling back regression coefficients.
A series of functions to call AD Model Builder (i.e.,
compile and run models) from within R, read the results back
into R as 'admb' objects, and provide standard accessors (i.e.
coef(), vcov(), etc.)
An R interface to estimate structured additive regression (STAR) models with BayesX.
R2Cuba implements four general-purpose multidimensional
integration algorithms: Vegas, Suave, Divonne and Cuhre
This package provides generic functions to analyze the distribution
of two continuous variables: 'conf2d' to calculate a smooth empirical
confidence region, and 'freq2d' to calculate a frequency distribution.
2dRUE is a methodology to make a diagnostic of land
condition in a large territory during a given time period. The
following projects have funded this package: DeSurvey IP (EC
FP6 Integrated Project contract No. 003950), DesertWatch (ESA
DUE contract No. 18487/04/I-LG) and MesoTopos (Junta de
Andalucia PE ref. RNM-4023).
Converting R CRAN outputs into Google Earth.
Wrapper functions for GUESS, a GPU-enabled sparse Bayesian variable
selection method for linear regression based analysis of possibly
multivariate/correlated outcomes.
Includes HTML function and methods to write in an HTML
file. Thus, making HTML reports is easy. Includes a function
that allows redirection on the fly, which appears to be very
useful for teaching purpose, as the student can keep a copy of
the produced output to keep all that he did during the course.
Package comes with a vignette describing how to write HTML
reports for statistical analysis. Finally, a driver for Sweave
allows to parse HTML flat files containing R code and to
automatically write the corresponding outputs (tables and
graphs).
Providing wrapper functions to implement Bayesian analysis in JAGS.  Some major features include monitoring convergence of a MCMC model using Rubin and Gelman Rhat statistics, automatically running a MCMC model till it converges, and implementing parallel processing of a MCMC model for multiple chains.
generate univariate and bivariate analyses in LaTeX or
HTML formats
An R command interface to the 'MLwiN' multilevel
modelling software package.
Using this package,
it is possible to call a BUGS model, summarize inferences and
convergence in a table and graph, and save the simulations in arrays for easy access
in R.
R2PPT provides a simple set of wrappers to easily use rcom
or RDCOMClient for generating Microsoft PowerPoint
presentations.
R2STATS is a gWidgetsRGtk2 GUI for fitting and comparing GLM or GLMM (based on Douglas Bates' lme4 package) in R. It is designed to make comparisons between numerous models easy, both numerically and graphically, which may be useful for teaching. Relevant plots are automatically produced for each model family. R2STATS is *not* a generic graphical interface for R, but a GUI for statistical modelling in a model comparison approach.
r2stl, R package for visualizing data using a 3D printer
Package r2stl converts R data to STL (stereolithography) files
that can be used to feed a 3-dimensional printer.  The
3-dimensional output from an R function can be materialized
into a solid surface in a plastic material, therefore allowing
more detailed examination. There are many possible uses for
this new R tool, such as to examine mathematical expressions
with very irregular shapes, to aid teaching people with
impaired vision, to create raised relief maps from digital
elevation maps (DEMs), to bridge the gap between mathematical
tools and rapid prototyping, and many more.  Ian Walker created
the function "r2stl" and Jose' Gama assembled the package.
Using the Ming library
(http://www.libming.org/) to create Flash animations.
Users can either use the SWF device swf() to generate SWF file
directly through plotting functions like plot() and lines(),
or convert images of other formats (SVG, PNG, JPEG) into SWF.
This package uses either the statconnDCOM server (via the
rcom package) or the RDCOMClient to communicate with MS-Word
via the COM interface.
Invoke a 'BUGS' model in 'OpenBUGS' or 'WinBUGS', a class "bugs" for 'BUGS'
results and functions to work with that class.
Function write.model() allows a 'BUGS' model file to be written.
The class and auxiliary functions could be used with other MCMC programs, including 'JAGS'.
This is a collection of useful functions and data for
Stats 330
CDISC Dataset-XML and Define-XML are used as file format for clinical trial data and metadata respectively. This functions supports reading both Dataset-XML and Define-XML.
Provides a collection of functions for basic
database and document management operations such as add, get, list or
delete. Every cdbFunction() gets and returns a list() containing the
connection setup.
Such a list (in the documentation mostly called cdb) can be generated by
cdb <- cdbIni(). Then, the list cdb provides some functions respectively
functionality e.g cdb$baseUrl() or cdb$getDocRev().
This package provides an R interface with 2-part 4dfp MRI images
(.4dfp.ifh and .4dfp.img files.)
A collection of R functions for use with Stock Synthesis, a
fisheries stock assessment modeling platform written in ADMB by Dr. Richard
D.  Methot at the NMFS Northwest Fisheries Science Center. The functions
include tools for summarizing and plotting results, manipulating files,
visualizing model parameterizations, and various other tasks.
The R6 package allows the creation of classes with reference
semantics, similar to R's built-in reference classes. Compared to reference
classes, R6 classes are simpler and lighter-weight, and they are not built
on S4 classes so they do not require the methods package. These classes
allow public and private members, and they support inheritance, even when
the classes are defined in different packages.
Implementation of some racing methods for the empirical
selection of the best. If the R package `rpvm' is installed
(and if PVM is available, properly configured, and
initialized), the evaluation of the candidates are performed in
parallel on different hosts.
Fit a variety of models to Rank Abundance Data
This package implements import, export, manipulation, visualization, and downstream
(post-clustering) analysis of RADseq data, integrating with the pyRAD package by Deren Eaton.
Fundamental formulas for Radar, for attenuation, range, velocity,
effectiveness, power, scatter, doppler, geometry, radar equations, etc.
Based on Nick Guy's Python package PyRadarMet
A platform-independent browser-based interface for business analytics in R, based on the Shiny package.
RadioSonde is a collection of programs for reading and
plotting SKEW-T,log p diagrams and wind profiles for data
collected by radiosondes (the typical weather balloon-borne
instrument), which we will call "flights", "sondes", or
"profiles" throughout the associated documentation.  The raw
data files are in a common format that has a header followed by
specific variables.  Use "help(ExampleSonde)" for the full
explanation of the data files.
Radioactive doses estimation using individual chromosomal aberrations information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015). A new inverse regression model applied to radiation biodosimetry. Proceedings of the Royal Society A, 471
Designed for the import, analysis, and visualization of dosimetric and volumetric data in Radiation Oncology, the tools herein enable import of dose-volume histogram information from Varian's 'Eclipse' platform and 3D structural representations and dosimetric information from 'DICOM-RT' files.  These tools also enable subsequent visualization and statistical analysis of these data.
Contains 4 different functions for radon and soil gas transport in a porous medium.
Aims at loading Google Adwords data into R. Adwords is an online
advertising service that enables advertisers to display advertising copy to web users.
Therefore the package implements three main features. First, the package provides an
authentication process for R with the Google Adwords API via OAUTH2. Second, the
package offers an interface to apply the Adwords query language in R and
query the Adwords API with ad-hoc reports. Third, the received data are
transformed into suitable data formats for further data processing and data
analysis.
A series of shortcuts for routine tasks originally developed by Rafael A. Irizarry to facilitate data exploration.
Package contains proper L2-penalized ML estimators for the precision matrix as well as supporting functions to employ these estimators in a graphical modeling setting.
Data fusion filters for Attitude Heading Reference System (AHRS) based on
Vlad Maximov's GyroLib AHRS library (quaternion based linearized/extended/unscented Kalman filter,
Euler based LKF, gyro-free with vector matching, SVD calibration and EKF calibration),
Sebastian O.H. Madgwick AHRS algorithms and Sebastian O.H. Madgwick implementation of Mayhony et al AHRS algorithm.
Functions and data sets for functional data display and outlier detection.
The Climate Prediction Center's (CPC) rainfall data for the
world (1979 to present, 50 km resolution) and the USA (1948 to
present, 25 km resolution), is one of the few high quality, long
term, observation based, daily rainfall products available for free.
Although raw data is available at CPC's ftp site, obtaining,
processing and visualizing the data is not straightforward. There are
more than 12,000 files for the world and about 24,000 files for the USA.
Moreover, file formats and file extensions have not been consistent.
This package provides functionality to download, process and visualize
over 35 years of global rainfall data and over 65 years of USA rainfall
data from CPC.
Estimates of rainfall at desired frequency (e.g., 1% annual
chance or 100-year return period) and desired duration (e.g.,
24-hour duration) are often required in the design of dams and other
hydraulic structures, catastrophe risk modeling, environmental
planning and management. One major source of such estimates for the
USA is the NOAA National Weather Service's (NWS) division of
Hydrometeorological Design Studies Center (HDSC). Raw data from
NWS-HDSC is available at 1-km resolution and comes as a huge number
of GIS files. This package provides functionality to easily access
and analyze the 1-km GIS files provided by NWS' PF Data Server for
the entire USA. This package also comes with datasets on record point
rainfall measurements provided by NWS-HDSC.
Programmatic interface to the Altmetric.com API.
Characterizing environmental microbiota diversity using amplicon-based next generation sequencing (NGS) data. Functions are developed to manipulate operational taxonomic unit (OTU) table, perform descriptive and inferential statistics, and generate publication-quality plots.
Estimate the parameters, the number of classes and cluster vertices of a random network into groups with homogeneous connection profiles. The clustering is performed for directed graphs with typed edges (edges are assumed to be drawn from multinomial distributions) for which a partition of the vertices is available.
A "define" function is provided that allows
for inclusion of external scripts without polluting
the global namespace and makes it easier to
write modular R code.
Additional matrix functionality for R including: (1) wrappers
for the base matrix function that allows matrices to be created from character
strings and lists (the former is especially useful for creating block
matrices), (ii) better printing of large matrices via a new generic function
for "pretty" printing, and (iii) a number of convenience functions for users
more familiar with other scientific languages like 'Julia', 'Matlab'/'Octave',
or 'Python'+'NumPy'.
This package provides an efficient procedure for fitting the entire solution path for high-dimensional regularized generalized linear models with interactions effects under the strong heredity constraint.
RAMpath is a rewrite of RAMpath software developed by John McArdle and Steven Boker. In addition to performing regular SEM analysis through the R package lavaan, RAMpath has unique features.  First, it can generate path diagrams according to a given model. Second, it can display path tracing rules through path diagrams and decompose total effects into their respective direct and indirect effects as well as decompose variances and covariances into individual bridges. Furthermore, RAMpath can fit dynamic system models automatically based on latent change scores and generate vector field plots based upon results obtained from a bivariate dynamic system.
Bayesian geostatistical modeling of Gaussian processes using a reparameterized and marginalized posterior sampling (RAMPS) algorithm designed to lower autocorrelation in MCMC samples.  Package performance is tuned for large spatial datasets.
The deterministic part of the Fortuna cryptographic
pseudorandom number generator, described by Schneier & Ferguson
"Practical Cryptography"
Generates random names with additional information including fake SSNs, gender, location, zip, age, address, and nationality.
The true random number service provided by the RANDOM.ORG
website created by Mads Haahr samples atmospheric noise via radio tuned to
an unused broadcasting frequency together with a skew correction algorithm
due to John von Neumann.  More background is available in the included
vignette based on an essay by Mads Haahr.  In its current form, the package
offers functions to retrieve random integers, randomized sequences and
random strings.
Methods for the inference on and the simulation of Gaussian fields are provided, as well as methods for the simulation of extreme value random fields.
Various utilities are provided that might be used in spatial statistics and elsewhere. It delivers a method for solving linear equations that checks the sparsity of the matrix before any algorithm is used. Furthermore, it includes the Struve functions.
Classification and regression based on a forest of trees
using random inputs.
A unified treatment of Breiman's random forests for survival, regression and classification problems based on Ishwaran and Kogalur's random survival forests (RSF) package.  The package runs in both serial and parallel (OpenMP) modes.
The package implements a bagging predictor based on
general linear models
Allows the user to conduct randomization-based inference for a wide variety of experimental scenarios. The package leverages a potential outcomes framework to output randomization-based p-values and null intervals for test statistics geared toward any estimands of interest, according to the specified null and alternative hypotheses. Users can define custom randomization schemes so that the randomization distributions are accurate for their experimental settings. The package also creates visualizations of randomization distributions and can test multiple test statistics simultaneously.
Contains a function to randomize subjects, patients in groups of
sequences (treatment sequences).
If a blocksize is given, the randomization will be done within blocks.
The randomization may be controlled by a Wald-Wolfowitz runs test.
Functions to obtain the p-value of that test are included.
The package is mainly intended for randomization of bioequivalence studies
but may be used also for other clinical crossover studies.
Contains two helper functions sequences() and williams() to get the sequences
of commonly used designs in BE studies.
Generates random assignments for common experimental
designs: simple, complete, blocked, and clustered.
Fits random effects latent class models, as well as standard latent class models.
Function for generating random gender and ethnicity correct first and/or last names. Names are chosen proportionally based upon their probability of appearing in a large scale data base of real names.
The Function performs a parallel analysis using simulated polychoric correlation matrices. The nth-percentile of the eigenvalues distribution obtained from both the randomly generated and the real data polychoric correlation matrices is returned. A plot comparing the two types of eigenvalues (real and simulated) will help determine the number of real eigenvalues that outperform random data. The function is based on the idea that if real data are non-normal and the polychoric correlation matrix is needed to perform a Factor Analysis, then the Parallel Analysis method used to choose a non-random number of factors should also be based on randomly generated polychoric correlation matrices and not on Pearson correlation matrices. Random data sets are simulated assuming or a uniform or a multinomial distribution or via the bootstrap method of resampling (i.e., random permutations of cases). Also Multigroup Parallel analysis is made available for random (uniform and multinomial distribution and with or without difficulty factor) and bootstrap methods. An option to choose between default or full output is also available as well as a parameter to print Fit Statistics (Chi-squared, TLI, RMSEA, RMR and BIC) for the factor solutions indicated by the Parallel Analysis.
Ensemble model, for classification, regression
and unsupervised learning, based on a forest of unpruned
and randomized binary decision trees. Each tree is grown
by sampling, with replacement, a set of variables at each node.
Each cut-point is generated randomly, according to the continuous
Uniform distribution. For each tree, data are either bootstrapped
or subsampled. The unsupervised mode introduces clustering, dimension reduction
and variable importance, using a three-layer engine. Random Uniform Forests are mainly
aimed to lower correlation between trees (or trees residuals), to provide a deep analysis
of variable importance and to allow native distributed and incremental learning.
Several non parametric randomness tests for numeric sequences
Provides (1) pseudo random generators - general linear congruential generators, multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister algorithm and WELL generators); (2) quasi random generators - the Torus algorithm, the Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some RNG tests - the gap test, the serial test, the poker test. The package depends on rngWELL package but it can be provided without this dependency on demand to the maintainer. For true random number generation, use the 'random' package, for Latin Hypercube Sampling (a hybrid QMC method), use the 'lhs' package. A number of RNGs and tests for RNGs are also provided by 'RDieHarder', all available on CRAN. There is also a small stand-alone package 'rngwell19937' for the WELL19937a RNG.
Implementation of random variables by means of S4 classes and methods
Tools for easy generation of (life-history) traits maps based on species range (extent-of-occurrence) maps.
A fast implementation of Random Forests, particularly suited for high
dimensional data. Ensembles of classification, regression, survival and
probability prediction trees are supported. Data from genome-wide
association studies can be analyzed efficiently. In addition to data
frames, datasets of class 'gwaa.data' (R package GenABEL) can be directly
analyzed.
This package performs aggregation of ordered lists based
on the ranks using several different algorithms: Borda count,
Cross-Entropy Monte Carlo algorithm, Genetic algorithm, and a
brute force algorithm (for small problems)
This package proposes a model-based clustering algorithm for
ranking data. Multivariate rankings as well as partial rankings are taken
into account. This algorithm is based on an extension of the Insertion
Sorting Rank (ISR) model for ranking data, which is a meaningful and
effective model parametrized by a position parameter (the modal ranking,
quoted by mu) and a dispersion parameter (quoted by pi). The heterogeneity
of the rank population is modelled by a mixture of ISR, whereas conditional
independence assumption is considered for multivariate rankings.
Implements distance based probability models for ranking data.
The supported distance metrics include Kendall distance, Spearman distance, Footrule distance, Hamming distance,
and Weigthed-tau distance and geo-Weighted Kendall distance.
Mixture models are also supported.
Rank-hazard plots (Karvanen and Harrell, Statistics in Medicine 2009) visualize the relative importance of covariates in a proportional hazards model. The key idea is to rank the covariate values and plot the relative hazard as a function of ranks scaled to interval [0,1]. The relative hazard is plotted in respect to the reference hazard, which can bee.g. the hazard related to the median of the covariate.
Methods for ranking responses of a single response question or a multiple response question
Finds the k nearest neighbours for every point in a given dataset
in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is
support for approximate as well as exact searches, fixed radius searches
and bd as well as kd trees.
Finds the k nearest neighbours for every point in a given dataset
in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is
support for approximate as well as exact searches, fixed radius searches
and 'bd' as well as 'kd' trees. The distance is computed using the L1
(Manhattan, taxicab) metric. Please see package 'RANN' for the same
functionality using the L2 (Euclidean) metric.
To find the reversal association between variables.
Facilitates efficient polygon search using kd trees.
Coordinate level spatial data can be aggregated to higher geographical
identities like census blocks, ZIP codes or police district boundaries.
This process requires mapping each point in the given data set to a
particular identity of the desired geographical hierarchy. Unless efficient
data structures are used, this can be a daunting task. The operation
point.in.polygon() from the package sp is computationally expensive.
Here, we exploit kd-trees as efficient nearest neighbor search algorithm
to dramatically reduce the effective number of polygons being searched.
Package to perform non-invasive fetal testing for aneuploidies
using sequencing count data from cell-free DNA
This package provides other packages with access to the internal
R serialization code. Access to this code is provided at the C function
level by using the registration of native function mechanism. Client
packages simply include a single header file RApiSerializeAPI.h provided by
this package.

This packages builds on the Rhpc package by Junji Nakano and Ei-ji Nakama
which also includes a (partial) copy of the file src/main/serialize.c from R
itself.

The R Core group is the original author of the serialization code made
available by this package.
This package implements R functions that interface to various methods in the Linux kernel related to enforcing security restrictions on a certain task (process). The package can apply mandatory access control (MAC) policies by loading an apparmor profile, and set hardware limits (rlimit), uid, gid, affinity and priority of the current process, directly from within R. The high level function eval.secure builds on these foundations to support dynamic sandboxing: it evaluates a single expression in a temporary fork with hard security restrictions and hardware limits without any side effects on the main R session.
An easy way to determine which directories on the users computer
you should use to save data, caches and logs. A port of Python's Appdirs
(\url{https://github.com/ActiveState/appdirs}) to R.
A package that facilitates creation of reproducible
statistical report templates. Once created, rapport templates
can be exported to various external formats (HTML, LaTeX, PDF,
ODT etc.) with Pandoc as the converter backend.
Helper functions that act as wrappers to more advanced statistical
methods with the advantage of having sane defaults for quick reporting.
This package uses the functions written by Daniel
Morissette <danmo@videotron.ca> to read geographical information in Arc/Info
V 7.x format and E00 files to import the coverages into R variables.
Tests gene-environment interaction for rare genetic variants using Sequence Kernel Association Test (SKAT) type gene-based tests. Includes two tests for the interaction term only, and one joint test for genetic main effects and gene-environment interaction.
Randomization tests for the statistical comparison of \emph{i} = two or more individual-based, sample-based or coverage-based rarefaction curves. The ecological null hypothesis is that the \emph{i} samples were all drawn randomly from a single assemblage, with (necessarily) a single underlying species abundance distribution. The biogeographic null hypothesis is that the \emph{i} samples were all drawn from different assemblages that, nonetheless, share similar species richness and species abundance distributions
Allows calculation of rarity weights for species and indices of rarity for assemblages of species according to different methods (Leroy et al. 2012, 2013).
rARPACK is an R wrapper of the ARPACK library
(http://www.caam.rice.edu/software/ARPACK/) to solve large scale
eigenvalue/vector 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.
MCMC based sampling of binary matrices with fixed margins as used in exact Rasch model tests.
This package contains functions to perform supervised and
pixel based raster image classification. It has been designed
to facilitate land-cover analysis. Five classification
algorithms can be used: Maximum Likelihood Classification,
Multinomial Logistic Regression, Neural Networks, Random
Forests and Support Vector Machines. The output includes the
classified raster and standard classification accuracy
assessment such as the accuracy matrix, the overall accuracy
and the kappa coefficient. An option for in-sample verification
is available.
The rase package primarily implements the Range Ancestral State Estimation for phylogeography described in Quintero, I., Keil, P., Jetz, W., Crawford, F. W. 2015 Historical Biogeography Using Species Geographical Ranges. Systematic Biology. doi: 10.1093/sysbio/syv057. It also includes Bayesian inference of ancestral states under a Brownian Motion model of character evolution and Maximum Likelihood estimation of rase for n-dimensional data. Visualizing functions in 3D are implemented using the rgl package.
Reading, writing, manipulating, analyzing and modeling of gridded spatial data. The package implements basic and high-level functions. Processing of very large files is supported.
Methods for enhanced visualization and interaction with raster data. It implements visualization methods for quantitative data and categorical data, both for univariate and multivariate rasters. It also provides methods to display spatiotemporal rasters, and vector fields. See the website for examples.
An implementation of routines for solving rate-distortion problems.
Rate-distortion theory is a field within information theory that
examines optimal lossy compression. That is, given that some
information must be lost, how can a communication channel be designed
that minimizes the cost of communication error? Rate-distortion
theory is concerned with the optimal  (minimal cost) solution to such
tradeoffs. An important tool for solving rate-distortion problems is
the Blahut algorithm, developed by Richard Blahut and described in:

Blahut, R. E. (1972). Computation of channel capacity and
rate-distortion functions. IEEE Transactions on Information Theory,
IT-18(4), 460-473.

This package implements the basic Blahut algorithm, and additionally contains a number of `helper' functions, including a routine for searching for an information channel that minimizes cost subject to a constraint on information rate.
A function which performs exact rate ratio tests and returns an object of class htest.
The kappa statistic implemented by Fleiss is a very popular index for assessing the reliability of agreement among multiple observers. It is used both in the psychological and in the psychiatric field. Other fields of application are typically medicine, biology and engineering. Unfortunately,the kappa statistic may behave inconsistently in case of strong agreement between raters, since this index assumes lower values than it would have been expected. We propose a modification kappa implemented by Fleiss in case of nominal and ordinal variables. Monte Carlo simulations are used both to testing statistical hypotheses and to calculating percentile bootstrap confidence intervals based on proposed statistic in case of nominal and ordinal data.
This package provides several functions to
manipulate rational functions, including basic
arithmetic operators, derivatives and integrals with
EXPLICIT forms.
This package provide an easy way to produce atmospheric profiles of Pressure,
Temperature and Density according to the standard atmosphere 1976.
It provides also profiles of molecular volume backscatter coefficients for standard atmosphere,
and approximated estimations of sunset, sunrise and solar zenith angle.
The R Analytic Tool To Learn Easily (Rattle) provides a
Gnome (RGtk2) based interface to R functionality for data mining.
The aim is to provide a simple and intuitive interface
that allows a user to quickly load data from a CSV file
(or via ODBC), transform and explore the data,
build and evaluate models, and export models as PMML (predictive
modelling markup language) or as scores. All of this with knowing little
about R. All R commands are logged and commented through the log tab. Thus they
are available to the user as a script file or as an aide for the user to
learn R or to copy-and-paste directly into R itself.
Rattle also exports a number of utility
functions and the graphical user interface, invoked as rattle(),  does
not need to be run to deploy these.
Parameter estimation for averaging models of Anderson's Information Integration Theory
Interface to <http://proyectoavis.com> database.
It provides means to download data filtered by species, order,
family, and several other criteria. Provides also basic functionality to
plot exploratory maps of the datasets.
Provides an interface to functions of the 'SAMtools' C-Library by Heng Li.
Basic R package to access data structures offered by any
BEFdata portal instance.
rbenchmark is inspired by the Perl module Benchmark, and
is intended to facilitate benchmarking of arbitrary R code. The
library consists of just one function, benchmark, which is a
simple wrapper around system.time.  Given a specification of
the benchmarking process (counts of replications, evaluation
environment) and an arbitrary number of expressions, benchmark
evaluates each of the expressions in the specified environment,
replicating the evaluation as many times as specified, and
returning the results conveniently wrapped into a data frame.
Oracle Berkeley DB -
<http://www.oracle.com/technetwork/database/database-technologies/berkeleydb/overview/index.html> -
is a family of embedded key-value database
libraries providing scalable high-performance data management services
to applications. The Berkeley DB products use simple function-call APIs
for data access and management. This package provides an R interface to
the Berkeley DB API.
The package contains functions to generate random numbers
from the beta distribution and random vectors from the
Dirichlet distribution.
Interface to 'Biodiversity' 'Heritage' Library ('BHL') 'API'
methods. 'BHL' is a repository of 'digitized' literature on 'biodiversity'
studies, including 'floras', research papers, and more.
To facilitate retrieving and processing biochemical reaction data such as Rhea, MetaCyc, KEGG and Unipathway, the package provides the functions to download and parse data, instantiate generic reaction and check mass-balance. The package aims to construct an integrated metabolic network and genome-scale metabolic model.
Interface to the 'USGS' 'BISON' 'API', a 'database' for
species occurrence data on the web. Data comes from species in the
United States from participating data providers. You can get
data via 'taxonomic' and location based queries. A simple function
is provided to help visualize data.
Utilities related to Bitcoin. Unified markets API interface
(bitstamp, kraken, btce, bitmarket). Both public and private API calls.
Integration of data structures for all markets. Support SSL. Read Rbitcoin
documentation (command: ?btc) for more information.
An R package for the BitCoinCharts.com API.
Allows users accessing 'Bit.ly API' http://dev.bitly.com/ and retrieve many useful statistics.
An R Interface to the BBG service is provided via the Blp API.
Creation, manipulation, simulation of linear Gaussian Bayesian
networks from text files and more...
Scalable decision tree training and prediction.
Takes matched and unmatched data and calculates Rosenbaum bounds for the treatment effect.  Calculates bounds for binary outcome data, Hodges-Lehmann point estimates, Wilcoxon signed-rank test for matched data and matched IV estimators, Wilcoxon sum rank test, and for data with multiple matched controls. Package is also designed to work with the Matching package and operate on Match() objects.
The package provides a visual tool, the RBP curve, to assess the
performance of prediction models.
Functions to prepare files needed for running BUGS in
batch-mode, and running BUGS from R. Support for Linux and
Windows systems with OpenBugs is emphasized.
Rbundler manages a project-specific library for dependency
package installation. By specifying dependencies in a DESCRIPTION file
in a project's root directory, one may install and use dependencies
in a repeatable fashion without requiring manual maintenance.
rbundler creates a project-specific R library in
`PROJECT_ROOT/.Rbundle` (by default) and a project-specific
`R_LIBS_USER` value, set in `PROJECT_ROOT/.Renviron`. It supports
dependency management for R standard "Depends", "Imports",
"Suggests", and "LinkingTo" package dependencies. rbundler also
attempts to validate and install versioned dependencies, such
as ">=", "==", "<=". Note that, due to the way R manages package
installation, differing nested versioned dependencies are not
allowed. For example, if your project depends on packages A (== 1),
and B (== 2), but package A depends on B (== 1), then a nested
dependency violation will cause rbundler to error out.
Relational Class Analysis (RCA) is a method for
detecting heterogeneity in attitudinal data. (as
described in Goldberg A., 2011, Am. J. Soc, 116(5)) .
src/ also contains the source files of igraph-C
which was written by Gabor. LAPACK routines are
included in the igraph source code.
Memoization can be used to speed up repetitive and computational expensive function calls.  The first time a function that implements memoization is called the results are stored in a cache memory.  The next time the function is called with the same set of parameters, the results are momentarily retrieved from the cache avoiding repeating the calculations.  With this package, any R object can be cached in a key-value storage where the key can be an arbitrary set of R objects.  The cache memory is persistent (on the file system).
Calculate the flow of particles between polygons by two integration methods: integration by a cubature method and integration on a grid of points.
Estimation of abundance and other of demographic parameters for closed
populations, open populations and the robust design in capture-recapture experiments
using loglinear models.
This package makes some maps using shapefiles and
dataframes. Five kinds of maps are available : proportionnal
circles, proportionnal circles colored by a discretized
quantitative variable, proportionnal circles colored by the
modalities of a qualitative variable, choropleth and typology.
This packages provides a direct interface (without the
use of Java) to the most basic functionality of Apache
Cassanda such as login, updates and queries.
Tools for large, sparse optimal matching of treated units
and control units in observational studies.  Provisions are
made for refined covariate balance constraints, which include
fine and near-fine balance as special cases.  Matches are
optimal in the sense that they are computed as solutions to
network optimization problems rather than greedy algorithms.
R interface to (some of) cddlib
(http://www.ifor.math.ethz.ch/~fukuda/cdd_home/cdd.html).
Converts back and forth between two representations of a convex polytope:
as solution of a set of linear equalities and inequalities and as
convex hull of set of points and rays.
Also does linear programming and redundant generator elimination
(for example, convex hull in n dimensions).  All functions can use exact
infinite-precision rational arithmetic.
This package allows the user to access functionality in the
CDK, a Java framework for cheminformatics. This allows the user to load
molecules, evaluate fingerprints, calculate molecular descriptors and so on.
In addition the CDK API allows the user to view structures in 2D.
This package provides the CDK libraries for use
in the R environment. Given the size of the library itself,
this package is not expected to change very frequently. To make
use of the CDK within R, it is suggested that you use the rcdk
package. Note that it is possible to directly interact with the CDK
using rJava. However rcdk exposes functionality in a more idiomatic way.
The CDK library itself is released as LGPL and the sources can be
obtained from https://github.com/cdk/cdk
RCEIM is a package implementing a stochastic heuristic method for performing multidimensional function optimization. The method is inspired in the Cross-Entropy Method. It does not relies on derivatives, neither imposes particularly strong requirements into the function to be optimized. Additionally, it takes profit from multicore processing to enable optimization of time-consuming functions.
Analyze microscopy based cytometry datasets created with 'Cell-ID'. It includes functions for manipulating and plotting the data. It can also create automatic image montages of cells in a user defined layout.
Example dataset for 'Rcell' package. Contains images and cell data object.
Conjugate gradient minimization of nonlinear functions
with box constraints incorporating the Dai/Yuan update. This
implementation should be used in place of the "CG" algorithm
of the optim() function.
A simple datascience challenge system using R Markdown and Dropbox.
It requires no network configuration, does not depend on external platforms
like e.g. Kaggle and can be easily installed on a personal computer.
An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data.
Collection of portable choice dialog widgets
Functions to generate stimuli and analyze data of reverse correlation image classification experiments (psychophysical tasks aimed at visualizing cognitive mental representations of faces).
RCircos package provides a simple and flexible way to generate Circos 2D track plot images for genomic data visualization. The types of plots include: heatmap, histogram, lines, scatterplot, tiles and plot items for further decorations include connector, link (lines and ribbons), and text (gene) label. All functions require only R graphics package that comes with R base installation.
This package contains wrapper functions and methods which allow to
use "climdex.pcic" and "RMAWGEN" packages.  With this simple approach it is
possible to calculate climate change indices, suggested by the WMO-CCL,
CLIVAR, ETCCDMI(http://www.climdex.org),on stochastic generations of
temperature and precipitation time series, obtained by the application of
RMAWGEN.  Each index can be applied to both observed data and to synthetic
time series produced by the Weather Generator, over a reference period
(e.g. 1981-2010, as in the example). It contains also functions and methods
to evaluate the generated time series of climate change indices consistency
by statistical tests.Bugs/comments/questions/collaboration of any kind are
warmly welcomed.
R tools for integrating with the www.clinicalcodes.org web
repository
ClinicalTrials.gov is a registry and results database of publicly
and privately supported clinical studies of human participants conducted
around the world. Users can search for information about and results from
those trials. This provides a set of functions to interact with the search
and download features. Results are downloaded to temporary directories and
returned as R objects.
Provide flexible native clustering routines that can be
linked against in downstream packages.
Tool for providing access to the Java version 'CMAEvolutionStrategy' of
Nikolaus Hansen. 'CMA-ES' is the Covariance Matrix Adaptation Evolution Strategy,
see https://www.lri.fr/~hansen/cmaes_inmatlab.html#java.
A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.
Various statistical, graphics, and data-management functions used by the Rcmdr package in the R Commander GUI for R.
An Rcmdr "plug-in" to accompany the book Customer and
Business Analytics: Applied Data Mining for Business Decision
Making Using R by Daniel S. Putler and Robert E. Krider.
This package provides a Rcmdr "plug-in" based on coin (Conditional Inference Procedures in a Permutation Test Framework).
This package provides an Rcmdr plug-in based on the
depthTools package, which implements different robust
statistical tools for the description and analysis of gene
expression data based on the Modified Band Depth, namely, the
scale curves for visualizing the dispersion of one or various
groups of samples (e.g. types of tumors), a rank test to decide
whether two groups of samples come from a single distribution
and two methods of supervised classification techniques, the DS
and TAD methods.
The package provides a platform-independent GUI for design of experiments.
It is implemented as a plugin to the R-Commander, which is a more general
graphical user interface for statistics in R based on tcl/tk.
DoE functionality can be accessed through the menu Design that is added to the
R-Commander menus.
This package provides an Rcmdr "plug-in" based on the
Design of experiments class Stat 4309
Este paquete proporciona una interfaz grafica de usuario (GUI) para algunos de los procedimientos estadisticos detallados en un curso de 'Estadistica aplicada a las Ciencias Sociales mediante el programa informatico R' (EACSPIR). LA GUI se ha desarrollado como un Plugin del programa R-Commander.
This package provides an Rcmdr plug-in GUI extension for Evidence Based Medicine medical indicators calculations (Sensitivity, specificity, absolute risk reduction, relative risk, ...).
This package provides an Rcmdr "plug-in" for the EcoVirtual package and was designed primarily for teaching ecological models using simulations.
This package provides an Rcmdr "plug-in" based on the time
series functions.  Contributors: G. Jay Kerns, John Fox, and
Richard Heiberger.
EZR (Easy R) adds a variety of statistical functions, including survival analyses, ROC analyses, metaanalyses, sample size calculation, and so on, to the R commander. EZR enables point-and-click easy access to statistical functions, especially for medical statistics. EZR is platform-independent and runs on Windows, Mac OS X, and UNIX. Its complete manual is available only in Japanese (Chugai Igakusha, ISBN: 978-4-498-10901-8 or Nankodo, ISBN: 978-4-524-26158-1), but an report that introduced the investigation of EZR was published in Bone Marrow Transplantation (Nature Publishing Group) as an Open article. This report can be used as a simple manual. It can be freely downloaded from the journal website as shown below.
Rcmdr menu support for many of the functions in the HH package.
The focus is on menu items for functions we use in our introductory
courses.
This package is an R Commander plugin that accompanies IPSUR, an Introduction to Probability and Statistics Using R.
This package is an R Commander plug-in for Kaplan-Meier
plots and other plots by using the ggplot2 package.
This package provides an Rcmdr "plug-in" based on the
lfstat package for low flow analysis.
Easy to use interface for conducting meta-analysis in R. This
package is an Rcmdr-plugin, which allows the user to conduct analyses in a
menu-driven, graphical user interface environment (e.g., CMA, SPSS). It
uses recommended procedures as described in The Handbook of Research
Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).
Rcmdr menu items to display mosaic and assoc plots Allows
to visually restructure the underlying structables Developed
after extended discussions with Rich Heiberger
This package provides an R Commander plugin that offers a
unified menu of new and pre-existing statistical functions
related to public management and policy analysis statistics.
Functions and menus have been renamed according to the usage
in PMGT 630 in the Master of Public Administration program at
Brigham Young University.
An R Commander "plug-in" extending functionality of linear models and providing an interface to Partial Least Squares Regression and Linear and Quadratic Discriminant analysis. Several statistical summaries are extended, predictions are offered for additional types of analyses, and extra plots, tests and mixed models are available.
This package provides a GUI for the orloca package, it is
developed as an Rcmdr plug-in.
Rcmdr menu support for some of the graphics by group in
the lattice package
This package provides a Rcmdr "plug-in" to analyze questionnaire data.
This package provides an Rcmdr "plug-in" based on the
Quality control class Stat 4300
Mixed Treatment Comparison is a methodology to compare directly and/or indirectly health strategies (drugs, treatments, devices). This package provides an Rcmdr "plug-in" to perform Mixed Treatment Comparison for binary outcome using BUGS code from Bristol University (Lu and Ades).
Rcmdr GUI extension plug-in for Receiver Operator Characteristic tools from pROC and ROCR packages. Also it ads a Rcmdr GUI extension for Hosmer and Lemeshow GOF test from the package ResourceSelection.
This package includes tools for calculating sample sizes and
selecting samples using various sampling designs. This package is an extension
of RcmdrPlugin.EHESsampling which was developed as part of the EHES pilot project.
The EHES Pilot project has received funding from the European Commission and
DG Sanco. The views expressed here are those of the authors and they do not represent
Commission's official position.
Provides a GUI for the SCVA, SCRT and SCMA packages. The package is written as an Rcmdr plugin.
Supports the text book Acevedo, M.F (2013) "Data Analysis
and Statistics for Geography, Environmental Science, and
Engineering" CRC Press
This package provides a GUI for the SLC package, it is
written as an Rcmdr plug-in.
This package provides an Rcmdr "plug-in" for studying
sport management data.
Rcmdr interface to the 'sos' package. The plug-in renders
the 'sos' searching functionality easily accessible via the Rcmdr
menus. It also simplifies the task of performing multiple searches and
subsequently obtaining the union or the intersection of the results.
This package provides a GUI for the steepness package, it
is written as an Rcmdr plug-in.
This package provides an R Commander plug-in for the survival
package, with dialogs for Cox models, parametric survival regression models,
estimation of survival curves, and testing for differences in survival
curves, along with data-management facilities and a variety of tests,
diagnostics and graphs.
This package provides an Rcmdr "plug-in" based on the
TeachingDemos package, and is primarily for illustrative
purposes.
An R Commander plug-in providing an integrated solution to perform
a series of text mining tasks such as importing and cleaning a corpus, and
analyses like terms and documents counts, vocabulary tables, terms
co-occurrences and documents similarity measures, time series analysis,
correspondence analysis and hierarchical clustering. Corpora can be imported
from spreadsheet-like files, directories of raw text files, Twitter queries,
as well as from Dow Jones Factiva, LexisNexis, Europresse and Alceste files.
Some extension to Rcmdr (R Commander) made by R-UCA project and used in teaching statistics at University of Cadiz (UCA).
Working with CMIP5 data can be tricky, forcing scientists to write
custom scripts and programs. The `RCMIP5` package aims to ease this
process, providing a standard, robust, and high-performance set of scripts
to (i) explore what data have been downloaded, (ii) identify missing data,
(iii) average (or apply other mathematical operations) across experimental
ensembles, (iv) produce both temporal and spatial statistical summaries,
and (v) produce easy-to-work-with graphical and data summaries.
Provides programmatic access to Colombos, a web based
interface for exploring and analyzing comprehensive organism-specific
cross-platform expression compendia of bacterial organisms.
Provides color schemes for maps (and other graphics)
designed by Cynthia Brewer as described at http://colorbrewer2.org
Solve some conic related problems (intersection of conics with lines and conics, arc length of an ellipse, polar lines, etc.).
A collection of small text corpora of interesting data.
It contains all data sets from https://github.com/dariusk/corpora.
Some examples:
names of animals: birds, dinosaurs, dogs; foods: beer categories,
pizza toppings; geography: English towns, rivers, oceans;
humans: authors, US presidents, occupations; science: elements,
planets; words: adjectives, verbs, proverbs, US president quotes.
R interface to CPLEX solvers for linear, quadratic, and (linear and quadratic) mixed integer programs. Support for quadratically constrained programming is available. A working installation of CPLEX is required for usage of the Rcplex package. See the file "INSTALL" for details on how to install the Rcplex package in Linux/Unix-like systems and Windows systems. Support for sparse matrices is provided by an S3-style class "simple_triplet_matrix" from package slam and by objects from the Matrix package class hierarchy.
Identifies regions of common (species) profiles (RCPs).  Within a region the probability of sampling all species remains approximately constant.  This is performed using mixtures-of-experts models.  The package also contains associated methods, such as diagnostics.  Currently, the model and methods are defined for species presence-absence data for a number of sites.
The 'Rcpp' package provides R functions as well as C++ classes which
offer a seamless integration of R and C++. Many R data types and objects can be
mapped back and forth to C++ equivalents which facilitates both writing of new
code as well as easier integration of third-party libraries. Documentation
about 'Rcpp' is provided by several vignettes included in this package, via the
'Rcpp Gallery' site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and
Francois (2011, JSS), and the book by Eddelbuettel (2013, Springer); see
'citation("Rcpp")' for details on these last two.
Rcpp11 includes a header only C++11 library that facilitates
integration between R and modern C++.
'Annoy' is a small C++ library for Approximate Nearest Neighbors
written for efficient memory usage as well an ability to load from / save to
disk. This package provides an R interface by relying on the 'Rcpp' package,
exposing the same interface as the original Python wrapper to 'Annoy'. See
<https://github.com/spotify/annoy> for more on 'Annoy'. 'Annoy' is released
under Version 2.0 of the Apache License. Also included is a small Windows
port of 'mmap' which is released under the MIT license.
The APT Package Management System provides Debian and
Debian-derived Linux systems with a powerful system to resolve package
dependencies. This package offers access directly from R.
'Armadillo' is a templated C++ linear algebra library (by Conrad
Sanderson) that aims towards a good balance between speed and ease of use. Integer,
floating point and complex numbers are supported, as well as a subset of
trigonometric and statistics functions. Various matrix decompositions are
provided through optional integration with LAPACK and ATLAS libraries.
The 'RcppArmadillo' package includes the header files from the templated
'Armadillo' library. Thus users do not need to install 'Armadillo' itself in
order to use 'RcppArmadillo'. 'Armadillo' is licensed under the MPL 2.0, while
'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the
GNU GPL version 2 or later, as is the rest of 'Rcpp'.
This package provides R with access to Boost Date_Time
functionality by using Rcpp modules.

Functionality from Boost Date_Time for dates, durations (both for days
and datetimes), timezones, and posix time ("ptime") is provided. The posix
time implementation can support high-resolution of up to nano-second
precision by using 96 bits (instead of R's 64) to present a ptime object.
The RcppClassic package provides a deprecated C++ library which
facilitates the integration of R and C++.

New projects should use the new Rcpp API in the Rcpp package.
The Rcpp package contains a C++ library that facilitates
the integration of R and C++ in various ways via a rich API.
This API was preceded by an earlier version which has been
deprecated since 2010 (but is still supported to provide
backwards compatability in the package RcppClassic).  This
package RcppClassicExamples provides usage examples for the
older, deprecated API. There is also a corresponding package
RcppExamples package with examples for the newer, current API
which we strongly recommend as the basis for all new
development.
The cnpy library written by Carl Rogers provides read and write
facilities for files created with (or for) the NumPy extension for Python.
Vectors and matrices of numeric types can be read or written to and from
files as well as compressed files. Support for integer files is available if
the package has been built with -std=c++11 which is the default starting
with release 0.2.3 following the release of R 3.1.0.
An efficient C++ based implementation of the 'DEoptim'
function which performs global optimization by differential evolution.
Its creation was motivated by trying to see if the old approximation "easier,
shorter, faster: pick any two" could in fact be extended to achieving all
three goals while moving the code from plain old C to modern C++.  The
initial version did in fact do so, but a good part of the gain was due to
an implicit code review which eliminated a few inefficiencies which have
since been eliminated in 'DEoptim'.
This package is based on the C++ code from Yusuke Sugomori,
which implements basic machine learning methods with
many layers (deep learning), including dA (Denoising Autoencoder),
SdA (Stacked Denoising Autoencoder), RBM (Restricted Boltzmann machine) and
DBN (Deep Belief Nets).
R and 'Eigen' integration using 'Rcpp'.
'Eigen' is a C++ template library for linear algebra: matrices,
vectors, numerical solvers and related algorithms.  It supports dense
and sparse matrices on integer, floating point and complex numbers,
decompositions of such matrices, and solutions of linear systems. Its
performance on many algorithms is comparable with some of the best
implementations based on 'Lapack' and level-3 'BLAS'.

The 'RcppEigen' package includes the header files from the 'Eigen' C++
template library (currently version 3.2.5). Thus users do not need to
install 'Eigen' itself in order to use 'RcppEigen'.

Since version 3.1.1, 'Eigen' is licensed under the Mozilla Public License
(version 2); earlier version were licensed under the GNU LGPL version 3 or
later. 'RcppEigen' (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under
the GNU GPL version 2 or later, as is the rest of 'Rcpp'.
Examples for Seamless R and C++ integration The Rcpp
package contains a C++ library that facilitates the integration
of R and C++ in various ways. This package provides some usage
examples.

Note that the documentation in this package currently does not cover
all the features in the package. It is not even close. On the
other hand, the site http://gallery.rcpp.org is regrouping a
number of examples for Rcpp.
Access to a family of Gauss error functions for arbitrary complex arguments is provided via the 'Faddeeva' package by Steven G. Johnson (see <http://ab-initio.mit.edu/wiki/index.php/Faddeeva_Package> for more information).
'Rcpp' integration for 'GNU GSL' vectors and matrices
The 'GNU Scientific Library' (or 'GSL') is a collection of numerical routines for
scientific computing. It is particularly useful for C and C++ programs as it
provides a standard C interface to a wide range of mathematical routines
such as special functions, permutations, combinations, fast fourier
transforms, eigensystems, random numbers, quadrature, random distributions,
quasi-random sequences, Monte Carlo integration, N-tuples, differential
equations, simulated annealing, numerical differentiation, interpolation,
series acceleration, Chebyshev approximations, root-finding, discrete
Hankel transforms physical constants, basis splines and wavelets.  There
are over 1000 functions in total with an extensive test suite.

The 'RcppGSL' package provides an easy-to-use interface between 'GSL' data
structures and R using concepts from 'Rcpp' which is itself a package that
eases the interfaces between R and C++.

This package also serves as a prime example of how to build a package
that uses 'Rcpp' to connect to another third-party library. The 'autoconf'
script, 'inline' plugin and example package can all be used as a stanza to
write a similar package against another library.
MLPACK is an intuitive, fast, scalable C++ machine learning
library, meant to be a machine learning analog to LAPACK. It
aims to implement a wide array of machine learning methods
and function as a Swiss army knife for machine learning
researchers: MLPACK is from http://www.mlpack.org/: sources are included in the package.
Direct interface to Octave. The primary goal is to facilitate the
port of Matlab/Octave scripts to R. The package enables to call any Octave
functions from R and as well as browsing their documentation, passing
variables between R and Octave, using R core RNGs in Octave, which ensures
that stochastic computations are also reproducible.
High level functions for doing parallel programming with 'Rcpp'.
For example, the parallelFor() function can be used to convert the work of
a standard serial "for" loop into a parallel one and the parallelReduce()
function can be used for accumulating aggregate or other values.
This package allows to display a progress bar in the R
console for long running computations taking place in c++ code,
and support for interrupting those computations even in multithreaded
code, typically using OpenMP.
Connection to the 'Redis' key/value store using the
C-language client library 'hiredis'.
Provides fast and efficient routines for
common rolling / windowed operations. Routines for the
efficient computation of windowed mean, median,
sum, product, minimum, maximum, standard deviation
and variance are provided.
An R interface to the C++/Boost Shark machine learning library.
This package provides R with access to the Sequential
Monte Carlo Template Classes by Johansen (Journal of Statistical
Software, 2009, v30, i6).

At present, two additional examples have been added, and the first
example from the JSS paper has been extended. Further integration
and extensions are planned.
The Streamulus (template, header-only) library by
Irit Katriel (at https://github.com/iritkatriel/streamulus)
provides a very powerful yet convenient framework for stream
processing.

This package connects Streamulus to R by providing both the header
files and all examples.
The configuration format defined by 'TOML' (which expands to
"Tom's Obvious Markup Language") specifies an excellent format (described at
<https://github.com/toml-lang/toml>) suitable for both human editing as well
as the common uses of a machine-readable format. This package uses 'Rcpp' to
connect the 'cpptoml' parser written by Chase Geigle (in modern C++11) to R.
This package provides access to some of the C level
functions of the xts package.

In its current state, the package is mostly a proof-of-concept to
support adding useful functions, and does not yet add any of
its own.
The Ziggurat generator for normally distributed random numbers,
originally proposed by Marsaglia and Tsang (JSS, 2000), has been improved
upon a few times starting with Leong et al (JSS, 2005). This package provides
an aggregation in order to compare different implementations. The goal is to
provide an 'faster but good enough' alternative for use with R and C++ code.

The package is still in an early state. Unless you know what you are doing,
sticking with the generators provided by R may be a good idea as these have
been extremely diligently tested.
Client for various 'CrossRef' 'APIs', including 'metadata' search
with their old and newer search 'APIs', get 'citations' in various formats
(including 'bibtex', 'citeproc-json', 'rdf-xml', etc.), convert 'DOIs'
to 'PMIDs', and 'vice versa', get citations for 'DOIs', and get links to
full text of articles when available.
Basic access to market infomation from the public API for the Crypto-Currency exchange Cryptsy.
R interface to the CSDP semidefinite programming library. Installs version 6.1.1 of CSDP from the COIN-OR website if required. An existing installation of CSDP may be used by passing the proper configure arguments to the installation command. See the INSTALL file for further details.
Functions and objects for CUR matrix decomposition.
A wrapper for 'libcurl' <http://curl.haxx.se/libcurl/>
Provides functions to allow one to compose general HTTP requests
and provides convenient functions to fetch URIs, get & post
forms, etc. and process the results returned by the Web server.
This provides a great deal of control over the HTTP/FTP/...
connection and the form of the request while providing a
higher-level interface than is available just using R socket
connections.  Additionally, the underlying implementation is
robust and extensive, supporting FTP/FTPS/TFTP (uploads and
downloads), SSL/HTTPS, telnet, dict, ldap, and also supports
cookies, redirects, authentication, etc.
Functions to convert Rd to roxygen documentation. It can parse an
Rd file to a list, create the roxygen documentation and update the original
R script (e.g. the one containing the definition of the function)
accordingly. This package also provides utilities which can help developers
build packages using roxygen more easily. The formatR package can be used
to reformat the R code in the examples sections so that the code will be
more readable.
Shrunken Centroids Regularized Discriminant Analysis for
the classification purpose in high dimensional data.
Provides basic functionalities for writing a module
for http://datacanvas.io. The http://datacanvas.io is a big data
analytics platform that helps data scientists to build, manage
and share data pipelines.
Fetches data from DataMarket.com, either as
timeseries in zoo form (dmseries) or as long-form data
frames (dmlist). Metadata including dimension structure
is fetched with dminfo, or just the dimensions with
dmdims.
This package provides the tools to undertake estimation in
Regression Discontinuity Designs. Both sharp and fuzzy designs are
supported. Estimation is accomplished using local linear regression.
A provided function will utilize Imbens-Kalyanaraman optimal
bandwidth calculation. A function is also included to test the
assumption of no-sorting effects.
Set of functions for Regression Discontinuity Design ('RDD'), for
data visualisation, estimation and testing.
Data Envelopment Analysis for R, estimating robust DEA scores without and with environmental variables and doing returns-to-scale tests.
The package provides functions for estimating the relevant
dimension of a data set in feature spaces, applications to
model selection, graphical illustrations and prediction.
Functions for creating plots and image files in a unified way regardless of output format (EPS, PDF, PNG, SVG, TIFF, WMF, etc.).  Default device options as well as scales and aspect ratios are controlled in a uniform way across all device types.  Switching output format requires minimal changes in code.  This package is ideal for large-scale batch processing, because it will never leave open graphics devices or incomplete image files behind, even on errors or user interrupts.
The package has many function that helps to perform
various quality check on the data.It basically provides many
function that helps in performing Extrapolative data analysis.
The RDieHarder packages provides an R interface to
the dieharder suite of random number generators and tests that
was developed by Robert G. Brown and David Bauer, extending
earlier work by George Marsaglia and others.
Analysis of distance sampling data collected on line transect surveys.  Estimates distance-based detection functions and abundances.
Imports real-time thermo cycler (qPCR) data from Real-time PCR
Data Markup Language (RDML) format files and transforms to the appropriate
formats of the 'qpcR' and 'chipPCR' packages. Contains a dendrogram
visualization for the structure of RDML object.
A package that controls the Java software Discourse Network
Analyzer (DNA) from within R. Network matrices, statement frequency time
series and attributes of actors can be transferred directly into R.
Data analysis functions for Dota2. Dota2 is a popular online game (see, e.g. <http://en.wikipedia.org/wiki/Dota_2> for more information) and there are more and more websites doing data analysis for paid players.The data of the latest hero, Winter Wyvern and the latest game version, 6.83c, are included. The package now contains functions for calculating the best choice given specific lineup, showing unconditional win rates and the global online population.
Functions for manipulation of Rd objects, including function
reprompt() for updating existing Rd documentation for
functions, methods and classes, and function rebib() for
import of references from bibtex files.
Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD	designs: rdrobust to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the 	cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect to perform bandwidth selection for the different procedures implemented, and rdplot to conduct exploratory data analysis (RD plots).
Provides full programmatic access to the Dropbox file hosting platform (dropbox.com), including support for all standard file operations.
Provides functionality for carrying out estimation
with data collected using Respondent-Driven Sampling. This includes
Heckathorn's RDS-I and RDS-II estimators as well as Gile's Sequential
Sampling estimator. The package is part of the "RDS Analyst" suite of
packages for the analysis of respondent-driven sampling data.
R interface to DSDP semidefinite programming library. The DSDP software is a free open source implementation of an interior-point method for semidefinite programming. It provides primal and dual solutions, exploits low-rank structure and sparsity in the data, and has relatively low memory requirements for an interior-point method.
Provides a threads-type programming environment for R.
The package gives the R programmer the clearer, more concise
shared memory world view, and in some cases gives superior
performance as well.  In addition, it enables parallel processing on
very large, out-of-core matrices.
This package provides an R interface to Pete Warden's Data
Science Toolkit.  See www.datasciencetoolkit.org for more
information.  The source code for this package can be found at
github.com/rtelmore/RDSTK Happy hacking!
The rDVR package allows you to start stop and save a video server
from within R. It does this by way of a REST interface to a JAVA service.
The jar binary relies on the screen recorder included in the Monte Media
Library (CC BY 3.0 licence) developed by Werner Randelshofer
(http://http://www.randelshofer.ch/monte/). The REST interface was modified
from https://github.com/tuenti/VideoRecorderService which has an Apache
licence.
Routines for developing models that describe reaction and advective-diffusive transport in one, two or three dimensions.
Includes transport routines in porous media, in estuaries, and in bodies with variable shape.
Identifies and reads Windows BMP, JPEG and PNG format bitmap
images. Identification defaults to the use of the magic number embedded in
the file rather than the file extension. Reading of JPEG and PNG image
depends on libjpg and libpng libraries. See file INSTALL for details if
necessary.
Reads data files acquired by MALDI-TOF MS on Bruker Daltonics
machines of the *flex series.
A set of functions to simplify reading data from files. The main function, reader(), should read most common R datafile types without needing any parameters except the filename. Other functions provide simple ways of handling file paths and extensions, and automatically detecting file format and structure.
A collection of R functions to read, write, manipulate, and
convert genotype data in GenAlEx format.  GenAlEx is a widely-used Excel
plugin for manipulating and analysing genotype data.  This package reads
GenAlEx data from text or Excel files and creates an annotated data frame
of class 'genalex'. Several functions are provided for accessing,
manipulating, printing, writing and converting this data. GenAlEx and its
documentation are available at http://biology-assets.anu.edu.au/GenAlEx.
Functions for reading data sets in different formats
for testing machine learning tools are provided. This allows to run
a loop over several data sets in their original form, for example
if they are downloaded from UCI Machine Learning Repository.
The data are not part of the package and have to be downloaded
separately.
Functions for reading mass spectrometry data in mzXML format.
Read ODS (OpenDocument Spreadsheet) files and put them into data
frames.
Function to read and write the Stata 13 (and newer) file format.
Import excel files into R. Supports '.xls' via the embedded 'libxls'
C library (http://sourceforge.net/projects/libxls/) and '.xlsx' via the
embedded 'RapidXML' C++ library (http://rapidxml.sourceforge.net). Works
on Windows, Mac and Linux without external dependencies.
The RealVAMs package fits a multivariate value-added model (VAM) (see Broatch and Lohr 2012) with normally distributed test scores and a binary outcome indicator. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.
Resampling methods for adaptive linear model selection.
These can be thought of as extensions of the Akaike information
criterion that account for searching among candidate models.
Kiefer-Wolfowitz maximum likelihood estimation for mixtures models
and some other density estimation and regression methods based on convex optimization.
A programmatic client for the eBird database, including functions
for searching for bird observations by geographic location (latitude,
longitude), eBird hotspots, location identifiers, by notable sightings, by
region, and by taxonomic name.
R functions for random univariate and multivariate finite mixture generation, number of components, component weights and component parameters estimation, printing and plotting of finite mixtures, bootstrapping and class membership prediction. Variables can be either continuous or discrete, may follow normal, lognormal, Weibull, gamma, binomial, Poisson or Dirac parametric families and should be independent within components.
Build regular expressions piece by piece using human readable code.
Relevant Component Analysis (RCA) tries to find a linear
transformation of the feature space such that the effect of irrelevant
variability is reduced in the transformed space.
recalls provides access to U.S. Federal Government recall data on drugs and food from the Food and Drug Administration, car safety from the National Highway Traffic Safety Administration, and product safety recalls from the Consumer Product Safety Commission.
Pathways in a database could have many redundancies among
them. This package allows the user to set a maximum value for
the proportion of these redundancies.
Beta-diversity indices provide dissimilarity matrices with particular distribution of data requiring specific treatment. For example the high frequency of ties and zero values in turnover indices produces hierarchical cluster dendrograms whose topology and bootstrap supports are affected by the order of rows in the original matrix. Moreover, biogeographical regionalization can be facilitated by a combination of hierarchical clustering and multi-dimensional scaling. The recluster package provides robust techniques to analyze pattern of similarity in species composition.
Simple, easy to use, and flexible functionality for recoding variables. It allows for simple piecewise definition of transformations.
Provides a research infrastructure to test and develop
recommender algorithms.
Provides the Book-Crossing Dataset for the package recommenderlab.
Provides the Jester Dataset for package recommenderlab.
Functions to aid in reconstructing sessions
and efficiently calculating an array of metrics from the resulting data,
including bounce rate, time-on-page, and session length. Although primarily
designed for web data and analytics, its approach is plausibly applicable
to other domains.
Provides functions for linking and de-duplicating data sets.
Methods based on a stochastic approach are implemented as well as
classification algorithms from the machine learning domain.
Functions for generating k-record values and k-record
times
R wrapper of the 'libmf' library
(http://www.csie.ntu.edu.tw/~cjlin/libmf/) for recommender
system using matrix factorization. It is typically used to
approximate an incomplete matrix using the product of two
matrices in a latent space. Other common names for this task
include "collaborative filtering", "matrix completion",
"matrix recovery", etc.
This package provides functions used in the second edition of “R: Einführung durch angewandte Statistik”.
Access data stored in REDCap databases using the Application
Programming Interface (API).  REDCap (Research Electronic Data CAPture) is
a web application for building and managing online surveys and databases
developed at Vanderbilt University.  The API allows users to access data
and project meta data (such as the data dictionary) from the web
programmatically.  The redcapAPI package facilitates the process of
accessing data with options to prepare an analysis-ready data set
consistent with the definitions in a database's data dictionary.
Encapsulates functions to streamline calls from R to the REDCap
API.  REDCap (Research Electronic Data CAPture) is a web application for
building and managing online surveys and databases developed at Vanderbilt
University.  The Application Programming Interface (API) offers an avenue
to access and modify data programmatically, improving the capacity for
literate and reproducible programming.
Reddit is an online bulletin board and a social networking website where registered users can submit and discuss content. This package uses Reddit API to extract Reddit data using Reddit API. The retrieved data has flat structure, i.e. the relationship between comments is not preserved.This may be addressed in the next update of this package. Note that due to the API limitations, the number of comments that can extracted is limited to 500 per thread. The package consists of 3 functions, one for extracting relevant URLS, one for extracting features out of given URLs and one that does both together.
Enables researchers to sample redistricting plans from a pre-specified target distribution using a Markov Chain Monte Carlo algorithm. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements.  The algorithm also can be used in combination with efficient simulation methods such as simulated and parallel tempering algorithms. Tools for analysis such as inverse probability reweighting and plotting functionality are included. The package implements methods described in Fifield, Higgins, Imai and Tarr (2015) ``A New Automated Redistricting Simulator Using Markov Chain Monte Carlo,'' working paper available at <http://http://imai.princeton.edu/research/files/redist.pdf>.
This package estimates regression trees with random
effects as a way to use data mining techniques to describe
longitudinal or panel data.
small package with functions for creating references,
reading from and writing to references and a memory efficient
refdata type that transparently encapsulates matrices and
data.frames
This is a collection of tools to allow the medical professional to
calculate appropriate reference ranges (intervals) with confidence intervals around
the limits for diagnostic purposes.
Reference-free method for conducting EWAS while deconvoluting DNA methylation arising as mixtures of cell types.  This method is similar to surrogate variable analysis (SVA and ISVA), except that it makes additional use of a biological mixture assumption.
Contains functionality for import and managing of downloaded genome annotation Data from Ensembl genome browser (European Bioinformatics Institute) and from UCSC genome browser (University of California, Santa Cruz) and annotation routines for genomic positions and splice site positions.
Provides tools for importing and working with
bibliographic references.  It greatly enhances the 'bibentry' class by
providing a class 'BibEntry' which stores 'BibTeX' and 'BibLaTeX' references,
supports 'UTF-8' encoding, and can be easily searched by any field, by date
ranges, and by various formats for name lists (author by last names,
translator by full names, etc.). Entries can be updated, combined, sorted,
printed in a number of styles, and exported. 'BibTeX' and 'BibLaTeX' '.bib' files
can be read into 'R' and converted to 'BibEntry' objects.  Interfaces to 'NCBI Entrez',
'CrossRef', and 'Zotero' are provided for importing references and
references can be created from locally stored 'PDF' files using 'Poppler'.  Includes
functions for citing and generating a bibliography with hyperlinks for
documents prepared with 'RMarkdown' or 'RHTML'.
Provides subsets with reference semantics, i.e. subsets
which automatically reflect changes in the original object, and which
optionally update the original object when they are changed.
Methods for regression for functional
data, including function-on-scalar, scalar-on-function, and
function-on-function regression. Some of the functions are applicable to
image data.
Methods for regressing scalar responses on functional or image predictors, via transformation to the wavelet domain and back.
This package clusters regression coefficients using the methods of clustering through linear regression models (CLM) (Qin and Self 2006). Maximum likelihood approach is used to infer the parameters for each cluster. Bayesian information criterion (BIC) combined with Bootstrapped maximum volume (BMV) criterion are used to determine the number of clusters.
Detecting mislabeled samples in genetic data.
Produces population distribution of disease risk and statistical risk categories, and predicts risks for individuals with genotype information.
An R framework for constructing and managing human
readable regular expressions.  It aims to provide tools that
enable the user to write regular expressions in a way that is
similar to the ways R code is written. The tools allow the user
to (1) write in smaller, modular, named, sub-expressions, (2)
write top to bottom, rather than a single string (3) comment
individual chunks, (4) indent expressions to clearly present
regular expression groups, (5) add vertical line spaces and R
comments (i.e., #), and (6) test the validity of the
concatenated expression and the modular sub-expressions.
Provides a generic infrastructure for creating and using registries.
Regularized (polychotomous) logistic regression
by Gibbs sampling. The package implements subtly different
MCMC schemes with varying efficiency depending on the data type
(binary v. binomial, say) and the desired estimator (regularized maximum
likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a
unified interface.
The package provides tools for
(1) nonparametric regression (kernel, local linear),
(2) semiparametric regression (single index, additive models), and
(3) quantile regression (linear, kernel)
Functions to fit Gaussian linear model by maximising the
residual log likelihood where the covariance structure can be
written as a linear combination of known matrices.  Can be used
for multivariate models and random effects models.  Easy
straight forward manner to specify random effects models,
including random interactions. Code now optimised to use
Sherman Morrison Woodbury identities for matrix inversion in
random effects models. We've added the ability to fit models
using any kernel as well as a function to return the mean and
covariance of random effects conditional on the data (BLUPs).
The expander functions rely on the mathematics developed for the Hessian-definiteness invariance theorem for linear projection transformations of variables, described in authors' paper, to generate the full, high-dimensional gradient and Hessian from the lower-dimensional derivative objects. This greatly relieves the computational burden of generating the regression-function derivatives, which in turn can be fed into any optimization routine that utilizes such derivatives. The theorem guarantees that Hessian definiteness is preserved, meaning that reasoning about this property can be performed in the low-dimensional space of the base distribution. This is often a much easier task than its equivalent in the full, high-dimensional space. Definiteness of Hessian can be useful in selecting optimization/sampling algorithms such as Newton-Raphson optimization or its sampling equivalent, the Stochastic Newton Sampler. Finally, in addition to being a computational tool, the regression expansion framework is of conceptual value by offering new opportunities to generate novel regression problems.
Performs Random Subspace Method (RSM) for high-dimensional linear regression to obtain variable importance measures. The final model is chosen based on validation set or Generalized Information Criterion.
For a sequence of event occurence times, we are interested in
finding subsequences in it that are too "regular". We define regular as being
significantly different from a homogeneous Poisson process. The departure from
the Poisson process is measured using a L1 distance. See Di and Perlman 2007
for more details.
Functions for unary and binary regression tests
Functions for the detection of footprints of selection on
dense SNP data using Extended Homozygosity Haplotype (EHH)
based tests. The package includes computation of EHH, iHS
(within population) and Rsb (across pairs of populations)
statistics. Various plotting functions are also included to
facilitate visualization and interpretation of the results.
Item analysis with alpha standard error and principal axis
factoring for continuous variable scales (with plots).
relaimpo provides several metrics for assessing relative importance in linear models. These can be printed, plotted and bootstrapped. The recommended metric is lmg, which provides a decomposition of the model explained variance into non-negative contributions. There is a version of this package available that additionally provides a new and also recommended metric called pmvd. If you are a non-US user, you can download this extended version from Ulrike Groempings web site.
Data structures and algorithms for k-ary relations with
arbitrary domains, featuring relational algebra, predicate functions,
and fitters for consensus relations.
package relax contains some functions for report
writing, presentation, and programming: relax(), tangleR(),
weaveR(), (g)slider(). "relax" is written in R and Tcl/Tk.
relax creates a new window (top level Tcl/Tk widget) that consists
of two text fields and some buttons and menus.
Text (chunks) and code (chunks) are inserted in the upper text field (report field).
Code chunks are evaluated by clicking on EvalRCode.
Results are shown in the lower text field (output field) and
will be transferred to the report field by pressing on Insert.
In this way you get correct reports. These reports can be
loaded again in cause of presentation, modification and result checking.
tangleR() and weaveR() implement a plain kind of tangling
and weaving. gslider() and slider() are designed to define sliders for interactive
experiments in a simple way.
The syntax rules of code chunks and text chunks are defined by
the noweb system proposed by Norman Ramsey
(http://www.eecs.harvard.edu/~nr/noweb/intro.html).
Extends the glmnet package with "relaxation", done by running glmnet once on the entire predictor matrix, then again on each different subset of variables from along the regularization path. Relaxation may lead to improved prediction accuracy for truly sparse data generating models, as well as fewer false positives (i.e. fewer noncontributing predictors in the final model). Penalty may be lasso (alpha = 1) or elastic net (0 < alpha < 1). For this version, family may be "gaussian" or "binomial" only. Takes advantage of fast FORTRAN code from the glmnet package.
Relaxed Lasso is a generalisation of the Lasso shrinkage
technique for linear regression. Both variable selection and
parameter estimation is achieved by regular Lasso, yet both
steps do not necessarily use the same penalty parameter. The
results include all standard Lasso solutions but allow often
for sparser models while having similar or even slightly better
predictive performance if many predictor variables are present.
The package depends on the LARS package.
R functions for the comparison of distributions.
This includes nonparametric estimation of the relative distribution
PDF and CDF and numerical summaries as described in
"Relative Distribution Methods in the Social Sciences"
by Mark S. Handcock and Martina Morris,
Springer-Verlag, 1999, Springer-Verlag, ISBN 0387987789
Functions for estimating parameters in software reliability models.
Only infinite failure models are implemented so far.
A variety of tools useful for performing structural
reliability analysis, such as with structure function and
system signatures.  Plans to expand more widely.
A collection of utilities for some reliability
models/probability distributions.
Functions to facilitate inference on the relative importance of predictors in a linear or generalized linear model, and a couple of useful Tcl/Tk widgets.
A set of tools to explore the behaviour statistics used for forensic DNA interpretation when close relatives are involved. The package also offers some useful tools for exploring other forensic DNA situations.
Various functions for relative survival analysis.
Classes and functions for analyzing the performance of portfolios relative to a benchmark.
remix provides remix, a quick and easy function for
describing datasets. It can be view as a mix of cast (in
package reshape) and summary.formula (in package Hmisc).
Implements TRACDS (Temporal Relationships
between Clusters for Data Streams), a generalization of
Extensible Markov Model (EMM). TRACDS adds a temporal or order model
to data stream clustering by superimposing a dynamically adapting
Markov Chain. Also provides an implementation of EMM (TRACDS on top of tNN
data stream clustering). Development of this
package was supported in part by NSF IIS-0948893 and R21HG005912 from
the National Human Genome Research Institute.
remMap is developed for fitting multivariate response regression models under the high-dimension-low-sample-size setting
Empirical orthogonal teleconnections in R.
'remote' is short for "R(-based) EMpirical Orthogonal TEleconnections".
It implements a collection of functions to facilitate empirical
orthogonal teleconnection analysis. Empirical Orthogonal Teleconnections
(EOTs) denote a regression based approach to decompose spatio-temporal
fields into a set of independent orthogonal patterns. They are quite
similar to Empirical Orthogonal Functions (EOFs) with EOTs producing
less abstract results. In contrast to EOFs, which are orthogonal in both
space and time, EOT analysis produces patterns that are orthogonal in
either space or time.
Peaks Over Threshold (POT) or 'methode du renouvellement'. The distribution for the exceedances can be chosen, and heterogeneous data (including historical data or block data) can be used in a Maximum-Likelihood framework.
Provides an R interact to the NCBI's EUtils API allowing
users to search databases like genbank and pubmed, process the resulting
files and pull data into their R sessions.
An R interface to the Encyclopedia of Life API. Includes functions for downloading and extracting information off the EOL pages.
Tools for performing the leaf reordering for the dendrogram that preserves the hierarchical clustering result and at the same time tries to group instances from the same class together.
Global tests for expression data of high-dimensional sets of
molecular features.
Estimation of Bayes and local Bayes false discovery rates for
replicability analysis.
Supplies classes and routines to convert data to and from EpiJSON files. This package provides conversion functions for data.frame, sp and obkData.
Test for effects of  both individual factors and their interaction on  replicated spatial patterns in a two factorial design.
A common problem faced by journal reviewers and authors is the
question of whether the results of a replication study are consistent with
the original published study. One solution to this problem is to examine
the effect size from the published study and generate the range of effect
sizes that could reasonably be obtained (due to random sampling) in a
replication attempt (i.e., calculate a replication interval). If a
replication effect size falls outside the replication interval then that
value could not have occurred to due the effects of sampling error alone.
Alternatively, if a replication effect size falls within the replication
interval then the replication results could have reasonably occurred due to
the effects of sampling error alone. This package has functions that
calculate the replication interval for two different types of effect sizes,
namely correlation (i.e., r) and the standardized mean difference
(i.e., d-value).
Tools to load 'R' packages
and automatically generate BibTeX files citing them as well as load
plain-text and 'Excel' formatted data stored on 'Dropbox', 'GitHub', and
from other sources.
This is an R data manager meant to avoid manual storage/retrieval of R data to/from the file system. It builds one (or more) centralized repository where R objects are stored with annotations, tags, dependency notes, provenance traces. It also provides navigation tools to easily locate, load and edit previously stored resources.
Fits regression models to repeated ordinal response
variables, using generalized estimating equations implemented
in package gee.
Create Microsoft Word document (>=2007),
Microsoft Powerpoint document (>=2007) and HTML documents from R. There are
several features to let you format and present R outputs ; e.g. Editable
Vector Graphics, functions for complex tables reporting, reuse of corporate
template document (*.docx and *.pptx). You can use the package as a tool
for fast reporting and as a tool for reporting automation. The package does
not require any installation of Microsoft product to be able to write
Microsoft files (docx and pptx).
External jars required for package ReporteRs. ReporteRs is an
R package for creating Microsoft Word document (>=2007), Microsoft
Powerpoint document (>=2007) and HTML documents from R.
The reportr package provides a system for reporting messages, which provides certain useful features over the standard R system, such as the incorporation of output consolidation, message filtering, expression substitution, automatic generation of stack traces for debugging, and conditional reporting based on the current "output level".
reportRx is a set of tools that integrates with LaTeX and knitr to
automatically generate generate reproducible clinical reports. Fuctions to
automatically produce demoraphic tables, outcome summaries, univariate and
multivariate analysis results and more are included.
Assists in writing reports and
presentations by providing a frame work that brings together
existing R, LaTeX/.docx and Pandoc tools. The package is
designed to be used with RStudio, MiKTex/Tex Live/LibreOffice,
knitr, knitcitations, Pandoc and pander. The user will want to
download these free programs/packages to maximize the
effectiveness of the reports package.  Functions with two
letter names are general text formatting functions for copying
text from articles for inclusion as a citation.
These functions are especially helpful when writing reports of data analysis using Sweave.
An R Interface to EPP-lab v1.0. EPP-lab is a Java program for projection pursuit using genetic algorithms written by Alain Berro and S. Larabi Marie-Sainte and is included in the package.
Methods to calculate resource adequacy
metrics in power systems, which are based on the notion of
loss-of-load probability (LOLP) and include the treatment of conventional
and variable renewable generators.
Contains workhorse function jrparams(), as well as two
helper functions Mboxtest() and JRsMahaldist(), and four
example data sets.
The reproducer R package includes data analysis functions and data sets (e.g., related to software defect prediction) to streamline reproducible research in software engineering.
This package contains the function run.eqs() which calls
an EQS script file, executes the EQS estimation, and, finally,
imports the results as R objects. These two steps can be
performed separately: call.eqs() calls and executes EQS,
whereas read.eqs() imports existing EQS outputs as objects into
R. It requires EQS 6.2 (build 98 or higher).
General purpose R client for 'ERDDAP' servers. Includes
functions to search for 'datasets', get summary information on
'datasets', and fetch 'datasets', in either 'csv' or 'netCDF' format.
'ERDDAP' information: http://upwell.pfeg.noaa.gov/erddap/information.html.
Bootstrap, permutation tests, and other resampling functions,
featuring easy-to-use syntax.
This package implements functions for spectral
similarity/dissimilarity analysis and memory-based learning (MBL) for
non-linear modelling in complex spectral datasets. MBL is
also known as local modelling in the chemometrics literature.
Measure single-storage water supply system performance using resilience, reliability,
and vulnerability metrics; assess storage-yield-reliability relationships;
determine no-fail storage with sequent peak analysis; optimize release
decisions using deterministic and stochastic dynamic programming; evaluate
inflow persistence using the Hurst coefficient.
Reshape lets you flexibly restructure and aggregate data using just two functions: melt and cast.
Flexibly restructure and aggregate data using just two
functions: melt and dcast (or acast).
A tool for learning how to use the functions, melt,
acast/dcast, and ddply.
electrical properties of resistor networks.
Resource Selection (Probability) Functions for
use-availability wildlife data as described in
Lele and Keim (2006, Ecology 87, 3021--3028),
and Lele (2009, J. Wildlife Management 73, 122--127).
Contains two functions that query AuriQ Systems' Essentia Database and return the results in R. 'essQuery' takes a single Essentia command and captures the output in R, where you can save the output to a dataframe or stream it directly into additional analysis. 'read.udb' takes a file containing any number of Essentia commands and captures the output of the specified statements into R dataframes. Essentia can be downloaded for free at http://www.auriq.com/documentation/source/install/index.html.
Contains easy scripts which can be used to quickly create GUI windows for 'Rcmdr' Plugins. No knowledge about Tcl/Tk is required to make use of these scripts (These scripts are a generalisation of the template scripts in the 'RcmdrPlugin.BiclustGUI' package).
Provides the user with functions to develop their trading strategy,
uncover actionable trading ideas, and monitor consensus shifts with
crowdsourced earnings and economic estimate data directly from
<www.estimize.com>. Further information regarding the web services this
package invokes can be found at <www.estimize.com/api>.
The restlos package provides algorithms for robust estimation of location (mean and mode) and scatter based on minimum spanning trees (pMST), self-organizing maps (Flood Algorithm), Delaunay triangulations (RDELA), and nested minimum volume convex sets (MVCH). The functions are also suitable for outlier detection.
Debugging with restore points instead of break points. A restore
point stores all local variables when called inside a function. The stored
values can later be retrieved and evaluated in a modified R console that
replicates the function's environment. To debug step by step, one can
simply copy & paste the function body from the R script. Particularly
convenient in combination with RStudio. See the github page for a tutorial.
Reaction time analysis by maximum likelihood
Reconstructs retinae by morphing a flat surface with
cuts (a dissected flat-mount retina) onto a curvilinear surface (the a
standard retinal shape). It can estimate the position of a point on the
intact adult retina to within 8 degrees of arc (3.6% of nasotemporal axis).
The coordinates in reconstructed retinae can be transformed to visuotopic
coordinates.
A collection of tools to import and structure the (currently) single-season
event, game-log, roster, and schedule data available from http://www.retrosheet.org.
In particular, the event (a.k.a. play-by-play) files can be especially difficult to parse.
This package does the parsing on those files, returning the requested data in the most
practical R structure to use for sabermetric or other analyses.
An interface to NCBI databases such as PubMed, GenBank, or GEO
powered by the Entrez Programming Utilities (EUtils). The nine EUtils
provide programmatic access to the NCBI Entrez query and database
system for searching and retrieving biological data.
Simplified scenario testing and sensitivity analysis with R via a
generalized function for one-factor-at-a-time (OFAT) sensitivity analysis,
evaluation of parameter sets and (sampled) parameter permutations. Options
for formatting output and parallel processing are also provided.
Computation of (direct and indirect) revealed preferences, fast non-parametric tests of rationality axioms (WARP, SARP, GARP), simulation of axiom-consistent data, and detection of axiom-consistent subpopulations.
An implementation of the reverse ecology framework. Reverse ecology
refers to the use of genomics to study ecology with no a priori assumptions
about the organism(s) under consideration, linking organisms to their
environment. It allows researchers to reconstruct the metabolic networks and
study the ecology of poorly characterized microbial species from their
genomic information, and has substantial potentials for microbial community
ecological analysis.
Adjusts the weights of survey respondents so that the
marginal distributions of certain variables fit more closely to
those from a more precise source (e.g. Census Bureau's data).
A friendly interface for the construction of regular expressions.
This package wraps some of the matrix exponentiation utilities from EXPOKIT (http://www.maths.uq.edu.au/expokit/), a FORTRAN library that is widely recommended for matrix exponentiation (Sidje RB, 1998. "Expokit: A Software Package for Computing Matrix Exponentials." ACM Trans. Math. Softw. 24(1): 130-156).  EXPOKIT includes functions for exponentiating both small, dense matrices, and large, sparse matrices (in sparse matrices, most of the cells have value 0).  Rapid matrix exponentiation is useful in phylogenetics when we have a large number of states (as we do when we are inferring the history of transitions between the possible geographic ranges of a species), but is probably useful in other ways as well.
Provides an interface to the Facebook API.
This package facilitates searching for and downloading seismic time series in miniSEED format (a minimalist version of the Standard for the Exchange of Earthquake Data) from International Federation of Digital Seismograph Networks repositories. This package can also be used to gather information about seismic networks (stations, channels, locations, etc) and find historical earthquake data (origins, magnitudes, etc).
An R implementation of the random ferns classifier by Ozuysal et al., modified for generic and multi-label classification and featuring OOB error approximation and importance measure.
RFGLS  uses a generalized least-squares method to perform single-marker association analysis,
in datasets of nuclear families containing parents, twins, and/or adoptees
Variable selection tools for groups of variables and functional data based on a new grouped variable importance with random forests.
An interface to 'figshare' (http://figshare.com), a scientific repository to archive and assign 'DOIs' to data, software, figures, and more.
A file set refers to a set of files located in one or more directories on the file system.  This package provides classes and methods to locate, setup, subset, navigate and iterate such sets.  The API is designed such that these classes can be extended via inheritance to provide a richer API for special file formats.  Moreover, a specific name format is defined such that filenames and directories can be considered to have full names which consists of a name followed by comma-separated tags.  This adds additional flexibility to identify file sets and individual files.  NOTE: This package's API should be considered to be in an beta stage.  Its main purpose is currently to support the aroma.* packages, where it is one of the main core components; if you decide to build on top of this package, please contact the author first.
Japanese stock market from Yahoo!-finance-Japan
A programmatic interface to http://www.fishbase.org, re-written based on an accompanying 'RESTful' API.
Access tables describing over 30,000 species of fish, their biology, ecology, morphology, and more.
This package also supports experimental access to http://www.sealifebase.org data, which contains nearly
200,000 species records for all types of aquatic life not covered by 'FishBase.'
A programmatic interface to openfisheries.org. This package is
part of the rOpenSci suite (http://ropensci.org)
R estimation and inference for linear models.  Estimation
is for general scores and a library of commonly used score
functions is included.
RFLPtools provides functions to analyse DNA fragment samples
(i.e. derived from RFLP-analysis) and standalone BLAST report files
(i.e. DNA sequence analysis).
A collection of tools for multivariate analysis of metabolomics
data, which includes several preprocessing methods (normalization, scaling)
and various exploration and data visualization techniques (Principal
Components Analysis and Multi Dimensional Scaling). The core of the package
is the Random Forest algorithm used for the construction, optimization and
validation of classification models with the aim of identifying potentially
relevant biomarkers.
R access to the FOAAS (F... Off As A Service) web service is provided.
Graphics for statistics on a sphere, as applied to geological fault data, crystallography, earthquake focal mechanisms, radiation patterns, ternary plots and geographical/geological maps.  Non-double couple plotting of focal spheres and source type maps are included for statistical analysis of moment tensors.
RForcecom provides the connection to Force.com and Salesforce.com from R.
Contains all the code examples in the book "R for
Dummies" (1st edition). You can view the table of contents as well as the sample code for each chapter.
A modified version (with great help from Ian J. Wilson) of Ian J. Wilson's program BATWING for calculating forensic trace-suspect match probabilities.
Estimate significance of importance metrics
for a Random Forest model by permuting the response
variable. Produces null distribution of importance
metrics for each predictor variable and p-value of
observed.
An R interface to a modified version of the Free Evolutionary Algorithm Kit FrEAK. FrEAK is a toolkit written in Java to design and analyze evolutionary algorithms. Both the R interface and an extended version of FrEAK are contained in the RFreak package. For more information on FrEAK see http://sourceforge.net/projects/freak427/.
Utilities for Random Forest model selection, class balance
correction, significance test, cross validation and partial dependency
plots.
Provides functions for accessing and retrieving data from the
Google Analytics APIs (https://developers.google.com/analytics/). Supports
OAuth 2.0 authorization. Package provides access to the Management, Core
Reporting, Multi-Channel Funnels Reporting, Real Time Reporting and
Metadata APIs. Access to all the Google Analytics accounts which the user
has access to. Auto-pagination to return more than 10,000 rows of the
results by combining multiple data requests. Also package provides
shiny app to explore the core reporting API dimensions and metrics.
This package was created to analyze multi-level one-way
experimental designs. It is designed to handle vectorized
observation and factor data where there are unequal sample
sizes and population variance homogeneity can not be assumed.
To conduct the Gabriel test, create two vectors: one for your
observations and one for the factor level of each observation.
The function, rgabriel, conduct the test and save the output as
a vector to input into the gabriel.plot function, which produces
a confidence interval plot for Multiple Comparison.
This package implements a Gamma convolution model for
background correction.
This package provides functions to interact with the
Gaug.es API. Gaug.es is a web analytics service, like Google
analytics. You have to have a Gaug.es account to use this package.
A programmatic interface to the Web Service methods
provided by the Global Biodiversity Information Facility ('GBIF').
'GBIF' is a database of species occurrence records from sources all
over the globe. 'rgbif' includes functions for searching for
taxonomic names, retrieving information on data providers,
getting species occurrence records, and getting counts of
occurrence records.
We utilize  approximate Bayesian machinery to fit two-level conjugate hierarchical models on overdispersed Gaussian, Poisson, and Binomial data and evaluates whether the resulting approximate Bayesian interval estimates for random effects meet the nominal confidence levels via frequency coverage evaluation. The data that Rgbp assumes comprise observed sufficient statistic for each random effect, such as an average or a proportion of each group, without population-level data.  The approximate Bayesian tool equipped with the adjustment for density maximization produces approximate point and interval estimates for model parameters including second-level variance component, regression coefficients, and random effect. For the Binomial data, the package provides an option to produce  posterior samples of all the model parameters via the acceptance-rejection method. The package provides a quick way to evaluate coverage rates of the resultant Bayesian interval estimates for random effects via a parametric bootstrapping, which we call frequency method checking.
Multi-block data analysis concerns the analysis of several sets of variables (blocks) observed on the same group of individuals. The main aims of the RGCCA package are: (i) to study the relationships between blocks and (ii) to identify subsets of variables of each block which are active in their relationships with the other blocks.
Thin plate spline fitting and prediction
Provides bindings to Frank Warmerdam's Geospatial Data Abstraction Library (GDAL) (>= 1.6.3) and access to projection/transformation operations from the PROJ.4 library. The GDAL and PROJ.4 libraries are external to the package, and, when installing the package from source, must be correctly installed first. Both GDAL raster and OGR vector map data can be imported into R, and GDAL raster data and OGR vector data exported. Use is made of classes defined in the sp package. Windows and Mac Intel OS X binaries (including GDAL, PROJ.4 and Expat) are provided on CRAN.
A method 'generate' is implemented in this package for the random
generation of vector time series according to models obtained by 'RMAWGEN',
'vars' or other packages.  This package was created to generalize the
algorithms of the RMAWGEN package for the analysis and generation of any
environmental vector time series.
The method 'generate' is extended for spatial multi-site
stochastic generation of daily precipitation. It generates precipitation
occurrence in several sites using logit regression (Generalized Linear
Models) and D.S. Wilks' approach (Journal of Hydrology, 1998).
A genetic algorithm plus derivative optimizer.
Connectors to online and offline sources for taking IP addresses and geolocating them to country, city, timezone and other geographic ranges. For individual connectors, see the package index.
Interface to Geometry Engine - Open Source (GEOS) using the C API for topology operations on geometries. The GEOS library is external to the package, and, when installing the package from source, must be correctly installed first. Windows and Mac Intel OS X binaries are provided on CRAN.
Create, read and write GEXF (Graph Exchange XML Format) graph files (used in Gephi and others). Using the XML package, it allows the user to easily build/read graph files including attributes, GEXF viz attributes (such as color, size, and position), network dynamics (for both edges and nodes) and edge weighting. Users can build/handle graphs element-by-element or massively through data-frames, visualize the graph on a web browser through "sigmajs" (a javascript library) and interact with the igraph package.
The rggobi package provides a command-line interface to GGobi, an
interactive and dynamic graphics package. Rggobi complements GGobi's
graphical user interface, providing a way to fluidly transition between
analysis and exploration, as well as automating common tasks.
This package provides some functions to create quizzes
in the GIFT format. This format is used by several Virtual Learning
Environments such as Moodle.
Provides medium to high level functions for 3D interactive graphics, including
functions modelled on base graphics (plot3d(), etc.) as well as functions for
constructing representations of geometric objects (cube3d(), etc.).  Output
may be on screen using OpenGL, or to various standard 3D file formats including
WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.
A programmatic interface to the web service methods
provided by Global Biotic Interactions (GloBI). GloBI provides
access to spatial-temporal species interaction records from
sources all over the world. rglobi provides methods to search
species interactions by location, interaction type, and
taxonomic name. In addition, it supports Cypher, a graph query
language, to allow for executing custom queries on the GloBI
aggregate species interaction dataset.
R interface to the GNU Linear Programming Kit.
GLPK is open source software for solving large-scale linear programming (LP),
mixed integer linear programming (MILP) and other related problems.
Interface for gnuplot
Based on gnuplot_i version 1.11, the GPL code from Nicolas Devillard.
Provides functions for accessing and retrieving data from the
Google Analytics API
This package serves two purposes: (i) Provide a
comfortable R interface to query the Google server for static
maps, and (ii) Use the map as a background image to overlay
plots within R. This requires proper coordinate scaling.
RGP is a simple modular Genetic Programming (GP) system build in
pure R. In addition to general GP tasks, the system supports Symbolic
Regression by GP through the familiar R model formula interface. GP
individuals are represented as R expressions, an (optional) type system
enables domain-specific function sets containing functions of diverse
domain- and range types. A basic set of genetic operators for variation
(mutation and crossover) and selection is provided.
RGP UI provides as modern web-based user interface to the modular
Genetic Programming (GP) system RGP.
Geological Survey of Canada (GSC) functions for exploratory data analysis with applied geochemical data, with special application to the estimation of background ranges and identification of outliers, 'anomalies', to support mineral exploration and environmental studies.  Additional functions are provided to support analytical data QA/QC, ANOVA for investigations of field sampling and analytical variability, and utility tasks.  NOTE: function caplot() for concentration-area plots employs package 'akima', however, 'akima' is only licensed for not-for-profit use.  Therefore, not-for-profit users of 'rgr' will have to independently make package 'akima' available through library(....); and use of function caplot() by for-profit users will fail.
Data and Functions from the book R Graphics, Second Edition. There is a function to produce each figure in the book, plus several functions, classes, and methods defined in Chapter 8.
Interpreted interface between GRASS 7 geographical
information system and R, based on starting R from within the GRASS GIS
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 6, for which
spgrass6 should be used.
Facilities in the R language for programming
graphical interfaces using Gtk, the Gimp Tool Kit.
DBI/RJDBC interface to h2 database. h2 version 1.3.175 is included.
An R interface to the 'Handsontable' JavaScript library, which is a
minimalist Excel-like data grid editor.
An R interface for the HealthData.gov data API.  For each data resource, you can filter results (server-side) to select subsets of data.
Evaluating risk (that a patient arises a side effect) during hospitalization is the main purpose of this package. Several methods (Parametric, non parametric and De Vielder estimation) to estimate the risk constant (R) are implemented in this package. There are also functions to simulate the different models of this issue in order to quantify the previous estimators. It is necessary to read at least the first six pages of the report to understand the topic.
Function of apply style using 'MPI' provides better 'HPC' environment on R.
and this package supports long vector, can deal with slightly big data.
Control the number of threads on 'BLAS' (Aka 'GotoBLAS', 'ACML' and 'MKL').
and possible to control the number of threads in 'OpenMP'.
get a number of logical cores and physical cores if feasible.
rHpcc is an R package providing an Interface between R and
HPCC.Familiarity with ECL (Enterprise Control Language) is a
must to use this package.HPCC is a massive parallel-processing
computing platform that solves Big Data problems.ECL is the
Enterprise Control Language designed specifically for huge data
projects using the HPCC platform.Its extreme scalability comes
from a design that allows you to leverage every query you
create for re-use in subsequent queries as needed. To do this,
ECL takes a dictionary approach to building queries wherein
each ECL definition defines an Attribute. Each previously
defined Attribute can then be used in succeeding ECL Attribute
definitions as the language extends itself as you use it.
Methods and tools for performing Heart Rate Variability analysis
of ECG records. RHRV allows to import data files containing heartbeat positions
in the most broadly used formats; eliminating outliers or spurious points
present in the time series with unacceptable physiological values; plotting HRV
data and performing time domain, frequency domain and nonlinear HRV analysis.
This package offers functions to perform regularized
Hotelling's T-square test for pathway or gene set analysis. The
package is tailored for but not limited to proteomics data, in
which sample sizes are often small, a large proportion of the
data are missing and/or correlations may be present.
DEPRECATED. Do not start building new projects based on this package. Cross-platform alternatives are the following packages: bigmemory (CRAN), ff (CRAN), BufferedMatrix (Bioconductor).  The main usage of it was inside the aroma.affymetrix package. (The package currently provides a class representing a matrix where the actual data is stored in a binary format on the local file system.  This way the size limit of the data is set by the file system and not the memory.)
This package provides a set of tools for conducting exact
or approximate randomization-based inference for experiments of
arbitrary design. The primary functionality of the package is
in the generation, manipulation and use of permutation matrices
implied by given experimental designs. Among other features,
the package facilitates estimation of average treatment
effects, constant effects variance estimation, randomization
inference for significance testing against sharp null
hypotheses and visualization of data and results.
Computes attributable effects based confidence set, permutation test confidence set, and asymptotic confidence interval for the average treatment effect on a binary outcome.
The Diceware method can be used to generate strong passphrases.
In short, you roll a 6-faced dice 5 times in a row, the number obtained is
matched against a dictionary of easily remembered words. By combining together 7
words thus generated, you obtain a password that is relatively easy to remember,
but would take several millions years (on average) for a powerful computer to guess.
Computes rarefaction curves, cumulated and mean species
richness. Compares these estimates by means of randomization
tests.
Linear and logistic ridge regression for small data sets
and genome-wide SNP data
This package implements ridge fusion methodology for inverse covariance matrix estimation for use in quadratic discriminant analysis.  The package also contains function for model based clustering using ridge fusion for inverse matrix estimation, as well as tuning parameter selection functions.  We have also implemented QDA using joint inverse covariance estimation.
An interface to iDigBio's search API that allows downloading
specimen records. Searches are returned as a data.frame. Other functions
such as the metadata end points return lists of information. iDigBio is a US
project focused on digitizing and serving museum specimen collections on the
web. See <https://www.idigbio.org> for information on iDigBio.
An extension of the Kruskal-Wallis Test that allow
selection of arbitrary reference group. Also provide Mean Ridit
for each group. Mean Ridit of a group is an estimate of
probability a random observation from that group will be
greater than or equal to a random observation from reference
group.
RIFS package provides functionality for generating &
plotting prefractals in R^n with various protofractal sets and
partition coefficient for iterative segments
Interactive data visualization supporting linked graphs can help users easily
explore data and gain valuable insights and enables such visualization and interactive
re-analysis using HTML5 canvas and JavaScript. Its R API is designed to create a seamless
analysis, visualization, and re-analysis workflow for interactive visualization and analysis.
Since HTML5 canvas and JavaScript is supported in virtually all modern web browsers, the
visualizations can be delivered to almost any device/platform for presentation purposes.
Provides functions to read 'ImageJ' (http://imagej.nih.gov/ij/)
Region of Interest (ROI) files, to plot the ROIs and to convert them to
'spatstat' (http://spatstat.org/) spatial patterns.
Cloudera 'Impala', which is a massively parallel processing (MPP) SQL query engine runs natively in Apache Hadoop. 'RImpala' facilitates the connection and execution of distributed queries through 'R'. 'Impala' supports JDBC integration which 'RImpala' utilizes to establish the connection between 'R' and 'Impala'. Thanks to Mu Sigma for their continued support throughout the development of the package.
A programmatic interface to the
API provided by the iNaturalist website.
Index structures allow quickly accessing elements from
large collections. While btree are optimized for disk databases
and ttree for ram databases we use hybrid static indexing which
is quite optimal for R.
C++ classes to embed R in C++ applications
The 'RInside' packages makes it easier to have "R inside" your C++ application
by providing a C++ wrapper class providing the R interpreter.

As R itself is embedded into your application, a shared library build of R
is required. This works on Linux, OS X and even on Windows provided you use
the same tools used to build R itself.

Numerous examples are provided in the eight subdirectories of the examples/
directory of the installed package: standard, mpi (for parallel computing)
qt (showing how to embed 'RInside' inside a Qt GUI application), wt (showing
how to build a "web-application" using the Wt toolkit), armadillo (for
'RInside' use with 'RcppArmadillo') and eigen (for 'RInside' use with 'RcppEigen').
The example use GNUmakefile(s) with GNU extensions, so a GNU make is required
(and will use the GNUmakefile automatically).

Doxygen-generated documentation of the C++ classes is available at the
'RInside' website as well.
Functions to calculate several ecological indices of individual and population niche width
(Araujo's E, clustering and pairwise similarity among individuals, IS, Petraitis' W, and Roughgarden's
WIC/TNW) to assess individual specialization based on data of resource use. Resource use can be
quantified by counts of categories, measures of mass/lenght or proportions. Monte Carlo resampling
procedures are available for hypothesis testing against multinomial null models.
Streamlined data import and export by making assumptions that the user is probably willing to make: 'import()' and 'export()' determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., 'stringsAsFactors=FALSE'), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate.
Functions for the analysis of Quaternary science data, including
constrained clustering, WA, WAPLS, IKFA, MLRC and MAT transfer
functions, and stratigraphic diagrams.
A package including various functions for image processing and analysis. With this package is possible to process and analyse RGB, LAN (multispectral) and AVIRIS (hyperspectral) images. This packages also provides functions for reading JPEG files, extracted from the archived 'rimage' package.
Risk regression models for survival analysis with and without
competing risks.
Compute time-dependent Incident/dynamic accuracy measures
(ROC curve, AUC, integrated AUC )from censored survival data
under proportional or non-proportional hazard assumption of
Heagerty & Zheng (Biometrics, Vol 61 No 1, 2005, PP 92-105).
Implements efficient simulation procedures to estimate tail loss probabilities and conditional excess for a stock portfolio. The log-returns are assumed to follow a t-copula model with generalized hyperbolic or t marginals.
A set of tools to extract bibliographic content from the National Center for Biotechnology Information (NCBI) databases, including PubMed. The name RISmed is a portmanteau of RIS (for Research Information Systems, a common tag format for bibliographic data) and PubMed.
This package implements the simulation and regression of
integrated Isothermal Titration Calorimetry (ITC) data using
the most commonly used one-to-one binding reaction model.
A simple yet powerful script editor built natively in R with tcltk.
Finds a robust instrumental variables estimator using a
high breakdown point S-estimator of multivariate location
and scatter matrix.
Functions for reading, analysing and plotting river networks.
For this package, river networks consist of sections and nodes with associated attributes,
e.g. to characterise their morphological, chemical and biological state.
The package provides functions to read this data from text files, to analyse the network
structure and network paths and regions consisting of sections and nodes that fulfill
prescribed criteria, and to plot the river network and associated properties.
Sankey plots are a type of diagram that is convenient to
illustrate how flow of information, resources etc. separates and joins,
much like observing how rivers split and merge. For example, they can be
used to compare different clusterings.
This R package is a flexible and efficient tool to
visualise both quantitative and qualitative data from river surveys.
It can be used to produce diagrams with the topological structure of
the river network.
This package is devoted to the IVIVC linear level A with
numerical deconvolution method. The latter is working for
inequal and incompatible timepoints between impulse and
response curves. A numerical convolution method is also
available. Application domains include pharamaceutical industry
QA/QC and R&D together with academic research.
A tool for undergraduate courses in open-channel hydraulics.
Provides functions for computing normal and critical depths, steady-state
water surface profiles (e.g. backwater curves) and unsteady flow
computations (e.g. flood wave routing).
Bayesian analysis of CGH microarrays fitting Hidden Markov
Chain models. The selection of the number of states is made via
their posterior probability computed by Reversible Jump Markov
Chain Monte Carlo Methods. Also returns probabilistic common
regions for gains/losses.
Jade is a high performance template engine heavily influenced by
Haml and implemented with JavaScript for node and browsers.
Low-level interface to Java VM very much like .C/.Call and friends. Allows creation of objects, calling methods and accessing fields.
RJDBC is an implementation of R's DBI interface using JDBC as a back-end. This allows R to connect to any DBMS that has a JDBC driver.
A series of useful functions, some available in different
forms in other packages, but which have been extended, sped up, or
otherwise modified in some way considered useful to the author.
R-interface to gene drop programs from Alun Thomas' Java Programs for Statistical Genetics and Computational Statistics (JPSGCS)
R interface to statistical database organized by Japanese government (http://statdb.nstac.go.jp/)
Provides functions to retrieve data and metadata from providers
that disseminate data by means of SDMX web services.
SDMX (Statistical Data and Metadata eXchange) is a standard that
has been developed with the aim of simplifying the exchange of
statistical information.
More about the SDMX standard and the SDMX Web Services
can be found at: http://sdmx.org .
Converts R object into JSON objects and vice-versa
This is a package that allows conversion to and from
data in Javascript object notation (JSON) format.
This allows R objects to be inserted into Javascript/ECMAScript/ActionScript code
and allows R programmers to read and convert JSON content to R objects.
This is an alternative to rjson package. Originally, that was too slow for converting large R objects to JSON
and was not extensible.  rjson's performance is now similar to this package, and perhaps slightly faster in some cases.
This package uses methods and is readily extensible by defining methods for different classes,
vectorized operations, and C code and callbacks to R functions for deserializing JSON objects to R.
The two packages intentionally share the same basic interface. This package (RJSONIO) has many additional
options to allow customizing the generation and processing of JSON content.
This package uses libjson rather than implementing yet another JSON parser. The aim is to support
other general projects by building on their work, providing feedback and benefit from their ongoing development.
Read and write the 'JSON-stat' format (http://json-stat.org) to and
from (lists of) R data frames. Not all features are supported, especially
the extensive metadata features of 'JSON-stat'.
R interface to Python via Jython allowing R to call python
code.
Apache 'Kafka' is an open-source message broker project developed by the Apache Software Foundation which can be thought of as a distributed, partitioned, replicated commit log service.At a high level, producers send messages over the network to the 'Kafka' cluster which in turn serves them up to consumers.See <http://kafka.apache.org/> for more information.Functions included in this package enable:1.Creating 'Kafka' producer 2.Writing messages to a topic 3.Closing 'Kafka' producer 4.Creating 'Kafka' consumer 5.Reading messages from a topic 6.Closing 'Kafka' consumer. The jars required for this package are included in a separate package 'rkafkajars'.Thanks to Mu Sigma for their continued support throughout the development of the package.
The 'rkafkajars' package collects all the external jars required for the 'rkafka' package.
An R interface to KEA (Version 5.0).
KEA (for Keyphrase Extraction Algorithm) allows for extracting
keyphrases from text documents. It can be either used for free
indexing or for indexing with a controlled vocabulary. For more
information see <http://www.nzdl.org/Kea/>.
External jars required for package RKEA.
An interface of R to Klout API v2. It fetches Klout Score for a Twitter Username/handle in real time. Klout is a website and mobile app that uses social media analytics to rank its users according to online social influence via the "Klout Score", which is a numerical value between 1 and 100.  In determining the user score, Klout measures the size of a user's social media network and correlates the content created to measure how other users interact with that content.
Random knn classification and regression are implemented. Random knn based feature selection methods are also included. The approaches are mainly developed for high-dimensional data with small sample size.
Contains function rkt which computes the Mann-Kendall test (MK) and the Seasonal and the Regional Kendall Tests for trend (SKT and RKT) and  Theil-Sen's slope estimator.
This package provides functionality to read files
containing observations which consist of arbitrary key/value
pairs.
Functions and Datasets Required for ST370 class
Allow a user to discover, query and modify data from a LabKey Server.
Standardized methods for calculating common important derived
physical features of lakes including water density based based on
temperature, thermal layers, thermocline depth, lake number, Wedderburn
number, Schmidt stability and others.
Provides an interface to the C implementation of the
random number generator with multiple independent streams
developed by L'Ecuyer et al (2002). The main purpose of this
package is to enable the use of this random number generator in
parallel R applications.
An R interface for C library libeemd for performing the ensemble
empirical mode decomposition (EEMD), its complete variant (CEEMDAN) or the
regular empirical mode decomposition (EMD).
Set of tools for reading, processing and visualizing small set
of LiDAR (Light Detection and Ranging) data for forest inventory applications.
An interface to LINDO API. Supports Linear, Integer, Quadratic, Conic, General Nonlinear, Global, and Stochastic Programming models. To download the trial version LINDO API, please visit www.lindo.com/rlindo.
A series of functions that allow users
to access the LinkedIn API to get information about connections,
search for people and jobs, share updates with their network,
and create group discussions.  For more information about using
the API please visit https://developer.linkedin.com/.
Provides a set of functions for data manipulation with
list objects, including mapping, filtering, grouping, sorting,
updating, searching, and other useful functions. Most functions
are designed to be pipeline friendly so that data processing with
lists can be chained.
Robust fitting of linear model which can take response in matrix form.
Estimates robust rank-based fixed effects and predicts robust random effects in two- and three- level random effects nested models.
Rapid, simulation-based exact (restricted) likelihood ratio tests
for testing the presence of variance components/nonparametric terms for
models fit with nlme::lme(),lme4::lmer(), gamm4::gamm4(), mgcv::gamm() and
SemiPar::spm().
R interface to LTP-Cloud service for Natural Language Processing
in Chinese. For more details please visit http://www.ltp-cloud.com/. Visit
https://github.com/hetong007/rLTP for up-to-date version.
A collection of 'shiny' applications for the R package 'Luminescence'.
These mainly, but not exclusively, include applications for plotting chronometric
data from e.g. luminescence or radiocarbon dating. It further provides access to
bootstraps tooltip and popover functionality and contains the 'jscolor.js' library
with a custom 'shiny' output binding.
RM2 is a simple package that implements functions used in
revenue management and pricing environments.
Uses refined moving average filter based on the optimal and data-driven moving average lag q or smoothing spline to estimate trend and seasonal components, as well as irregularity (residuals) for univariate time series or data.
An EM algorithm to fit Mallows' Models to full or partial
rankings, with or without ties.
This package implements an algorithm family for continuous
optimization called memetic algorithms with local search chains
(MA-LS-Chains). Memetic algorithms are hybridizations of genetic
algorithms with local search methods. They are especially suited
for continuous optimization.
An interface to the software package MARK that constructs input
files for MARK and extracts the output. MARK was developed by Gary White
and is freely available at (http://www.phidot.org/software/mark/downloads/)
but is not open source.
Convert R Markdown documents into a variety of formats.
rmatio is a package for reading and writing Matlab MAT
files from R. The rmatio package supports reading MAT version 4,
MAT version 5 and MAT compressed version 5. The rmatio package can
write version 5 MAT files and version 5 files with variable
compression.
Methods readMat() and writeMat() for reading and writing MAT files.  For user with MATLAB v6 or newer installed (either locally or on a remote host), the package also provides methods for controlling MATLAB (trademark) via R and sending and retrieving data between R and MATLAB.
S3 and S4 functions are implemented for spatial multi-site
stochastic generation of daily time series of temperature and
precipitation. These tools make use of Vector AutoRegressive models (VARs).
The weather generator model is then saved as an object and is calibrated by
daily instrumental "Gaussianized" time series through the 'vars' package
tools. Once obtained this model, it can it can be used for weather
generations and be adapted to work with several climatic monthly time
series.
Functions for fitting, diagnosing and predicting from a
class of Markov models.
RMediation package provides functions to compute confidence
intervals (CIs) for a well-defined nonlinear function of the model
parameters (e.g., product of k coefficients) in single--level and
multilevel structural equation models.
Functions for simple fixed and random effects
meta-analysis for two-sample comparisons and cumulative
meta-analyses. Draws standard summary plots, funnel plots, and
computes summaries and tests for association and heterogeneity
An interface between R and the metasim simulation engine.
Facilitates the use of the metasim engine to build and
run individual based population genetics simulations. The
simulation environment is documented in: Allan
Strand. Metasim 1.0: an individual-based environment for
simulating population genetics of complex population
dynamics. Mol. Ecol. Notes, 2:373-376, 2002. (Please
contact Allan Strand with comments, bug reports, etc).
This version represents a significant alteration of
function names that hopefully increases consistency and
reduces the chances of collisions with other packages
naming conventions.  For a spatially-explicit, but slower, package
with a similar interface, see kernelPop
Methods that simplify the setup of S3 generic functions and S3 methods.  Major effort has been made in making definition of methods as simple as possible with a minimum of maintenance for package developers.  For example, generic functions are created automatically, if missing, and naming conflict are automatically solved, if possible.  The method setMethodS3() is a good start for those who in the future may want to migrate to S4.  This is a cross-platform package implemented in pure R that generates standard S3 methods.
Feasible multivariate GARCH models including DCC, GO-GARCH and Copula-GARCH.
Facilitates the use of data mining algorithms in classification and regression (including time series forecasting) tasks by presenting a short and coherent set of functions. Versions: 1.4.1 new tutorial and more robust version; 1.4 - new classification and regression models/algorithms, with a total of 14 classification and 15 regression methods, including: Decision Trees, Neural Networks, Support Vector Machines, Random Forests, Bagging and Boosting; 1.3 and 1.3.1 - new classification and regression metrics (improved mmetric function); 1.2 - new input importance methods (improved Importance function); 1.0 - first version.
The Rmisc library contains many functions useful for data analysis
and utility operations.
Supervised and unsupervised classification with MIXture MODelling
The Rmixmod package provides model-based clustering by fitting a mixture model (e.g. Gaussian components for quantitative continuous data) to the data and identifying each cluster with one of its components. The number of components can be determined from the data, typically using the BIC criterion. In practice, however, individual clusters can be poorly fitted by Gaussian distributions, and in that case model-based clustering tends to represent one non-Gaussian cluster by a mixture of two or more Gaussian components. If the number of mixture components is interpreted as the number of clusters, this can lead to overestimation of the number of clusters. This is because BIC selects the number of mixture components needed to provide a good approximation to the density. This package, RmixmodCombi, according to \emph{Combining Mixture Components for Clustering} by J.P. Baudry, A.E. Raftery, G. Celeux, K. Lo, R. Gottardo, combines the components of the EM/BIC solution (provided by Rmixmod) hierarchically according to an entropy criterion. This yields a clustering for each number of clusters less than or equal to K. These clusterings can be compared on substantive grounds, and we also provide a way of selecting the number of clusters via a piecewise linear regression fit to the (possibly rescaled) entropy plot.
Sundry discrete probability distributions and helper functions.
A collection of miscellaneous functions for medical data analysis. Visualization
of multidimensional data, diagnostic test calibration, pairwise tests for qualitative variables and outcome simulation.
Connect R with MOA (Massive Online Analysis -
http://moa.cms.waikato.ac.nz) to build classification models and
regression models on streaming data or out-of-RAM data
External jars required for package RMOA. RMOA is a framework to
build data stream models on top of MOA (Massive Online Analysis -
http://moa.cms.waikato.ac.nz)
MongoDB Database interface for R. The interface is provided via Java calls to the mongo-java-driver.
This R package provides an interface to the NoSQL MongoDB database
using the MongoDB C-driver version 0.8.
Programmatic access to the Survey Monkey API <https://developer.surveymonkey.com/>, which currently provides extensive functionality for monitoring surveys and retrieving survey results and some functionality for creating new surveys and data collectors.
An interface to the MOSEK optimization library designed to
solve large-scale mathematical optimization problems. Supports
linear, quadratic and second order cone optimization
with/without integer variables, in addition to the more general
separable convex problems.  Trial and free academic licenses
available at http://www.mosek.com.
Performs probability mass function estimation with
Dirichlet process mixtures of rounded kernels
Rmpfr provides (S4 classes and methods for)
arithmetic including transcendental ("special") functions for
arbitrary precision floating point numbers. To this end, it interfaces to
the LGPL'ed MPFR (Multiple Precision Floating-Point Reliable) Library
which itself is based on the GMP (GNU Multiple Precision) Library.
Rmpi provides an interface (wrapper) to MPI APIs. It also
provides interactive R slave environment.
This package contains functions and S3 methods for spatial
multi-site stochastic generation of daily precipitation. It generates
precipitation occurrence in several sites using Wilks' Approach (1998).
Bugs/comments/questions/collaboration of any kind are warmly welcomed.
Regression modeling, testing, estimation, validation,
graphics, prediction, and typesetting by storing enhanced model design
attributes in the fit.  rms is a collection of functions that
assist with and streamline modeling.  It also contains functions for
binary and ordinal logistic regression models, ordinal models for
continuous Y with a variety of distribution families, and the Buckley-James
multiple regression model for right-censored responses, and implements
penalized maximum likelihood estimation for logistic and ordinary
linear models.  rms works with almost any regression model, but it
was especially written to work with binary or ordinal regression
models, Cox regression, accelerated failure time models,
ordinary linear models,	the Buckley-James model, generalized least
squares for serially or spatially correlated observations, generalized
linear models, and quantile regression.
This package can be used to test any simple null
hypothesis using the root-mean-square goodness of fit test.
Monte Carlo estimation is used to calculate the associated
P-value.
Functions for working with the Tracy-Widom laws and other distributions
related to the eigenvalues of large Wishart matrices.
The tables for computing the Tracy-Widom densities and distribution
functions were computed by Momar Dieng's MATLAB package "RMLab"
(formerly available on his homepage at
http://math.arizona.edu/~momar/research.htm ).
This package is part of a collaboration between Iain Johnstone,
Zongming Ma, Patrick Perry, and Morteza Shahram.  It will soon be
replaced by a package with more accuracy and built-in support for
relevant statistical tests.
Implements 'DBI' Interface to 'MySQL' and 'MariaDB' Databases.
This package is designed to streamline several of the common steps for RNA-seq
analysis, including differential expression and variant discovery.
For the development build, or to contribute changes to this package,
please see our repository at https://bitbucket.org/petersmp/rnaseqwrapper/
GUI to explore high dimensional data (including image data) using graphs as navigational infrastructure.
Image data used as examples in the RnavGraph R package.
See the demos in the RnavGraph package.
Access to data held by the National Biodiversity Network (NBN, www.nbn.org.uk). The NBN acts as a data warehouse for biological records data in the UK and is the UK node of GBIF (Global Biodiversity Information Facility). In this package NBN data is accessed via its web-services.
Provides the libraries of the EUtils operations for the
RNCBI package.
This package contains functions to retrieve, organize, and visualize weather data from the NCEP/NCAR Reanalysis (http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html) and NCEP/DOE Reanalysis II (http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis2.html) datasets.  Data are queried via the Internet and may be obtained for a specified spatial and temporal extent or interpolated to a point in space and time.  We also provide functions to visualize these weather data on a map.  There are also functions to simulate flight trajectories according to specified behavior using either NCEP wind data or data specified by the user.
An interface to the Nexus Class Library which allows parsing
of NEXUS, Newick and other phylogenetic tree file formats. It provides
elements of the file that can be used to build phylogenetic objects
such as ape's 'phylo' or phylobase's 'phylo4(d)'.
This package is a collection of various functions to extract the implied risk neutral density from option.
Within this package the XML-RPC API to NEOS is implemented. This enables the user to pass optimization problems to NEOS and retrieve results within R.
An interface to the NetCDF file format designed by Unidata
for efficient storage of array-oriented scientific data and descriptions.
The R interface is closely based on the C API of the NetCDF library,
and it includes calendar conversions from the Unidata UDUNITS library.
The current implementation supports all operations on NetCDF datasets
in classic and 64-bit offset file formats, and NetCDF4-classic format
is supported for reading and modification of existing files.
Interface to use and access Wilensky's NetLogo (Wilensky 1999) from R using either headless (no GUI) or interactive GUI mode. Provides functions to load models, execute commands, and get values from reporters. Mostly analogous to the NetLogo Mathematica Link http://ccl.northwestern.edu/netlogo/docs/mathematica.html
Provides access to phyloinformatic data in NeXML format.  The
package should add new functionality to R such as the possibility to
manipulate NeXML objects in more various and refined way and compatibility
with 'ape' objects.
A function setVectorSeed() is provided. Its argument
is a numeric vector of an arbitrary nonzero length, whose
components have integer values from [0, 2^32-1]. The input
vector is transformed using AES (Advanced Encryption Standard)
algorithm into an initial state of Mersenne-Twister random
number generator. The function provides a better alternative
to the R base function set.seed(), if the input vector is
a single integer. Initializing a stream of random numbers
with a vector is a convenient way to obtain several streams,
each of which is identified by several integer indices.
This package contains a set of functions for working with
Random Number Generators (RNGs). In particular, it defines a generic
S4 framework for getting/setting the current RNG, or RNG data
that are embedded into objects for reproducibility.
Notably, convenient default methods greatly facilitate the way current
RNG settings can be changed.
It is a dedicated package to WELL pseudo random generators, which were introduced in Panneton et al. (2006), ``Improved Long-Period Generators Based on Linear Recurrences Modulo 2'', ACM Transactions on Mathematical Software. But this package is not intended to be used directly, you are strongly __encouraged__ to use the 'randtoolbox' package, which depends on this package.
Long period linear random number generator WELL19937a by
F. Panneton, P. L'Ecuyer and M. Matsumoto. The initialization
algorithm allows to seed the generator with a
numeric vector of an arbitrary length and uses MRG32k5a by
P. L'Ecuyer to achieve good quality of the initialization. The
output function may be set to provide numbers from the interval
(0,1) with 53 (the default) or 32 random bits. WELL19937a is of
similar type as Mersenne Twister and has the same period.
WELL19937a is slightly slower than Mersenne Twister, but has
better equidistribution and "bit-mixing" properties and faster
recovery from states with prevailing zeros than Mersenne
Twister. All WELL generators with orders 512, 1024, 19937 and
44497 can be found in randtoolbox package.
Provides an R interface to the NiftyReg image registration tools <http://sourceforge.net/projects/niftyreg/>. Linear and nonlinear registration are supported.
An implementation of robust nonnegative matrix factorization (rNMF). The rNMF algorithm decomposes a nonnegative high dimension data matrix into the product of two low rank nonnegative matrices, while detecting and trimming outliers. The main function is rnmf(). The package also includes a visualization tool, see(), that arranges and prints vectorized images.
Client for many 'NOAA' data sources including the 'NCDC'
climate 'API' at http://www.ncdc.noaa.gov/cdo-web/webservices/v2, with
functions for each of the 'API' 'endpoints': data, data categories, data sets,
data types, locations, location categories, and stations. In addition, we
have an interface for 'NOAA' sea ice data, the 'NOAA' severe weather inventory,
'NOAA' Historical Observing 'Metadata' Repository ('HOMR') data,
'NOAA' storm data via 'IBTrACS', and tornado data via the 'NOAA' storm prediction
center.
An interface to the National Oceanic and Atmospheric Administration's Operational Model Archive and Distribution System (NOMADS) that allows R users to quickly and efficiently download global and regional weather model data for processing.  rNOMADS currently supports a variety of models ranging from global weather data to an altitude of 40 km, to high resolution regional weather models, to wave and sea ice models. It can also retrieve archived NOMADS models.  rNOMADS can retrieve binary data in grib format as well as import ascii data directly into R by interfacing with the GrADS-DODS system.
Utility functions to retrieve data from the UK National River Flow
Archive. The package contains R wrappers to the UK NRFA data temporary-API.
There are functions to retrieve stations falling in a bounding box,
to generate a map and extracting time series and general information.
Provides an interface to the OAuth 1.0 specification
allowing users to authenticate via OAuth to the
server of their choice.
Base S4-classes and functions for robust asymptotic statistics.
Methods for analysis of compositional data
including robust methods, imputation, methods to replace rounded zeros, (robust)
outlier detection for compositional data, (robust) principal component analysis for
compositional data, (robust) factor analysis for compositional data,
(robust) discriminant analysis for compositional data (Fisher rule), robust
regression with compositional predictors and (robust) Anderson-Darling
normality tests for compositional data as well as popular log-ratio
transformations (addLR, cenLR, isomLR, and their inverse transformations).
In addition, visualisation and diagnostic tools are implemented as well as
high and low-level plot functions for the ternary diagram.
Robust pairwise correlations based on estimates of scale,
particularly on "FastQn" one-step M-estimate.
Locations problems, M-estimates of coefficients and scale
in linear regression, Weights for bounded influence regression,
Covariance matrix of the coefficient estimates, Asymptotic
relative efficiency of regression M-estimates, Robust testing
in linear models, High breakdown point regression, M-estimates
of covariance matrices, M-estimates for discrete generalized
linear models.
A set of functions to filter time series based on concepts
from robust statistics.
Functions for the determination of optimally robust influence curves and
estimators in case of normal location and/or scale
Functions for the determination of optimally robust influence curves and
estimators for preprocessing omics data, in particular gene expression data.
Calculates periodograms based on (robustly) fitting periodic functions to light curves (irregularly observed time series, possibly with measurement accuracies, occurring in astroparticle physics). Three main functions are included: RobPer calculates the periodogram. Outlying periodogram bars (indicating a period) can be detected with betaCvMfit. Artificial light curves can be generated using the function tsgen. For more details see Thieler, Fried and Rathjens (2013).
Functions for the determination of optimally robust influence curves in case of
linear regression with unknown scale and standard normal distributed errors where the
regressor is random.
This package provides the function to calculate SVD, regularized SVD, robust SVD and robust regularized SVD method. The robust SVD methods use alternating iteratively reweighted least squares methods. The regularized SVD uses generalized cross validation to choose the optimal smoothing parameters.
Data management in hydrology and other fields is facilitated with functions to enter and modify data in a database according to the Observations Data Model (ODM) standard by CUASHI (Consortium of Universities for the Advancement of Hydrologic Science). While this data model has been developed in hydrology, it is also useful for other fields. RObsDat helps in the setup of the database within one of the free database systems MariaDB, PostgreSQL or SQLite. It imports the controlled water vocabulary from the CUASHI web service and provides a smart interface between the analyst and the database: Already existing data entries are detected and duplicates avoided. The data import function converts different data table designs to make import simple. Cleaning and modifications of data are handled with a simple version control system. Variable and location names are treated in a user friendly way, accepting and processing multiple versions. When querying data from the database, it is stored in a spacetime objects within R for subsequent processing.
Functions for conducting robust variance estimation (RVE) meta-regression using both large and small sample RVE estimators under various weighting schemes. These methods are distribution free and provide valid point estimates, standard errors and hypothesis tests even when the degree and structure of dependence between effect sizes is unknown. Also included are functions for conducting sensitivity analyses under correlated effects weighting and producing RVE-based forest plots.
R functions for the computation of the truncated maximum
likelihood and the robust accelerated failure time regression
for gaussian and log-Weibull case.
"Essential" Robust Statistics.
Tools allowing to analyze data with robust methods.  This includes
regression methodology including model selections and multivariate
statistics where we strive to cover the book "Robust Statistics,
Theory and Methods" by 'Maronna, Martin and Yohai'; Wiley 2006.
Robust mixture discriminant analysis (RMDA, Bouveyron & Girard, 2009) allows to build a robust supervised classifier from learning data with label noise. The idea of the proposed method is to confront an unsupervised modeling of the data with the supervised information carried by the labels of the learning data in order to detect inconsistencies. The method is able afterward to build a robust classifier taking into account the detected inconsistencies into the labels.
The Spatial-EM is a new robust EM algorithm for the finite
mixture learning procedures. The algorithm utilizes median-
based location and rank-based scatter estimators to replace sample
mean and sample covariance matrix in each M step, hence enhancing
stability and robustness of the algorithm. To understand more about
this algorithm, read the article
''Yu, K., Dang, X., Bart Jr, H. and Chen, Y. (2015). Robust Model-
based Learning via Spatial-EM Algorithm. IEEE Transactions on
Knowledge and Data Engineering, 27(6), 1670-1682.
doi:10.1109/TKDE.2014.2373355''.
An object oriented solution for robust factor analysis. In the solution, new S4 classes "Fa", "FaClassic", "FaRobust", "FaCov", "SummaryFa" are created.
This package provides robust estimation for generalized
additive models. It implements a fast and stable algorithm in
Wong, Yao and Lee (2013). The implementation also contains
three automatic selection methods for smoothing parameter. They
are designed to be robust to outliers. For more details, see
Wong, Yao and Lee (2013).
Robust methods for high-dimensional data, in particular linear
model selection techniques based on least angle regression and sparse
regression.
A method to fit linear mixed effects models robustly.
Robustness is achieved by modification of the scoring equations
combined with the Design Adaptive Scale approach.
Robust estimation of the generalized log gamma model is provided using Quantile Tau estimator and Weighted Likelihood estimator.
Methods for aggregating ranked lists, especially lists of
genes. It implements the Robust Rank Aggregation (Kolde et. al
in preparation) and some other simple algorithms for the task.
RRA method uses a probabilistic model for aggregation that is
robust to noise and also facilitates the calculation of
significance probabilities for all the elements in the final
ranking.
Linear regression functions using Huber and bisquare psi functions. Optimal weights are calculated using IRLS algorithm.
Robust Estimation of Variance Component Models by classic and composite robust procedures. The composite procedures are robust against outliers generated by the Independent Contamination Model.
eXperimental, eXtraneous, or eXtraordinary Functionality
for Robust Statistics.  In other words, methods which are not
yet well established, often related to methods in package
robustbase.
This package computes traditional ROC curves and time-dependent ROC curves using the cross-validation, the 0.632 and the 0.632+ estimators. The 0.632+ estimator of time-dependent ROC curve is useful to estimate the predictive accuracy of prognostic signature based on high-dimensional data. For instance, it outperforms the other approaches, especially the cross-validation solution which is often used. The 0.632+ estimators correct the area under the curve in order to adequately estimate the prognostic capacities regardless of the overfitting level. This package also allows for the construction of diagnostic or prognostic scoring systems (penalized regressions). The methodology is adapted to complete data (penalized logistic regression associated with ROC curve) or incomplete time-to-event data (penalized Cox model associated with time-dependent ROC curve).
Functions for a classification method based on receiver
operating characteristics (ROC). Briefly, features are selected
according to their ranked AUC value in the training set. The
selected features are merged by the mean value to form a
metagene. The samples are ranked by their metagene value and
the metagene threshold that has the highest accuracy in
splitting the training samples is determined. A new sample is
classified by its metagene value relative to the threshold. In
the first place, the package is aimed at two class problems in
gene expression data, but might also apply to other problems.
A collection of functions for ease of
presentation and interpretation of regression analysis.
These functions are used to produce the statistics lectures
in http://pj.freefaculty.org/guides. There
are functions to explore the effect (or lack thereof) from
"mean centering," "residual centering", and standardization.
The vignette "rockchalk" offers a fairly comprehensive overview.
The vignette "Rstyle" has advice about coding in R.
See the outreg function for a convenient way to generate
regression models for reports. For nice, easy to use pictures,
see plotSlopes, plotCurves, plotPlane.
The package title "rockchalk" refers to our school motto,
"Rock Chalk Jayhawk, Go K.U.".
Provides functions to complete three-dimensional rock fabric and strain analyses following the Rf Phi, Fry, and normalized Fry methods. Also allows for plotting of results and interactive 3D visualization functionality.
The rococo package provides a robust gamma rank correlation
coefficient along with a permutation-based rank correlation test.
The rank correlation coefficient and the test are explicitly
designed for dealing with noisy numerical data.
ROC graphs, sensitivity/specificity curves, lift charts,
and precision/recall plots are popular examples of trade-off
visualizations for specific pairs of performance measures. ROCR is a
flexible tool for creating cutoff-parameterized 2D performance curves
by freely combining two from over 25 performance measures (new
performance measures can be added using a standard interface).
Curves from different cross-validation or bootstrapping runs can be
averaged by different methods, and standard deviations, standard
errors or box plots can be used to visualize the variability across
the runs. The parameterization can be visualized by printing cutoff
values at the corresponding curve positions, or by coloring the
curve according to cutoff. All components of a performance plot can
be quickly adjusted using a flexible parameter dispatching
mechanism. Despite its flexibility, ROCR is easy to use, with only
three commands and reasonable default values for all optional
parameters.
Plots the Receiver Operating Characteristics Surface for high-throughput class-skewed data, calculates the Volume under the Surface (VUS) and the FDR-Controlled Area Under the Curve (FCAUC), and conducts tests to compare two ROC surfaces.
This package contains functions in order to estimate time-dependent ROC with right-censored data. More precisely, two functions concern the estimation of ROC curves defined by Heagerty, Lumley and Pepe (Biometrics, 2000). The two other functions concern their adaptation for studying the capacity of a marker to predict the excess of mortality of a specific population compared to the general population (same age, gender and calendar year). This last part is based on additive relative survival models and the work of Pohar-Perme (Biometrics, 2011).
Function to estimate the ROC Curve of a continuous-scaled
diagnostic test with the help of a second imperfect diagnostic
test with binary responses.
An extension for RODBC package adding support for parameterized
queries.
A collection of functions for numerical construction of optimal discriminating designs. At the current moment T-optimal designs (which maximize the lower bound for the power of F-test for regression model discrimination) and their robust analogues can be calculated with the package.
This package implements an interface to Oracle Data Mining
(ODM). It provides an ideal environment for rapid development
of demos and proof of concept data mining studies. It
facilitates the prototyping of vertical applications and makes
ODM and the RDBMS environment easily accessible to
statisticians and data analysts familiar with R but not fluent
in SQL or familiar with the database environment. It also
facilitates the benchmarking and testing of ODM functionality
including the production of summary statistics, performance
metrics and graphics. It enables the scripting and control of
production data mining methodologies from a high-level
environment. Oracle Data Mining (ODM) is an option of Oracle
Relational Database Management System (RDBMS) Enterprise
Edition (EE). It contains several data mining and data analysis
algorithms for classification, prediction, regression,
clustering, associations, feature selection, anomaly detection,
feature extraction, and specialized analytics. It provides
means for the creation, management and operational deployment
of data mining models inside the database environment. For more
information consult the entry for "Oracle Data Mining" in
Wikipedia (en.wikipedia.org).
The R Optimization Infrastructure (ROI) package provides a
sophisticated framework for handling optimization problems in R.
This package enhances the R Optimization Infrastructure (ROI) package
with the GLPK solver for solving mixed integer linear programming (MILP)
problems as well as all variants/combinations of LP, IP.
This package enhances the R Optimization Infrastructure (ROI) package
with the quadprog solver for solving quadratic programming (QP)
problems.
This package enhances the R Optimization Infrastructure (ROI) package
with the symphony solver from the COIN-OR suite for solving mixed integer
linear programming (MILP) problems as well as all variants/combinations of LP, IP.
Provides the possibility to plot Lexis surface maps (heat maps) of rates of mortality improvement. Raw data to be plotted can be read from the Human Mortality Database using code originally written by Tim Riffe. The European Research Council has provided financial support under the European Community's Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no. 263744.
Methods and classes for object-oriented programming in R with or without references.  Large effort has been made on making definition of methods as simple as possible with a minimum of maintenance for package developers.  The package has been developed since 2001 and is now considered very stable.  This is a cross-platform package implemented in pure R that defines standard S3 classes without any tricks.
This package contains the Rook specification and
convenience software for building and running Rook applications. To
get started, be sure and read the 'Rook' help file first.
Implementation of the Taylor Regression Estimator method described in Christopoulos (2014,<https://www.researchgate.net/publication/261562841>)
for finding the root, extreme or inflection point of a curve, when we only have a set of probably noisy xy points for it. The method uses a suitable
polynomial regression in order to find the coefficients of the relevant Taylor polynomial for the function that has generated our data.
Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE).
Includes routines that: (1) generate gradient and Jacobian matrices (full and banded),
(2) find roots of non-linear equations by the Newton-Raphson method,
(3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the Newton-Raphson method, or by dynamically running,
(4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ODEs
by numerical differencing (using the method-of-lines approach).
Includes fortran code.
An R package for the OpenSecrets.org web services API.
Optimally robust estimation in general smoothly parameterized models using S4 classes and methods.
Optimally robust estimation using S4 classes and methods. Old version still needed
for current versions of ROptRegTS and RobRex.
R package extracts optimizely test results and test information using Optimizely REST API. Only read functionality is supported for analysis and reporting.
Optimally robust estimation for regression-type models using S4 classes and
methods
An R package for computing both exact- and stochastic
robust ordinal regression, and maximal vectors.
Oracle database interface (DBI) driver for R.
This is a DBI-compliant Oracle driver based on the OCI.
Implementation of Robust Ordinal Regression for value-based sorting with some extensions and additional tools. It is a novel Multiple-Criteria Decision Aiding (MCDA) framework.
The package provides functions to deal with binary classification
problems in the presence of imbalanced classes. Synthetic balanced samples are
generated according to ROSE (Menardi and Torelli, 2013).
Functions that implement more traditional remedies to the class imbalance
are also provided, as well as different metrics to evaluate a learner accuracy.
These are estimated by holdout, bootstrap or cross-validation methods.
Fit and deploy rotation forest models ("Rodriguez, J.J., Kuncheva, L.I., 2006. Rotation forest: A new classifier ensemble method. IEEE Trans. Pattern Anal. Mach. Intell. 28, 1619-1630") for binary classification. Rotation forest is an ensemble method where each base classifier (tree) is fit on the principal components of the variables of random partitions of the feature set.
Tools for working with rotational data, including
simulation from the most commonly used distributions on SO(3),
methods for different Bayes, mean and median type estimators for
the central orientation of a sample, confidence/credible
regions for the central orientation based on those estimators and
a novel visualization technique for rotation data.  Most recently,
functions to identify potentially discordant (outlying) values
have been added.
R build of Rothermel's (1972) model for surface fire rate of spread with some additional utilities (uncertainty propagation, standard fuel model selection, fuel model optimization by genetic algorithm) and sample datasets.
An interface to the 'Open Tree of Life' API to retrieve phylogenetic
trees, information about studies used to assemble the synthetic tree, and
utilities to match taxonomic names to 'Open Tree identifiers'. The 'Open Tree of
Life' aims at assembling a comprehensive phylogenetic tree for all named
species.
A set of functions to support Xiong K, 'Roughened Random Forests for Binary Classification' (2014). The functions include RRFA, RRFB, RRFC1-RRFC7, RRFD and RRFE. RRFB and RRFC6 are usually recommended. RRFB is much faster than RRFC6.
Rough Sets were introduced by Zdzislaw Pawlak on his book "Rough Sets: Theoretical Aspects of Reasoning About Data". Rough Sets provide a formal method to approximate crisp sets when the set-element belonging relationship is either known or undetermined. This enables the use of Rough Sets for reasoning about incomplete or contradictory knowledge. A decision table is a prescription of the decisions to make given some conditions. Such decision tables can be reduced without losing prescription ability. This package provides the classes and methods for knowledge reduction from decision tables as presented in the chapter 7 of the aforementioned book. This package provides functions for calculating the both the discernibility matrix and the essential parts of decision tables.
Implementations of algorithms for data analysis
based on the rough set theory (RST) and the fuzzy rough set theory (FRST). We
not only provide implementations for the basic concepts of RST and FRST but also
popular algorithms that derive from those theories. The methods included in the
package can be divided into several categories based on their functionality:
discretization, feature selection, instance selection, rule induction and classification
based on nearest neighbors. RST was introduced by Zdzisław Pawlak in 1982
as a sophisticated mathematical tool based on indiscernibility relations to
model and process imprecise or incomplete information. It works on
symbolic-valued datasets for tackling the data analysis problems. By using
the indiscernibility relation for objects/instances, RST does not require
additional parameters to analyze the data. FRST is an extension of RST. The
FRST combines concepts of vagueness and indiscernibility that are expressed
with fuzzy sets (as proposed by Zadeh, in 1965) and RST.
Allows the manipulation of R objects as if they were
organized rows in a way that is familiar to people used to working with
databases.  It allows more consistent and predictable output to common
functions, and generalizes a number of utility functions to to be failsafe
with any number and type of input objects.
A 'Doxygen'-like in-source documentation system
for Rd, collation, and 'NAMESPACE' files.
Performs a multivariate normality test based on Royston's H test
Implements fits of diversification models to phylogenetic data. See Morlon et al. PLoSB (2010), Morlon et al. PNAS (2011), Condamine et al. Eco Lett (2013), Morlon et al. Eco Lett (2014) and Manceau et al. (in prep).
rpanel provides a set of functions to build simple
GUI controls for R functions.  These are built on the tcltk package.
Uses could include changing a parameter on a graph by animating it
with a slider or a "doublebutton", up to more sophisticated control
panels.
Some functions for specific graphical tasks, referred to as 'cartoons',
are provided.
Recursive partitioning for classification,
regression and survival trees.  An implementation of most of the
functionality of the 1984 book by Breiman, Friedman, Olshen and Stone.
Provides algorithims for randomly sampling a feasible set defined
by a given total and number of elements using integer partitioning.
Plot rpart models. Extends plot.rpart and text.rpart in
the rpart package.
This package contains functions that allow to build
classification trees for ordinal responses within the CART
framework. The trees are grown using the Generalized Gini
impurity function, where the misclassification costs are given
by the absolute or squared differences in scores assigned to
the categories of the response. Pruning is based on the total
misclassification rate or on the total misclassification cost.
This package contains additional tools for working with rpart
objects.  Most importantly, it includes methods for converting rpart rules
into a series of structured tables sufficient for executing the decision
tree completely in SQL.
Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Candes, E. J., Li, X., Ma, Y., & Wright, J. (2011). Robust principal component analysis?. Journal of the ACM (JACM), 58(3), 11. prove that we can recover each component individually under some suitable assumptions. It is possible to recover both the low-rank and the sparse components exactly by solving a very convenient convex program called Principal Component Pursuit; among all feasible decompositions, simply minimize a weighted combination of the nuclear norm and of the L1 norm. This package implements this decomposition algorithm resulting with Robust PCA approach.
This package implements the R-PCLR (Random-Penalized
Conditional Logistic Regression) algorithm for obtaining
variable importance. The algorithm is applicable for the
analysis of high dimensional data from matched case-control
studies.
Provides tools to read, write, visualize PDB files and perform some structural manipulations.
Monthly Pacific Decadal Oscillation (PDO) index
values from January 1900 to present.
Implements the methodology of "Cannings, T. I. and Samworth, R. J. (2015) Random projection ensemble classification. http://arxiv.org/abs/1504.04595". The random projection ensemble classifier is a very general method for classification of high-dimensional data, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower-dimensional space. The random projections are divided into non-overlapping blocks, and within each block the projection yielding the smallest estimate of the test error is selected. The random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment.
The purpose of this package is to factor out logic and math common
to Item Factor Analysis fitting, diagnostics, and analysis. It is
envisioned as core support code suitable for more specialized IRT packages
to build upon. Complete access to optimized C functions are made available
with R_RegisterCCallable.
Allows ad hoc queries and reading and
writing data frames to and from a database.
RPHAST is an R interface to the PHAST software
(Phylogenetic Analysis with Space/Time Models).  It can be used for
many types of analysis in comparative and evolutionary genomics,
such as estimating models of evolution from sequence data, scoring
alignments for conservation or acceleration, and predicting
elements based on conservation or custom phylogenetic hidden Markov
models.  It can also perform many basic operations on multiple
sequence alignments and phylogenetic trees.
Rphylip provides an R interface for the PHYLIP package. All users
of Rphylip will thus first have to install the PHYLIP phylogeny methods
program package (Felsenstein 2013). See http://www.phylip.com for more
information about installing PHYLIP.
Tools for performing phylogenetic comparative methods for datasets with with multiple observations per species (intraspecific variation or measurement error) and/or missing data. Available functions allow ancestral state reconstruction, missing data imputation, phylogenetic regression (phylogenetic generalized least squares), and phylogenetic principal components analysis (pPCA).
rPlant is an R interface to the the many computational
resources iPlant offers through their RESTful application
programming interface. Currently, rPlant functions interact
with the iPlant foundational API, the Taxonomic Name Resolution
Service API, and the Phylotastic Taxosaurus API. Before using
rPlant, users will have to register with the iPlant
Collaborative.
http://www.iplantcollaborative.org/discover/discovery-environment
Efficiently read and analyze 'PLEXOS' solutions by converting them
into 'SQLite' databases that can be easily queried. It supports collation of
solutions that may have been divided into different time partitions,
as well as the comparison across different scenarios. 'PLEXOS' is a power systems
production cost model, created and distributed by Energy Exemplar
(see URL below for more information).
A programmatic interface to the 'SOLR' based
search 'API' (http://api.plos.org/) provided by the Public
Library of Science journals to search their articles.
Functions are included for searching for articles, retrieving
articles, making plots, doing 'faceted' searches,
'highlight' searches, and viewing results of 'highlighted'
searches in a browser.
This package is intended for using R as a plotting engine either by custom
applications, or from a small script launched from the system console, or even within
the R console. Two ASCII text files are necessary:
(1) The graph parameters file, which name is passed to the function 'rplotengine()'.
The user can specify the titles, choose the type of the graph, graph output formats
(e.g. png, eps), proportion of the X-axis and Y-axis, position of the legend,
whether to show or not a grid at the background, etc.
(2) The data to be plotted, which name is specified as a parameter ('data_filename')
in the previous file. This data file has a tabulated format, with a single character
(e.g. tab) between each column, and a headers line located in the first row.
Optionally, the file could include data columns for showing confidence intervals.
Really Poor Man's Graphical User Interface, used to create interactive R analysis sessions with simple R commands.
Recursively Partitioned Mixture Model for Beta and Gaussian Mixtures.
This is a model-based clustering algorithm that returns a hierarchy
of classes, similar to hierarchical clustering, but also similar to
finite mixture models.
PDF tools based on the Poppler PDF rendering library.
See <http://poppler.freedesktop.org/> for more information on Poppler.
A collection of utility functions to generate
various types of random portfolios.  The weights of these
portfolios are random variables derived from uniformly
distributed random variables
Database interface and PostgreSQL driver for R This
package provides a Database Interface (DBI) compliant driver
for R to access PostgreSQL database systems.

In order to build and install this package from source, PostgreSQL
itself must be present your system to provide PostgreSQL
functionality via its libraries and header files. These files
are provided as postgresql-devel package under some Linux
distributions.

On Microsoft Windows system the attached libpq library source will be
used.

A wiki and issue tracking system for the package are available at
Google Code at https://code.google.com/p/rpostgresql/ .
Using some association schemes to obtain a new series of resolvable partially pairwise balanced designs (RPPBD) and space-filling designs.
Reads in sample description and slide description files and
annotates the expression values taken from gpr files. After
normalization data can be visualized as boxplot, heatmap or
dotplot.
Routines to select and visualize the maxima for a given strict
partial order. This especially includes the computation of the Pareto
frontier, also known as (Top-k) Skyline operator, and some
generalizations (database preferences).
'Eprime' is a set of programs for administering psychological
experiments by computer. This package provides functions for loading,
parsing, filtering and exporting data in the text files produced by
'Eprime' experiments.
A set of tools for building formatted string under various
replacement rules: C-style formatting, variable-based formatting, and
number-based formatting
Protocol Buffers are a way of encoding structured data in an
efficient yet extensible format. Google uses Protocol Buffers for almost all
of its internal RPC protocols and file formats.  Additional
documentation is available in the arXiv.org preprint "RProtoBuf:
Efficient Cross-Language Data Serialization in R" by Eddelbuettel,
Stokely, and Ooms (2014) at <http://arxiv.org/abs/1401.7372>.
The rpsychi offers a number of functions for psychiatry, psychiatric nursing, clinical psychology. Functions are primarily for statistical significance testing using published work. For example, you can conduct a factorial analysis of variance (ANOVA), which requires only the mean, standard deviation, and sample size for each cell, rather than the individual data. This package covers fundamental statistical tests such as t-test, chi-square test, analysis of variance, and multiple regression analysis. With some exceptions, you can obtain effect size and its confidence interval. These functions help you to obtain effect size from published work, and then to conduct a priori power analysis or meta-analysis, even if a researcher do not report effect size in a published work.
Access PubChem data (compounds, substance, assays).
Structural information is provided in the form of SMILES
strings. This package only provides access to a subset of the
precalculated data stored by PubChem. Bio-assay data can be
accessed to obtain descriptions as well as the actual data. It
is also possible to search for assay ID's by keyword. Currently
the main limitation is that only 1000 molecules can be
downloaded at a time from the PubChem servers
Client for accessing ProPublica's data journalism APIs
This package provides R functions for performing
computation on GPU. The implementation is based on the NVIDIA
CUDA Toolkit. Besides the core functionality, it also aims for
robustness, performance, and scalability.
An R interface to the Pushbullet messaging service which
provides fast and efficient notifications (and file transfer) between
computers, phones and tablets.  An account has to be registered at the site
http://www.pushbullet.com site to obtain a (free) API key.
Provide access to (virtually any) ArcGIS Geoprocessing
tool from within R by running Python geoprocessing scripts
without writing Python code or touching ArcGIS. Requires ArcGIS
>=9.2, a suitable version of Python (for ArcGIS 9.2: Python
2.4; for ArcGIS 10.0: 2.6), and Windows.
This package permits calls to Python from R
R package for Qualitative Data Analysis. Current version only supports plain text, but it can import PDF highlights if the Enhance package of rjpod, which is available on R-Forge, is installed.
Performs penalized quantile regression for LASSO, SCAD and MCP functions. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC.
Hypocenter estimation and analysis of seismic data collected continuously, or in trigger mode. The functions organize other functions from RSEIS and GEOmap to help researchers pick, locate, and store hypocenters for detailed seismic investigation.
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,'' Working paper available at <http://graemeblair.com/papers/randresp.pdf>.
Analyzes and predicts from matrix population models in the way of the Ramas (c) software
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:
outlier detection, PCA, PLS, 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".
R client interface to the "Redis" key-value database.
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 and as
predictors in a linear regression. 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/.
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.
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.
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 2.10 and 2.11 are supported.
Client for Rserve, allowing to connect to Rserve instances and issue commands.
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.
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.
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.
Read and analyse Root System Markup Language (RSML) files, used to
store plant root system architecture data. More information can be found
here: 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.
RSNPset is an implementation of the use of efficient score statistics
in genome-wide SNP set analysis with complex traits. The package provides three standard
score statistics (Cox, binomial, and Gaussian) but 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.
Manages throttling by 'Socrata'.
sofia-ml is a suite of fast incremental algorithms for machine learning that can be used for training models for classification or ranking
General Non-linear Optimization Using Augmented Lagrange Multiplier Method
Somoclu is a cluster-oriented implementation of self-organizing maps. It 			     relies on MPI for distributing the workload, and it can be accelerated by 			     CUDA on a GPU cluster. A sparse kernel is also included, which is useful for 		     training maps on vector spaces generated in text mining processes.
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.
Calculate SPEARpesticide in R
(http://www.systemecology.eu/SPEAR/index.php)
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.
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.
RSQLServer wraps the jTDS Project's JDBC 3.0 SQL Server
driver and extends the RJDBC classes and DBI methods. It defines a
SQLServerDriver, SQLServerConnection & SQLServerRsult S4 classes as
extensions of the RJDBC equivalent classes. Most of the DBI methods will
simply be calls to methods defined by RJDBC classes. However, the dbConnect
and some of the dbGetInfo methods are specific to SQL Server. The jTDS
drivers do extend to Sybase SQL Server, but currently, only Microsoft SQL
Server is supported by this package.
Methods and tools for Singular Spectrum Analysis including decomposition, forecasting and gap-filling for univariate and multivariate time series.
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 by this package 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 and (optionally penalized) maximum likelihood estimation via optimization. In both cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
Access to the Digital Universe Data set API pulls data on
exoplants, stars, and galaxies.
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."
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 Stata's stpm2 function (flexible link-based survival models), with extensions to different smoothers and penalised models.
Unified object oriented interface for multiple independent streams of random numbers from different sources.
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 four 'Sunlight' Foundation 'APIs'
(http://sunlightfoundation.com/api/) for government data, including the
Congress 'API' 'v3', the Capitol Words 'API', the Influence Explorer '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
four 'APIs'.
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.
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.
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, and random generation): (a) Ratcliff diffusion model based on
C code by Andreas and Jochen Voss and (b) linear ballistic accumulator (LBA)
with different distribution underlying the drift rate.
Exploit controlled vocabularies organized on tematres servers.
rTensor is 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 also
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, product, and 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. Development of rTensor has
been generously supported by Cornell's Department of Statistical Science.
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.
RTFBS 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.
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.
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.
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.
This package 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 'mp3' or 'wav' format) with APIs offered by Google Translate and ITRI TTS (Text-To-Speech service, Industrial Technology Research Institute, Taiwan. http://tts.itri.org.tw/). Two main functions are given corresponding these two APIs, tts_google() and tts_ITRI(). For tts_google(), only English is supported. For tts_ITRI(), English and Chinese (both traditional and simplified) are supported, and user can specify the speaker accent, speed and volume. Both functions require internet connection.
A strong type system for R which supports
symbol declaration and assignment with type checking
and condition checking.
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.
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'.
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 XML and httr packages to make it easy to
download, then manipulate, both 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.
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.
Variable metric nonlinear function minimization with bounds constraints.
R interface to Vowpal Wabbit fast out-of-core learning system
The Vowpal Wabbit (VW) project is a fast out-of-core learning system
sponsored by Yahoo! Research and written by John Langford along with a
number of contributors.

There are two ways to have a fast learning algorithm: (a) start with a slow
algorithm and speed it up, or (b) build an intrinsically fast learning
algorithm. This project is about approach (b), and it has reached a state
where it may be useful to others as a platform for research and
experimentation.

There are several optimization algorithms available with the baseline being
sparse gradient descent (GD) on a loss function (several are available). The
code should be easily usable. Its only external dependence is on the Boost
library, which is often installed by default.

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 servie is also not directly supported as the aim is a simpler direct
call from R for validation and comparison.
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.
This package provides programmatic access to Yahoo!
Weather and NOAA APIs
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 3.7.12).
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.
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 basic wireless communications simulation package in R. The package includes
modulation functions for BPSK, QPSK, 8-PSK, 16-QAM and 64-QAM. Also included is
an AWGN noise generation function. Additionally, the package includes functions to plot
an I (in-phase) and Q (quadrature) scatter diagram, or density plot. Together these functions
enable the evaluation of respective bit error and symbol rates in an AWGN channel and for
easily viewing the respective signals and noise in a scatter plot or density plot.
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.
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.
The RXMCDA package for the R statistical software allows you to read many XMCDA tags and transform them into R variables which are then usable in your MCDA algorithms written in R. The library also allows to write certain R variables into XML files according to 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.
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.
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.
Data, functions etc. from the 'R you ready?' book
A programmatic interface to web-services of Youtheria. Youtheria is an online database of mammalian trait data.
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'.
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 assess the performance of a model 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).
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.
A collection of baseball analytics functions for sabermetrics purposes. Among these functions include popular metrics such as OBP, wOBA, runs created functions as well as field-independent pitching 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.
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'.
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.
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.
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.
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.
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.
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. Single and two stage sampling designs are considered. Some approximations for the second order inclusion probabilities are also available (sample and population based).
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.
This package has 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
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
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.
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.
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.
scholar 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).
Provides miscellaneous functions for carrying out political behaviour analysis, including measures of political fragmentation, seats allocation, and graphical demonstrations.
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
An R package for single-case meta-analysis.
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 to quickly score models commonly used to data
analysis and data science using uncommon scoring metrics. For example,
you might want to use a weighted absolute percent error instead of
a root mean square deviation to score that regression model.
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.
Division of an ANOVA experiment treatment means into
homogeneous distinct groups using the clustering method of
Scott & Knott
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.
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.
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.
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.
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.
This package includes several methods 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 marginal mixture distributions
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).
Implementation of some algorithms for the data mining task called "subgroup discovery" without package dependencies. It also provide a Shiny App for make the analysis easier.
The algorithms works with data sets provided in KEEL format.
If you want more information about this format, please refer to < http://www.keel.es > .
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 API v3,
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 does not
contain the binaries of X-13, which must be installed separately. See the
README file or the vignette for installation notes.
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.
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'
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.
This package 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.
This package performs a fast exact segmentation on data and allows for use of various cost functions
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.
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.
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 inference after selection, for use with forward stepwise regression, least angle regression, the lasso, and the many normal means problem. This R code was developed in coordination with an analogous Python package developed by Jonathan Taylor and others, see http://github.com/selective-inference/selective-inference.
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.
Regularization for variable selection in model-based clustering and discriminant analysis
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.
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.
More generators are planned in near future.
Data evaluation support tools include:
-single attribute based statistical evaluation: mean, median,standard deviation, skewness, kurtosis, KS test, Hellinger distance
-evaluation based on clustering using Adjusted Rand Index (ARI)
-evaluation based on classification performance with various learning models, eg, random forests.
This package contains algorithms to perform various types of parametric and semi-parametric analyses of semi-competing risks data. We also provide functions to fit survival regression models to univariate time-to-event outcome.
This package 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.
Routine for fitting bivariate models for binary and continuous responses with linear and nonlinear 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 semiparametric 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.
A collection of functions for factor screening, global sensitivity analysis and reliability sensitivity analysis of model output.
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 are provided. 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 for the  functionalities
forms part of the package.
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.
Functions to generate separation plots for evaluation of
model fit.
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.
Exploratory data analysis and data visualization
for biological sequence (DNA and protein) data.  Includes also
utilities for sequence data management under the ACNUC system.
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 (VCF/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.
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. These calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. For group sequential analyses, the group sizes do not have to be specified in advance and, for binomial data, 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.
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 (SEM) is a powerful statistical
approach for the testing of networks of direct and indirect theoretical
causal relationships in complex datasets with intercorrelated dependent and
independent variables. Here we implement a simple method for spatially
explicit SEM (SE-SEM) based on the analysis of variance covariance matrices
calculated across a range of lag distances. This method provides readily
interpretable 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.
SetMethods is a package companion to the book by C. Q.
Schneider and C. Wagemann "Set-Theoretic Methods for the Social
Sciences", Cambridge University Press. It contains some
additional functions not present in other packages and 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".
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.
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 and default values.
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).
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 inference. It
features many different 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+
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. This package
apply template metaprogramming techniques, therefore -- when compiling the
package from source -- a high level of optimization is needed to gain full
speed (e.g. for the GCC compiler use -O3). Use of multiple processors for
cross validation and subsampling is supported through OpenMP. The Armadillo
C++ library is used as the primary linear algebra engine. (The sglOptim
package version a.b.c.d is interpreted as follows: a - primary
version, b - major updates and fixes, c - source revision as corresponding
to R-Forge, d - minor fixes made only to the CRAN
branch of the source)
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
The package SGPdata contains three data sets utilized by the SGP Package as exemplars for users to set up their own data for 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 plotting graphical shapes
such as ellipses, circles, cylinders, arrows, ...
Functions to read and write ESRI shapefiles
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.
Data sets and SAR, SARX, HSAR and HSARX
models as described in Solymos and Lele
(2012, GEB 21, 109-120).
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 or quantile 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 additional quantiles. A graphical interface for the roulette elicitation method is also provided. For multiple experts, a weighted linear pool can be calculated.
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.
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.
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,
and many more useful functions. Even if you do know JavaScript,
'shinyjs' can be used as convenience functions to avoid dealing with message
passing and writing JavaScript code. 'shinyjs' can also be used to
easily run your own custom JavaScript functions from R.
Shiny wrappers for the RGL package. This package exposes RGL's
ability to export WebGL visualization in a shiny-friendly format.
We provide 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 package and the No-U-Turn sampler).
Themes for use with Shiny. Includes several Bootstrap themes
from http://bootswatch.com/, which are packaged for use with Shiny
applications.
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.
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. Works
with files exported by OnTarget PC and OnTarget TDS or with
custom data files in text format with a similar structure.
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.
Post-estimation shrinkage of regression coefficients in statistical modeling can be
used to correct for the overestimation of regression coefficients caused by variable selection.
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 (for
R <= 3.1.0) mfp is available.
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 bivariate 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.
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).
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 presence of signal peptides in eukaryotic protein using
hidden semi-Markov models. The implemented algorithm can be accessed both
from 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.
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 by utilizing threshold approaches under a cumulative link model, a continuation ratio model or a baseline-category logit marginal model specification.
Algorithms for the implementation and evaluation of Monte Carlo tests, as well as for their use in multiple testing procedures.
The package Sim.DiffProc is an object created in R environment 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.
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.
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.
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.
The R package simone 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.
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.
Trains neural networks (multilayer perceptrons with one hidden layer) for bi- or multi-class classification.
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.
This package 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.
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.
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.
This 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 aims is to provide an estimation of 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', adapted to regression of binary genotype against HPO encoded phenotype. The purpose is to weigh the evidence for an association between phenotype and genotype. This is done by estimating a Bayes factor comparing a `no association' model with one in which log odds of presenting a particular binary genotype is linked to the semantic similarity between the corresponding phenotype and an estimated characteristic phenotype.
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.
Tools for setting up, conducting, and evaluating larger-scale
simulation studies, including parallel computations.
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.
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
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.
This packages provides and implementation of the Smooth Incremental Graphical Lasso Estimation (SINGLE) which can be used to estimate dynamic networks from non-stationary time series data.
A platform for experimenting with spatially explicit individual-based vegetation models.
Package provides functions to calculate daily solar
radiation at horizontal surface using several well-known
models. It also includes functions for model calibration based
on ground-truth data as well as a function for
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, faceted and hierarchical rater models,
ordinal IRT model (ISOP), latent regression models,
DETECT statistic, local structural equation modeling (LSEM).
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.
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.
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.
This package contains 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 book "Six Sigma with R" (Springer, 2012)
are also included in the package.
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.
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.
The Skillings-Mack test statistic is 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. The results from the SkiMack function are the Skillings-Mack statistic, p-values based on the chi-squared distribution and Monte Carlo method. The Monte Carlo method is recommended for approximating p-values when there are many ties and/or small designs with missing values are conducted.
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 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.
Slackr contains functions that make it possible to
interact with Slack.com messaging platform. When you need to share
information/data from R, rather than resort to copy/paste in e-mails
or other services like Skype, 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 (as RData),
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.
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 extensiosn 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).
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 presented on the blog SmarterPoland.pl. Among all: functions for downloading data from eurostat database, coordinates from Google Maps and data from GUS (Central Statistical Office of Poland).
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.
It categorizes a numeric variable into bins mapped to a binary target variable for its ulterior usage in scoring modeling. Its purpose is to automate the time consuming process of selecting the right cut points, quickly calculate metrics such as Weight of Evidence and Information Value; and also document SQL codes, tables, and plots used throughout the development stage. The package also allows users to establish their own 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.
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))".
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
Define 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.
Robust and non-robust SNHT tests for changepoint detection.
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.
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.
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.
The package 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), 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.
SocialMediaMineR is a 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, tweets, pins, and hits on Facebook, Twitter, Pinterest, StumbleUpon, LinkedIn, and Reddit. The package also includes dedicated functions for each social networking site and a function to decode 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.
To implement two clustering methods, ODC and SODC, for
clustering datasets using optimal scoring, can also be used as
an dimension reduction tool.
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)
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.
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.
This package 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'.
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.
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.
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.
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.
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.
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.
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 combining or aggregating, 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.
The package 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.
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")`.
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.
Implements a collection of functions for inference in mixed models. It was developed in particular for GLMMs with spatial correlations, but also fits models with non-Gaussian random effects (e.g., Beta Binomial, or negative-binomial mixed models). Heteroskedasticity 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.
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
Computes Hessian of a scalar-valued function, and returns it in
sparse Matrix format, using ACM TOMS Algorithm 636. The user must supply the objective function, the
gradient, and the row and column indices of the non-zero elements of the
lower triangle of the Hessian (i.e., the sparsity structure must be known
in advance). The algorithm exploits this sparsity, so Hessians can be
computed quickly even when the number of arguments to the objective
functions is large. This package is intended to be useful for numeric
optimization (e.g., with the trustOptim package) or in simulation (e.g.,
the sparseMVN package). The underlying algorithm is ACM TOMS Algorithm 636,
written by Coleman, Garbow and More (ACM Transactions on Mathematical
Software, 11:4, Dec. 1985).
Performs sparse linear discriminant analysis for gaussians
and mixture of gaussians models.
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.  Beyond regression analyses, applications include subgroup analysis, particularly for conjoint experiments, and panel data.  Functionality for dichotomous and censored outcome (Types I and II tobit) is also included.  Future plans involve extending the method to propensity score and instrumental variable methods.
Sparse-aware maximum likelihood for structural equation models in inferring gene regulatory networks
Computes sparse vector autoregressive coefficients and precision
matrices for time series chain graphical models.
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, graph visualization and graph component
calculations, ment to be used as a tool in spatial point
pattern analysis. See package 'spatstat' for more info about
spatial point patterns.
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 modeling.
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 subsampling, polygon and point-distance landscape metrics, auto-logistic
model, sampling models, cluster optimization and statistical exploratory tools.
Tools for the statistical modelling of spatial extremes using max-stable processes, copula or Bayesian hierarchical models.
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 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.
Bayesian inference for parametric proportional hazards spatial survival models; flexible spatial survival models.
Fits univariate and multivariate spatio-temporal
models with Markov chain Monte Carlo (MCMC).
This package provides several Bayesian survival models for spatial/non-spatial survival data: marginal Bayesian Nonparametric models, marginal Bayesian proportional hazards models, and generalized accelerated failure time frailty models.
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 ...).
Computes Least Squares Sparse Principal Components either by a
Branch-and-Bound search or with an iterative Backward Elimination
algorithm. Sparse solutions can be plotted, printed and compared using the
methods included.
Calibration of  thresholds of control charts such as
CUSUM charts based on past data, taking estimation error into account.
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.
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 data in relation to geographical areas 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.
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.
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.
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.
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 based on work by Chris
Brunsdon, Martin Charlton and Stewart Fotheringham,
http://gwr.nuim.ie/
Various functions for creating spherical coordinate system plots via extensions to rgl.
This package defines 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.
A package for the analysis of species limits and DNA barcoding data
Fits and simulates data from our predator preferences model
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).
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.
Classes and methods for times and dates (ported from S-PLUS)
Classes and methods for time series (ported from S-PLUS).
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.
The package provides methods for dealing with spatial social
networks. It allows to plot networks for which actors have a specific
location on a map (cities, participants in a political debate, etc.).
SpatialPolygons objects from the sp package are supported.
A programmatic interface to many species occurrence data sources,
including 'GBIF', 'USGS's' 'BISON', 'iNaturalist', Berkeley 'Ecoinformatics'
Engine 'eBird', and 'AntWeb'. 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.
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.
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 methods for dimension reduction and regression analysis are implemented that yield estimates with a partial least squares alike interpretability. Partial robust M regression is robust to both vertical outliers and leverage points. Sparse partial robust M regression is a related robust method with sparse coefficient estimate, and therefore with intrinsic variable selection.
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 sample configurations using spatial simulated
annealing. Multiple objective functions are implemented for various
purposes, such as variogram estimation, 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.
Semiparametric transformation model, 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.
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.
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.
The ss3sim package develops a framework for fisheries stock
assessment simulation testing with Stock Synthesis 3 (SS3).
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.
Provides functions to evaluate user-defined power functions for a parameter range, and draws a sensitivity plot. It also provides a resampling procedure for semi-parametric sample size estimation and methods for adding information to a Sweave report.
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) and the sample size calculation method proposed for microarray experiments by Liu and Hwang (2007). 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', type = 'source')".
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.
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.
sss is a set of tools to import survey files
in the .sss (triple-s) format. It 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.
Compute the maximum-likelihood(ML), generalised method of moment with finite and continuum number of points, the iterative Koutrouvelis regression and the Kogon-McCulloch methods to estimate the 4 parameters of stable law. The asymptotic properties of the estimator (covariance matrix, confidence intervals) are also provided.
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.
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.
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, shared objects, vignettes, or function documentation. It 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 Bayesian statistical inference via Markov Chain Monte Carlo and (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.
A Set of Tools for Administering SHared Repositories
Datasets for Stat2 textbook (by Cannon, et. al., published
by WH Freeman)
A set of tools to explore data.frames (summarize,
tabulate, xtile, pctile, binscatter) and work with panel data (elapsed
quarters/month, lead/lag, fill in rows of values, rolling functions).
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.
statebins is an alternative to choropleth maps for USA States and
is based on work by the Washington Post graphics department in their report
on "The states most threatened by trade". statebins preserves 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 both a binned, discrete scale and continuous scale 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 Statistical Methods for Ranking Data by Mayer Alvo and Philip L.H. Yu(2014). 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.
This package implements 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.
Provides a number of functions for carrying out
inference with set-theoretic comparative methods, including
facilities for examining causal paths, assessing the sensitivity
of results to measurement and model specification error,
and performing Random Forest Comparative Analysis.
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.
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
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.
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.
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 and assumes that the explanatory variables are observed for all of the individuals. Once a "good" training set is identified, the response variable can be obtained only for this set to build a model for predicting the response in the test set.
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.
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.
This package 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 the class "StratSel" 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.
The package provide functions for computing the reliability of 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. via regular expressions), random string generation,
string collation, transliteration, concatenation,
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.
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.
A number of functions, supplemented by GUI, to perform various analyses in the field of computational stylistics, authorship attribution, etc.
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.
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.
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.
The subplex algorithm for unconstrained optimization, developed by Tom Rowan.
essentially a discussion tool about estimation of copula using ranks and subsampling.
Functions that compute sub-scores for a test using different methods in classical test theory (CTT).
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.
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.
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.
This package 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.
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.
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 biomarker 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 7th 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.
Implementation of statistical methods for the modeling and
change-point detection in time series of counts, proportions and
categorical data, as well as for the modeling of continuous-time
epidemic phenomena, e.g., discrete-space setups such as the spatially
enriched Susceptible-Exposed-Infectious-Recovered (SEIR) models,
or continuous-space point process data such as the
occurrence of infectious diseases. Main focus is on outbreak
detection in count data time series originating from public health
surveillance of communicable diseases, but applications could just as well
originate from environmetrics, reliability engineering, econometrics or
social sciences.
Currently, the package contains implementations of many typical
outbreak detection procedures such as Farrington et al (1996),
Noufaily et al (2012) or the negative binomial LR-CUSUM method
described in Höhle and Paul (2008). A novel CUSUM approach combining
logistic and multinomial logistic modelling is also included.
Furthermore, inference methods for the retrospective infectious
disease models in Held et al (2005), Held et al (2006),
Paul et al (2008), Paul and Held (2011), Held and Paul (2012),
and Meyer and Held (2014) are provided.
Continuous self-exciting spatio-temporal point processes are
modeled through additive-multiplicative conditional
intensities as described in Höhle (2009) ('twinSIR', discrete
space) and Meyer et al (2012) ('twinstim', continuous space).
The package contains several real-world data sets, the ability
to simulate outbreak data, visualize the results of the
monitoring in temporal, spatial or spatio-temporal fashion.
Note: Using the 'boda' algorithm requires the 'INLA'
package, which should be installed automatically through the
specified Additional_repositories, if uninstalled dependencies
are also requested. As this might not work under OS X it
might be necessary to manually install the 'INLA' package as
specified at <http://www.r-inla.org/download>.
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.
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.
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.
A collection of functions for analysis of survival data. These
extend the methods available in the 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.
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.
This package can be used to conduct asymptotic and empirical power and sample size calculations for SNP association studies with right censored time to event outcomes
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.
This package provides various R bindings to various 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
Some visualization tools based on Singular Value Decomposition
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
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.
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 Tex-package-listings "language" and
including R / Rd source file (sniplets) 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.
swirl turns the R console into an interactive learning
environment. Users receive immediate feedback as they are guided through
self-paced lessons in data science and R programming.
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 devel/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).
In this package the dynamic FBA technique proposed by
Varma was implemented.
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).
This package provides Boost mutex functionality in R.
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.
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.
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.
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 are observed.
Extracts sentiment and sentiment-derived plot arcs
from text using three sentiment dictionaries conveniently
packaged for consumption by R users.  Implemented dictionaries include
"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 method 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.
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 convenience wrappers for producing and exporting various commonly-used numerical table types to .xls/.xlsx multi-tab spreadsheets while controlling spreadsheet position and layout, via XLConnect functionality.
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
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 and joint 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).
Latent regression models and plausible value imputation are
also supported.
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).
A collection of various utility and convenience functions.
A collection of miscellaneous spatial object manipulation 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.
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
Taxonomic information from around the web. This package
interacts with a suite of web 'APIs' for taxonomic tasks, such
as verifying species names, getting taxonomic hierarchies,
and verifying name spelling.
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.
This package implements the TcGSA, an algorithm to analyze longitudinal gene-expression data at the gene set level.
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
Platform for the advanced analysis of T cell receptor repertoires data and visualisation of the analysis results.
This package provides tools for the statistical analysis of persistent homology and for density clustering.
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.)
Transmission/disequilibrium tests for extended marker haplotypes
This package is a set of 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 in the context of trimmed elemental regressions.
Fits mixtures of multivariate t-distributions (with eigen-decomposed covariance structure) via the multi-cycle ECM algorithm under a clustering or classification paradigm.
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, Fernandez, Litterman,
Denton and Denton-Cholette.
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.
The target equivalence range (TEQR) design, previously named the toxicity equivalence range design is an up-down design patterned after the modified toxicity probability interval design.The TEQR design extends the well known 3+3 design to allow for: an explicit target range for the dose limiting toxicity (DLT) rate, more subjects at the maximum tolerated dose (MTD), and specification of a too-toxic rate, which closes a dose level, In addition, the TEQR design can be implemented to target a dose based either on toxicity rate or activity rate constrained for toxicity.
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.
tester allows you to test characteristics of common R objects.
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.
This package intends to go above and beyond of the features
provided by the testthat package. Namely, stubbing of functions and methods
is provided as well as the ability to architect mock structured hierarchies
of files (sometimes called fixtures).
Intended for developers, testthatsomemore aims to
raise the caliber of R testing frameworks to that of famous libraries
like JUnit and RSpec.
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.
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.
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.
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).
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 first-order thermoluminescence glow curves 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. Glow peaks can be simulated according to the Randall-Wilkins model.
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.
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-armed non-inferiority or superiority trials which follow a gold-standard design, i.e. trials with an experimental treatment, an active and a placebo control. The following distribution of endpoints is covered: negative binomial distribution.
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.
Create interactive 3D scatter 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.
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.
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.
Calculate Characteristics of Qasi-Periodic Time Series, e.g. Estuarine Water Levels.
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.
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
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' attached. R Studio is freely available (www.rstudio.org), and
includes package 'manipulate'.  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.
This package contains functions for tight clustering
Algorithm.
The tikzDevice package 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 paper typeset by LaTeX, 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.
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.
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.
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.
TIMP is a problem-solving environment (PSE) for fitting
separable nonlinear models to measurements arising in physics
and chemistry experiments, and 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.
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.
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.
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
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 statistical data are visualized. This package offers a flexible, layer-based, way to create thematic maps, such as choropleths and bubble maps.
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.
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.
The tmod package contains definitions of human blood
transcriptional modules and tools to analyse them.
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).
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.
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.
R package for analyzing weighted, two-mode, and
longitudinal networks.
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).
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
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.
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 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).
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.
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.
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.
The tractor.base package consists of functions for working with magnetic resonance images. It can read and write image files stored in Analyze, NIfTI, MGH and DICOM formats (DICOM support is read only), generate images for use as regions of interest, and manipulate and visualise images.
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.
TRAMPR is an R package for matching terminal restriction
fragment length polymorphism (TRFLP) profiles between unknown
samples and a database of knowns.  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.
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.
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.
The trapezoid package provides dtrapezoid, ptrapezoid,
qtrapezoid, and rtrapezoid functions for the trapezoidal
distribution.
Transmission Ratio Distortion (TRD) is a genetic phenomenon where two alleles from either parent are not transmitted to the offspring at the Mendelian 1:1 ratio. Occurrence of TRD in general population can lead to false inflation or attenuation of association signals in case populations. Therefore, it is necessary to adjust for TRD in model fitting of case populations. This package uses models such as loglinear model (Weinberg 1998), augmented loglinear model (Huang 2014), and tests such as TDT (Spielman 1993), augmented TDT (Labbe 2013), on simulated or real datasets. This package has a simulation function which generates a population that is under the influence of TRD, and samples a sub-population, which can serve as the dataset to fit a loglinear model or to perform a TDT. Real dataset with the same data structure as described in the help file of the function 'll' can also be used in the loglinear model and the TDT functions. No real dataset is included in this package.
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
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.
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.
The package simulates 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.
This package implements TreeThresh, a locally adaptive
version of EbayesThresh.
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.
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.
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
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 MCMC simulations of
point data.
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,
between-groups t-tests for multiple groups. 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.
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 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.
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).
This function assign and integrate target peaks in
two-dimentional chromatogram.
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
This package contains 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.
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. Innovative 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.
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.
Interactive laboratory of Time Series based in Box-Jenkins methodology.
This interface was created to develop a standard procedure
of temporal trend analysis in the framework of the OSPAR convention.
It is based on four successive steps : simply manipulate your database,
select the parameters you want to analyse, build your regulated
time series, perform analysis and read the results all in one easy to use
interface. Statistical analysis call other package function such as
Kendall tests (wq package) or cusum function (Pastec package).
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.
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.
This package makes Travel To Work Area from a commuting flow data frame.
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.
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.
This package offers 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 2011-2015.
Maximum likelihood computations for Tweedie families.
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.
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 nonparametric 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.
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.
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'.
Provides simple bindings to version 2 of Unidata's udunits library.
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).
Helper functions for making, running, and reporting SEM models in OpenMx.
If you are just starting, 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.
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 or spheres as grains
together with functions for planar sections.
Data from Unicode 7.0.0 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.
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.
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.
Unit root and cointegration tests encountered in applied
econometric analysis are implemented.
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.
This package provides spatial objects with the boundaries of
states or counties in the United States of America from 1629 to 2000.
It provides data from the Atlas of Historical County Boundaries.
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
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 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.
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.
Implements the variational inference procedure for
Bayesian variable selection, as described in the "Scalable
variational inference for Bayesian variable selection in
regression, and its accuracy in genetic association studies"
(Bayesian Analysis 7, March 2012, pages 73-108). This software
has been used to implement Bayesian variable selection for
large problems 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
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.
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.
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).
Computes a portfolio of European options that replicates
the cost of capturing the realised variance of an equity index.
Generates R scripts useful to perform repetitive
tasks on variables of different classes from a simple database. First it
helps to create a tabular file describing the variables. Then the package
could process this tabulate file to create a script in a .R or .Rmd format.
This script will include code blocks for each variable according to the
variable description. It could help to import, adapt to R classes and
perform descriptive analysis on each variable according to its type. This R
script could be used as it is or it could be modified if necessary to
perform additional analysis. The user could write his own R script template
to produce a customized script.
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.
A package to fit and simulate latent position and cluster
models for statistical networks using a 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-type estimation (prediction) of random effects in linear mixed models is implemented, following
Searle et al. 1991 (ANOVA for unbalanced data). For better performance the SWEEP-Operator is now implemented
for generating the ANOVA Type-1 error sum of squares. The primary objective of this package is to perform
Variance Component Analyses (VCA). This is a special type of analysis frequently used in verifying the
precision performance of diagnostics.
The Satterthwaite approximation of the total degrees of freedom and for individual variance components is
implemented. These are used in the Chi-Squared tests against a claimed value, and in the respective confidence intervals.
Satterthwaite's approximation of denominator degrees of freedom in t-/F-tests of fixed effects are also
available.
There are several functions for extracting, random effects, fixed effects, variance-covariance
matrices of random and fixed effects. Residuals (marginal, conditional) can be extracted as raw, standardized
and studentized residuals.
Additionally, plotting methods for residuals and random effects and a variability chart are available. The latter
is useful for visualizing the variability in sub-classes emerging from the experimental design.
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.
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
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.
This package performs a 2D statistical analysis, 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.
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.
This package contains functions used to perform fuzzy clustering of vegetation data under different models.
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 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.
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.
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.
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. 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,
especially before version 1.0.0 is released; see the NEWS
file for latest changes.
Data sets to accompany the VGAM package.
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).
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).
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.
Tools for bivariate exploratory data analysis, bivariate copula selection and (vine) tree construction are provided. Vine copula models can be estimated either sequentially or by joint maximum likelihood estimation. Sampling algorithms and plotting methods are included. Data is assumed to lie in the unit hypercube (so-called copula data). For C- and D-vines links to the package 'CDVine' are provided.
Implementation of the vine graphical model for building
high-dimensional 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.
Port of the new Matplotlib default color map ('viridis') to R. This color map is designed in such a way that it will analytically be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white. It is also designed to be perceived by readers with the most common form of color blindness.
Provides a framework for generating virtual species distributions,
a procedure increasingly used in ecology to improve species distribution models.
This package integrates the existing methodological approaches with the
objective of generating virtual species distributions with increased
ecological realism.
Provides 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.
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)
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.
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).
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.
Contains 2 new functions for visualization of univariate data: ccdplot and qddplot, along with input data.
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.
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.
Fit the fixed effect panel data model with heteroskedasticity and
autocorrelation correction.
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.
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.
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.
Lets you connect to any CUAHSI WaterOneFlow web service from any hydroserver.
To see list of available hydroservers, see http://hiscentral.cuahsi.org.
The package has five data download functions: GetServices(): show all public
HydroServers 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 endtime, fetch a data.frame of all the observation time series data values.
The data.frame has two columns: time and DataValue. This function has an optional "daily"
parameter, you can set daily="max", daily="min" or daily="mean" to get aggregated daily
values. The GetValues function can also retrieve WaterML 1 or WaterML 2.0 data
from a custom URL. 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 ODM database
via the JSON data upload web service interface.
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.
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.
Provides efficient implementation of the Wild Binary Segmentation and Binary
Segmentation algorithms for estimation of the number and locations of
multiple change-points in the piecewise constant function plus Gaussian
noise model.
Implements 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.
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.
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.
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.
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 AWS logs.
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.
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 that handle the steps for the weighted scores method in Nikoloulopoulos, Joe and Chaganty (2011, Biostatistics, 12: 653-665) for binary (logistic and probit), Poisson and negative binomial regression, with dependent data. Two versions of negative binomial regression from Cameron and Trivedi (1998) are used. Let NB(tau,xi) be a parametrization with probability mass function f(y; tau, xi) = Gamma(tau + y) xi^y / [ Gamma(tau) y! (1 + xi)^( tau + y )], for y = 0, 1, 2, ... , tau > 0 , xi > 0, with mean mu = tau*xi = exp(beta^T x) and variance tau*xi*(1 + xi), where x is a vector of covariates. For NB1, the parameter gamma is defined so that tau=mu/gamma, xi=gamma; for NB2, the parameter gamma is defined so that tau=1/gamma, xi=mu*gamma. In NB1, the convolution parameter tau is a function of the covariate x and xi is constant; in NB2, the convolution parameter tau is constant and xi is a function of the covariate x.
This package currently provides a variety of functions for producing simple weighted statistics, such as weighted Pearson's correlations, partial correlations, Chi-Squareds, histograms, and t-tests.  Also now includes some software for quickly recoding survey data.  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.
Provides computational support for flow over weirs, such as sharp-crested, broad-crested, and embankments. Initially, the package supports broad- and sharp-crested weirs.
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.
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.
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
WideLM fits large numbers of linear models to a fixed
design matrix and response.  An Nvidia GPU is used to
accelerate model fitting, with the CUDA API enabling parallel
execution of multiple individual fits.  The individual models
must have modest size.  The package implements a chunking
interface to the GPU kernel, allowing the caller to stream
model specifications.  Hence the number of fits to be performed
is essentially unlimited.
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' store of semantic data.
Provides an interface to the Wikipedia web application programming interface (API), using internet connection. 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.
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.
Analysing convergent evolution using the Wheatsheaf index.
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.
WITNESS is a computational model intended to understand the
psychological processes underlying eyewitness identification. This package
contains the WITNESS computational model as well as two methods of fitting
the model to data.
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 (OGC). 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.
Analyses individually geo-referenced multilocus genotypes
for the inferences of genetic boundaries between populations.
It is based on the wombling method that estimates the systemic
function by looking for the local variation of the allele
frequencies. The systemic function estimation is based on the
local polynomial regression, and a binomial test assess the
significance of boundaries. The method applies to codominant or
dominant markers and allows for missing data.
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.
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 plankton. Intended for programs
that sample approximately monthly 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.
wrassp is 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. 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 user-friendly version of Wilcox' robust statistics functions (WRS package on GitHub). It implements robust tests for various ANOVA and ANCOVA techniques as described in R. Wilcox (2012) 'Introduction to Robust Estimation and Hypothesis Testing'.
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
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, 8(2):44-63, 2012, proposed by Baoxun Xu, Joshua Zhexue
Huang, Graham Williams, Qiang Wang, and Yunming Ye.  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. (2013).
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
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), and Temporal Network Autocorrelation Models (TNAM).
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.
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.
This package 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 programmed for RKWard.
This package allows the representation of ggplot2 graphs using the
XKCD style.
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.
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.
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 (multi) or a
random sample of them (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.
Tool set for crystallographer to design and analyze crystallization experiments of 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.
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.
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.
Software accompanying the book by Girosi and King: Demographic Forecasting.
Four different forecast models (i.e, OLS, LC, POISSON, and MAP).
The driver of the simulation is function mortality.driver(),
with your choices of input parameters, such as country, disease, and gender, and
many others; please read the software manual.
An R implementation of Yplant, combined with the QuasiMC
raytracer. Calculate radiation absorption, transmission and scattering,
photosynthesis and transpiration of virtual 3D plants.
This package contains various inference procedures associated with a two-sample semi-parametric model that can accommodate a flexible range of hazard ratio patterns. 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.
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.
Zelig is an easy-to-use program that can estimate, and
help interpret the results of, an enormous range of statistical
models. It literally is ``everyone's statistical software'' because
Zelig's simple unified framework incorporates everyone else's (R)
code. We also hope it will become ``everyone's statistical
software'' for applications and teaching, and so have designed
Zelig so that anyone can easily use it or add their programs to it.
Zelig also comes with infrastructure that facilitates the use of
any existing method, such as by allowing multiply imputed data for
any model, and mimicking the program Clarify (for Stata) that takes
the raw output of existing statistical procedures and translates
them into quantities of direct interest.
Add-on package for Zelig. Enables the use of a variety of logit
and probit regressions.
General Additive Models extend GLM's to support the application of
smoothing functions to the predictor terms.
Add-on package for Zelig. Enables the use of multilevel (mixed-effect) 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.
This package 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.
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
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 questions and comments regarding BH to
http://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/boostheaders-devel
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>
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 <r.dematossimoes@qub.ac.uk>
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>
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>
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>
Alejandro Quintela del Rio <aquintela@udc.es>
Jorge Luis Ojeda Cabrera <jojeda@unizar.es>
Eufrasio de A. Lima Neto <eufrasio@de.ufpb.br>
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>
Rune Haubo Bojesen Christensen <rune.haubo@gmail.com>
Euloge Clovis Kenne Pagui <kenne@stat.unipd.it>
Joaquin Bienvenido Ordieres Mere <j.ordieres@upm.es>
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>
Raymond K. W. Wong <raymondkww.dev@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>
Rune Haubo Bojesen Christensen <rhbc@dtu.dk>
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>
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>
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.
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
2015-03-17 02:31:38 UTC; Jose Antonio Garcia
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
2015-05-19 12:00:31 UTC; LARMARANGE Joseph
2014-08-28 18:37:46 UTC; Sophie Baillargeon
2014-10-17 18:39:03 UTC; Christiane Dargatz
2014-12-04 17:04:02 UTC; Sophie Baillargeon
2014-10-24 12:34:10 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()
JAGS (>= 3.4.0) (see
http://mcmc-jags.sourceforge.net)
jags (>= 3.3.0, see
http://mcmc-jags.sourceforge.net)
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)
Nvidia CUDA driver (>= 270.xx.xx), Nvidia CUDA
Toolkit (>= release 3.0)
OpenCL library; double-precision AMD or Nvidia GPU;
GNU make
Java (>= 7.0); Stanford CoreNLP
<http://nlp.stanford.edu/software/corenlp.shtml> (>= 3.5.2)
couchDB instance to connect to and work on.
nvcc (release >= 3.1) (NVIDIA Cuda Compiler
driver); Linux operating system; GNU make.
libcurl: libcurl-devel (rpm) or
libcurl4-openssl-dev (deb).
none, one or more of JAGS (>= 3.0.0), WinBUGS (>=
1.4), OpenBUGS (>= 3.2.2)
Xft (only needed for platforms other than OSX and
Windows)
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 4.0) and Nvidia
GPU with compute capibility >=2.0
libhdf5 (>= 1.8.x, v18 API) with C++ interface
enabled (--enable-cxx=yes) and v18 API
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.
Boost.Asio and Boost.Regex from
http://www.boost.org/. See README.
ImageJ (>=1.48) (see http://imagej.nih.gov/ij/),
Java
At least trial version of LocalSolver to be
downloaded from http://www.localsolver.com/download.html
ADMB version 11 (http://admb-project.org/) for
use.admb=TRUE; see readme.txt
OpenSSL: libssl-dev (deb) or openssl-devel (rpm) or
libssl_dev (csw). SASL: libsasl2-dev (deb) or cyrus-sasl-devel
(rpm) or sasl_dev (csw).
pandoc, ipython (>= 3.0) or jupyter,
ipython/jupyter notebook optional dependencies, pywin32 (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 and Mac,
MPICH2 (>= 1.4.1p1) on Windows
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 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.
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)
JAGS (>= 3.2.0) (see
http://mcmc-jags.sourceforge.net)
proj 4.4.6 or higher (http://proj.maptools.org/)
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()
Pandoc (http://johnmacfarlane.net/pandoc) for
exporting markdown files to other formats.
A valid BBG installation. API headers and dynamic
library are downloaded from <https://github.com/Rblp/blp>
during the build step.
GMP (GNU MP bignum library from http://gmplib.org/)
pandoc (>= 1.12.3) -
http://johnmacfarlane.net/pandoc
A Debian-based system with the libapt-pkg-dev
package
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)
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.
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.
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://trac.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)
GLPK library package (e.g., libglpk-dev on
Debian/Ubuntu)
R built as a shared or static library, 'MPI'
library.
JAGS (>= 3.0.0) (see
http://mcmc-jags.sourceforge.net)
Java JDK 1.2 or higher (for JRI/REngine JDK 1.4 or
higher), GNU make
Java (>= 1.5), zlib headers and library.
Oracle Java 7,Apache Kafka 2.8.0-0.8.1.1
curl (version 7.12.0 or higher)
<http://curl.haxx.se>
notepad.exe, mark.exe (>= 8.0) (or mark32.exe and
mark64.exe) and rel_32.exe (see README.txt)
libmariadb-client-dev / libmysqlclient-dev (deb),
mariadb-devel (rpm), mariadb or 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 (>= 1.4.0) 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
Binary executables of X-13-ARIMA-SEATS
(installation notes: see README or vignette)
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
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
PARI/GP >= 2.3.0 [strongly recommended for
logkda()]
V8: libv8-dev (deb), v8-devel (rpm), v8-3.14 (arch)
Nvidia's CUDA toolkit (release >= 4.1); Linux
operationg system; gcc (release <= 4.5).
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
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 Computation via Random Forests
Data Modelling with Additive Bayesian Networks
Abundant regression and high-dimensional principal fitted
components
Functions for Processing Minute-to-Minute Accelerometer Data
Creation and Evaluation of Acceptance Sampling Plans
Data Quality Visualization Tools for Partially Accruing Data
Tools for Autoregressive Conditional Duration Models
ace() and avas() for selecting regression transformations
Analysing Conditional Distributions of Income
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
Download, manipulate, and present data from the US Census
American Community Survey
Algorithmic Complexity for Short Strings
Data Only: Algorithmic Complexity of Short Strings (Computed via
Coding Theorem Method)
Asymptotic Classification Theory for Cognitive Diagnosis
Actuarial Functions and Heavy Tailed Distributions
ada: an R package for stochastic boosting
Applies Multiclass AdaBoost.M1, SAMME and Bagging
Discrete and Global Optimization Routines
Adaptive Semiparametric Regression with Simultaneous Confidence
Bands
Implementation of a generic adaptive Monte Carlo Markov Chain
sampler
Fit Additive Hazards Models for Survival Analysis
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 generation of pseudo-random
numbers
calculate ad hoc distance thresholds for DNA barcoding
identification
An Interpretation of the ADM method - automated detection
algorithm
Adaptive Mixture of Student-t distributions
Fast Clustering Using Adaptive Density Peak Detection
Wavelet Analysis of Genomic Data from Admixed Populations
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
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
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 spaced data
Adaptive Kmeans algorithm based on threshold
Quantile Regression Using Asymmetric Laplace Distribution
An R-package for estimating absolute protein quantities from
label-free LC-MS/MS proteomics data
Alignment of Phonetic Sequences Using the 'ALINE' Algorithm
Generate Age-Length Keys for fish populations
Allele simulation 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
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
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
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)
Process the Apache Web Server Log Combined 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)
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
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
Example Datasets from Archaeological Research
Plant Root System Architecture Analysis Using DART and RSML
Files
Tools for Storing, Restoring and Searching for R Objects
Activated Region Fitting, fMRI data analysis (3D)
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
Application in R for Queueing Analysis and Simulation
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
A Collection of Statistical Tools for Biologists
Export R objects to several markup languages
Simulations for adaptive seamless designs
Linkage Map Construction using the MSTmap Algorithm
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
Assertive Programming for R Analysis Pipelines
Optimal pricing of assets with fixed expiry date
A Suite of R Functions Implementing Spline Smoothing Techniques
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
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
Sparse Autoencoder for Automatic Learning of Representative
Features from Unlabeled Data
Automated Hierarchical Multiple Regression with Assumptions
Checking
Partial Least Squares Regression with Backward Selection of
Predictors
Automated Vector Autoregression Models and Networks
Class and Methods definitions for packages aws, adimpro, fmri,
dwi
Discover, Publish and Consume Web Services on Microsoft Azure
Machine Learning
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
Bayesian Analysis of Computer Code Output (BACCO)
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
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
Recovering a Basic Space from Issue Scales
A package for estimating age-specific survival from incomplete
capture-recapture/recovery data
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
Bayesian Feature Allocation Model for Tumor Heterogeneity
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 Melding of GPS and DR Path for Animal Tracking
Bayesian Beta regression: joint mean and precision modeling
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 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
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
Bayesian clustering using spike-and-slab hierarchical model,
suitable for clustering high-dimensional data
Bayesian Analysis of Change Point Problems
Behavioral change point analysis of animal movement
Bayesian Multiple Changepoint Detection Using Metadata
Bayesian continual reassessment method (CRM) designs for Phase I
dose-finding trials
Cross-Validation for the SVD (Bi-Cross-Validation)
Bayesian Graph Selection Based on Birth-Death MCMC Approach
Inference and design for predictive values in binary diagnostic
tests
Remove Weekends and Holidays From ggplot2 Axes
Routines for Block Diagonal Symmetric matrices
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
Quantifies effects of geo/eco distance on genetic
differentiation
Easily Play Notification Sounds on any Platform
The Bee Swarm Plot, an Alternative to Stripchart
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
Detecting rare variants for quantitative traits using nuclear
families
Beta-Diversity Within a Metaweb of Species Interactions
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
Breaks For Additive Season and Trend (BFAST)
Binary Generalized Extreme Value Additive Models
Bayesian Estimation in Generalized Linear Models
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
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
A library of utilities for big.matrix objects of package
bigmemory
Case-Control Analysis of Multi-Allelic Loci
Scalable Least-Angle Regression and Lasso
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
Big Random Forests: Classification and Regression Forests for
Large Data Sets
Generalized Ridge Regression (with special advantage for p >> n
cases)
table-, tapply-, and split-like functionality for matrix and
big.matrix objects
Top Scoring Pair based methods for classification
Power for SNP analyses using silver standard cases
Estimates Mixture Models for Case-Control Data
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
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
Package for Community Ecology and Suitability Analysis
Analyze Biogas Data and Predict Biogas Production
BioGeography with Bayesian (and Likelihood) Evolutionary
Analysis in R Scripts
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
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
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
Estimating the Parameters of Some Bivariate Distributions
Sample size calculations for bivariate longitudinal data
Conduct Univariate and Bivariate Wavelet Analyses
Functions to compute the biweight mean vector and covariance &
correlation matrices
Business Days Calculations and Utilities
Plots (slightly extended) Bland-Altman plots
Calculate and Analyze Blau statuses for measuring social
distance
Black-Litterman and Copula Opinion Pooling Frameworks
Analyze biotic homogenization of landscapes
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, contingency, continuous and
categorical 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
Constrained Optimization Via Stochastic Gradient Descent
Request Data From The U.S. Bureau of Labor Statistics API
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
Learning Bayesian Network Classifiers from Data
Data Generator based on Bayesian Network Model
Bayesian Network Structure Learning, Parameter Learning and
Inference
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
Bayesian Network Structure Learning from Data with Missing
Values
Bayesian Output Analysis Program (BOA) for MCMC
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 Design for Phase I Clinical Trials
Construction, Simulation and Analysis of Boolean Networks
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
Bootstrap Tolerance Levels for Credit Scoring Validation
Statistics
Bayesian Ordination and Regression AnaLysis
Wrapper Algorithm for All-Relevant Feature Selection
Boosted One-Step Statistics: Fast and accurate approximations
for GLM, GEE and Mixed models for use in GWAS
a Bunch of Structure and Sequence Analysis
Analytic Solutions for (ground-water) Boussinesq Equation
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
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
Species richness estimation and modelling
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
brnn (Bayesian regularization for feed-forward neural networks)
Convert Statistical Analysis Objects into Tidy Data Frames
Interface to the 'OpenBUGS' MCMC Software
Statistical methods for safety assessment in agricultural field
trials
Bayesian Survival Model 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
Buckley-James Regression for Survival Data with High-Dimensional
Covariates
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 ordinary differential
equations
Bayesian Variant Selection: Bayesian Model Uncertainty
Techniques for Genetic Association Studies
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
Multiple imputation using MICE and Random Forest
Calibration of Scatterplot and Biplot Axes
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 Photograph Management and Preparation of Occupancy
Analyses
Estimation of Temporal Ordering of Cancer Abnormalities
Visualizing Generalized Canonical Discriminant and Canonical
Correlation Analysis
Combined analysis of pleiotropy and epistasis
Comparative Analyses of Phylogenetics and Evolution in R
Numbers Figures and Creates Simple Captions
Capushe, data-driven slope estimation and dimension jump
Estimates population size from non-invasive sampling
Spatial Generalised Linear Mixed Models for Areal Unit Data
Data Sets Used in the Vignette Accompanying the CARBayes Package
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
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
CRISPR AnalyzeR for Pooled CRISPR Screens
Reparameterized and marginalized posterior sampling for
conditional autoregressive models
Reparameterized and marginalized posterior sampling for
conditional autoregressive models, OpenCL implementation
Séries temporelles avec R - Méthodes et cas
Identify similar cases for qualitative case studies
Analysis of categorical-variable datasets with missing values
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
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
R Package for Covariate Balancing Propensity Score
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
Cox Model for Case-Cohort Data with Stratified
Subcohort-Selection
Convex Clustering Methods and Clustering Indexes
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 of light scattering by clusters of
nanoparticles
Retrieve U.S. Flu Season Data from the CDC FluView Portal
Conditional Distance Correlation and Its Related Feature
Screening Method
Coordinate Descent Algorithms for Lasso Penalized L1, L2, and
Logistic Regression
Components of Canadian Monetary and Credit Aggregates
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
Modeling Censored Data Using Mixture Regression
Fits Normal and Student-t Censored Regression Model
Cross-Entropy R Package for Optimization
Context Driven Exploratory Projection Pursuit
Outlier detection using the iterated RMCD method of Cerioli
(2010)
Covariance Estimation Regularized by Nuclear Norm Penalties
Analysis of configuration frequencies (CFA)
Cause-Specific Framework for Competing-Risk Analysis
Estimate quantiles using any order Cornish-Fisher expansion
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
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
A tool for the design of synthetic experiments in machine
olfaction
Multiple Testing Methods for Exploratory Research
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
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
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
CircNNTSR: An R package for the statistical analysis of circular
data using nonnegative trigonometric sums (NNTS) models
Detecting of Outliers in Circular Regression
Circular Statistics, from "Topics in circular Statistics" (2001)
CIT Breast Cancer Molecular SubTypes Prediction
CIT Colon Cancer Molecular SubTypes Prediction
Visualization of structure and contents of a database
Optimal k-Means Clustering for One-Dimensional Data
Measuring Morphological Diversity and Evolutionary Tempo
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
CLERE methodology for 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
Climate Classification According to Several Indices
Constrained L1-minimization for Inverse (covariance) Matrix
Estimation
Clinical Trial Design and Data Analysis Functions
Constrained Inference for Linear Mixed Effects Models
Fitting exact conditional logistic regression with lasso and
elastic net penalties
Central Limit Theorem Experiments (Theoretical and Simulation)
Clustering Method Based on Local Shrinking
"Finding Groups in Data": Cluster Analysis Extended Rousseeuw et
al.
Explore clustering interactively using R and GGobi
A hierarchical clustering method based on genetic algorithms
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
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
Clustering of Observations with Geographical Constraints
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
Control Charts for Conway-Maxwell-Poisson Distribution
Subdistribution Analysis of Competing Risks
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
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
COBS -- COnstrained B-Splines (Sparse matrix based)
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
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
Collocation Inference for Dynamic Systems
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
Tools for colors in a Hue-Saturation-Value (HSV) color model
Synergy/Antagonism Analyses of Drug Combinations
Construction Methods of some Series of PBIB Designs
Exact Test from the Combinations of Mutually Exclusive
Alterations (CoMEt) Algorithm
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
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
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
Primal or Dual Cone Projections with Routines for Constrained
Regression
Confidence Estimation of Environmental State Classifications
Conformal Prediction for Regression and Classification
Configural Frequencies Analysis Using Log-Linear Modeling
A package to check the cancellation axioms of conjoint
measurement
Tools for working with connectivity matrices
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
Contouring of Non-Regular Three-Dimensional Data
Median Comparison for Two-Sample Right-Censored Survival Data
Quantifies and assesses the significance of convergent evolution
Probabilistic Species Co-occurrence Analysis in R
Cooperative aspects of optimal trees in weighted graphs
Tools for processing COPAS large-particle flow cytometer data
General Bivariate Copula Theory and Many Utility Functions
Fitting the copCAR Regression Model for Discrete Areal Data
Coverage Probability Excursion (CoPE) Sets
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
Generate correlated count random variables
Classification, Regression and Feature Evaluation
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
Nonparametrics with Clustered Binary and Multinomial Data
Linear Regression Based on Linear Structure Between Covariates
Multivariate Data Generation by Permutation
A collection of functions for graphing correlation matrices
Estimate Correlations Between Repeatedly Measured Endpoints
(E.g., Reliability) Based on Linear Mixed-Effects Models
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
Mean and variance modeling of count data
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
Computes covariance test for adaptive linear modelling
Streamlined Plot Theme and Plot Annotations for 'ggplot2'
Cox models by likelihood based boosting for a single survival
endpoint or competing risks
Cox-Type Models for Interval-Censored Data
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
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
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
Downloads and Builds datasets for Climate Reference Network
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
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)
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
Continuous Time Structural Equation Modelling
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"
Analyze Multivariate Phenotypes by Combining Univariate results
Extends ddply to allow calculation of cumulative quantities
Change point detection in genomic sequences
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
curvHDR filtering of flow cytometry samples
Cusp-Catastrophe Model Fitting Using Maximum Likelihood
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
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
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
Functions Useful in the Design and ANOVA of Experiments
Design and Analysis of Experiments with R
Learning directed acyclic graphs (DAGs) through bootstrap
aggregating
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-Bolzmann-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
dataframes2xls writes data frames to xls files
An R package to convert data sets for import into JAGS, WinBUGS
and OpenBUGS and to generate data.frames for predicting the
effects of particular variables
A system for mapping foreign objects to R variables and
environments
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
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
methods of distance-based gene set functional enrichment
analysis
Discrete Beta Kernel Graduation of Mortality Data
Compute the NPMLE of distribution from doubly censored data
Distance-Based Measures of Spatial Structures
A Database Exploration Tool with Assisted Querying and Schema
Exploration
Density Based Clustering of Applications with Noise (DBSCAN) and
Related Algorithms
A Package for Image Analysis of DCE-MRI (S4 Implementation)
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
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)
Learning Bayesian Networks with Mixed Variables
Deconvolution density estimation with adaptive methods for a
variable prone to measurement error
Get Energy Data from the UK Dept of Energy and Climate Change
DEComposition of Indirect and Direct Effects
Quantitative Support of Decision Making under Uncertainty
Differential Co-Expression and Differential Expression Analysis
Deconvolution Estimation in Measurement Error Models
Additional dialogs and functions for Deducer
Deductive Correction, Deductive Imputation, and Deterministic
Correction
Dirichlet-multinomial Evolutionary Event Profile Randomization
(DEEPR) test
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
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
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
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
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
Seasonal Adjustment by Frequency Analysis
R interface to DescribeDisplay (GGobi plugin)
Optimal deseasonalization for geophysical time series using AR
fitting
Computational tool for designing genetical genomics experiments
Desirability Functions for Ranking, Selection, and Data
Integration
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
Analyzing Wildlife Data with Detection Error
Detect Data Containing Personally Identifiable Information
DetMCD Algorithm (Robust and Deterministic Estimation of
Location and Scatter)
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
Capture-Recapture Estimation using Bayesian Model Averaging
Differential Geometric LARS (dgLARS) method
dgmb Simulating data for PLS structural models
Double Hierarchical Generalized Linear Models
Block Diagonal Extraction or Replacement
Functions for visualising simple graphs (networks), plotting
flow diagrams
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
Defines some physical constants and dielectric functions
commonly used in optics, plasmonics
Detection of Differential Item Functioning (DIF) in Rasch Models
by Boosting Techniques
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
Baseline identification and peak decomposition for x-ray
diffractograms
A penalty approach to Differential Item Functioning in Rasch
Models
Collection of Methods to Detect Dichotomous Differential Item
Functioning (DIF)
Item Focused Trees for the Identification of Items in
Differential Item Functioning
Create Cryptographic 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
Direct labels for multicolor plots in lattice or ggplot2
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
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
2D Hausdorff and Simplex Dispersion Orderings
Disparity Filter Algorithm of Weighted Network
Create Disposable R Packages for Testing
Utilities for making pairwise comparisons of multivariate data
Distance Sampling Detection Function and Abundance Estimation
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 Packages distr, distrEx, distrSim, distrTEst,
distrTeach, distrMod, and distrEllipse
S4 classes for elliptically contoured distributions
Object Oriented Implementation of Probability Models
Package distr 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
diversitree: comparative phylogenetic analyses of
diversification
A Comprehensive, General Purpose Population Genetics Analysis
Package
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
Bayesian and Likelihood Analysis of Dynamic Linear Models
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 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 for the multicore 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
Dirichlet Process Mixture model simulation for clustering and
image segmentation
Semi- and nonparametric Bayesian Subset Selection Procedures
Methods for Dimension Reduction for Regression
Doubly Robust Generalized Estimating Equations
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
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'
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
Time Series Clustering with Dynamic Time Warping
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
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
A Dynamic Nomogram for Linear and Generalized Linear Models as
Shiny Applications
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
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
Evaluation of stratified genome-wide association meta-analysis
results
Entropy reweighting to create balanced samples
Empirical Bayes Thresholding and Related Methods
Empirical Bayes Estimation of Dynamic Bayesian Networks
Genotyping 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
Functions for Spatial Point Pattern Analysis
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"
Ecological regression using aggregate and individual data
Procedures for Ecological Assessment of Surface Waters
Non-Parametric Multiple Change-Point Analysis of Multivariate
Data
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
Empirical Differentially Methylated Regions Calculation
Estimation of the effective dimension reduction (EDR) space
Provides tools for dimension reduction methods
Tools for analysis and classification of electroencephalography
(EEG) data
Read and Analyze Fluorescence Excitation-Emission Matrix (EEM)
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
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
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
Functions for drawing ellipses and ellipse-like confidence
regions
Implementation of ELM (Extreme Learning Machine ) algorithm for
SLFN ( Single Hidden Layer Feedforward Neural Networks )
Animal Dominance Hierarchies by Elo Rating
ELT - A package to build Experience Life Tables
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
Evolutionary Monte Carlo (EMC) methods for clustering
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
End-member modelling algorithm and supporting functions for
grain-size analysis
Contrasts in mixed effects for EMMIX model with random effects
The EM Algorithm and Skew Mixture Distribution
Fitting Unrestricted Multivariate Skew t Mixture Models
Fitting Mixed Models with Known Covariance Structures
Eye Movement Analysis Package for Fixation and Saccade Detection
Expected Maximum Profit Classification Performance Measure
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
Entropy Minimization over Variable Clusters (EMVC)
R Package for Fitting Multinomial Probit Models with Endogenous
Selection
R Package for Analyzing Endorsement Experiments
Data sets from "Introductory Statistics for Engineering
Experimentation"
Automated runs and evaluations of ecological niche models
Ensemble Partial Least Squares (EnPLS) Regression
Enrichment assessment of virtual screening approaches
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
Integration of Base Learners
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
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
A Collection of Epidemic/Network-Related Tools
Tools for the Analysis of Epidemiological Data
Basic Sensitivity Analysis of Epidemiological Results
Density Estimation with Soft Information by Exponential
Epi-splines
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
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
ERG Modeling Based on Graphlet Properties
Local Health Department network data set
User-specified terms for the statnet suite of packages
Significance analysis of Event-Related Potentials data
Event-related potentials (ERP) analysis, graphics and utility
functions
Estimate Number of Latent Factors and Factor Matrix for Factor
Analysis
ESEA: Discovering the Dysregulated Pathways based on Edge Set
Enrichment Analysis
Toolkit for the simulation of financial assets and interest
rates models
Calibrating Parameters for the Samejima's Continuous IRT Model
Estimation of Heritability in High Dimensional Sparse Linear
Mixed Models using Variable Selection
Modeling earthquake data using Epidemic Type Aftershock Sequence
model
Mixed FLP and ML Estimation of ETAS Space-Time Point Processes
Utility Functions to Execute Standard Extract/Transform/Load
Operations (using Package 'ff') on Large Data
eulerian: A package to find eulerian paths from graphs
Parsing and Evaluation Tools that Provide More Details than the
Default
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
Tools for Evolutionary Quantitative Genetics
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
experiment: R package for designing and analyzing randomized
experiments
Modeling without data using expert opinion
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"
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
Extremely Randomized Trees (ExtraTrees) Method for
Classification and Regression
Estimate Lower Extreme Quantile with the Censored Weibull MLE
and Censored Weibull Mixture
Easy analysis and visualization of factorial experiments
selects significant non-additive interaction between two
variables using fast GLM implementation
provide an easy to use framework to conduct simulation
Bayesian Sparse Factor Analysis model for the inference of
pathways responsive to drug treatment
Combination of Factorial Methods and Cluster Analysis
Multivariate Exploratory Data Analysis and Data Mining
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
File Abstraction Interface Layer (FAIL) mimicking a key-value
store
Faisal Conjoint Model: A New Approach to Conjoint Analysis
Finding Allele-specific Copy Number in Next-Generation
Sequencing Data
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 Linear Programming Problems and
Constrained L1 Minimization Approach to Sparse Precision Matrix
Estimation
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 Rcpp implementation of Gauss-Hermite quadrature
Efficiently Using Gaussian Processes with Rcpp and RcppEigen
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
Fast Computation of Multivariate M-estimators
FastPCS Robust Fit of Multivariate Location and Scatter
Foundations and Applications of Statistics Using R
FastRCS Robust Fit of 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 Polytomous 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
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
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
Estimation of (Local) False Discovery Rates and Higher Criticism
Frequency Distribution Tables, Histograms and Polygons
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
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
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
File-Backed Matrix Class with Convenient Read and Write Access
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
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
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
Fits Piecewise Constant Models with Data-Adaptive Knots
Implementation of optimal hierarchical clustering
Flexible Parametric Models for Censored and Truncated Data
Flexible Parametric Survival and Multi-State Models
Tools for Interacting with the Brazilian Flora Checklist
Tools for characterizing flowering traits
Forecasts future values of a univariate time series
Streamlining Design and Deployment of Complex Workflows
Path algorithm for the general Fused Lasso Signal Approximator
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
Functions for medical statistics book with some demographic data
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
Foraminifera and Community Ecology Analyses
Forecasting Functions for Time Series and Linear Models
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
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
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
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 Moving Average Plots (MAP) of Multinomial Data by a
Continuous Covariate
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
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++)
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
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
Exact calculation of fuzzy decision rules for multiple testing
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 Questionnaires (or Other 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
Statistical Estimation of Game-Theoretic Models
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
Difference measures for multivariate Gaussian probability
density functions
Collection of functions for Gaussian quadrature
Gazepath Transforms Eye-Tracking Data into Fixations and
Saccades
Generalize Lambda Distribution and Generalized Bootstrapping
Generalized Beta Distribution of the Second Kind: Properties,
Likelihood, Estimation
Utilities for processing Rd objects and files
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
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
Modified Variance Estimators for Generalized Estimating
Equations
Calculate Generalized Eigenvalues, the Generalized Schur
Decomposition and the Generalized Singular Value Decomposition
of a Matrix Pair
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
Genetic Class Association Testing (GenCAT)
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
Genetic Epidemiology Design and Inference
Blinder-Oaxaca Decomposition for Generalized Linear Model
Generate Data Containing Fake Personally Identifiable
Information
Construct time delay gene regulatory network
Identify Favorable Subsets of Germplasm Collections
Collection of Genetic Data Analysis Tools
The Forward Imputation: A Sequential Distance-Based Approach for
Imputing Missing Data
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 Publication-Grade Gene and Genome Maps
Simulation of Ordinal and Discrete 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
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
Quantification of the effect of geographic versus environmental
isolation on genetic differentiation
Convert Data from and to 'geoJSON' or 'topoJSON'
Data for topographic and Geologic Mapping
Geometric Morphometric Analyses of 2D/3D Landmark Data
Interface to www.geonames.org web service
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
Estimation and Fit Diagnostics for Generalized Exponential
Random Graph Models
Parsing Command-Line Arguments and Variable Interpolation
GetR: Calculate Guttman error trees in R
General-to-Specific (GETS) Modelling and Indicator Saturation
Methods
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. 2013 Global Forest Change
dataset
Tools for extracting dendrogram and tree diagram plot data for
use with ggplot2
GGEBiplotGUI: Interactive GGE Biplots in R
Visualization Tools for Genealogical Data
Add Marginal Histograms to 'ggplot2', and More 'ggplot2'
Enhancements
Group Lasso Penalized Learning Using A Unified BMD Algorithm
Tools for Analyzing MCMC Simulations from Bayesian Inference
Variations of Parallel Coordinate Plots for Categorical Data
An Implementation of the Grammar of Graphics
North Symbols and Scale Bars for Maps Created with 'ggplot2' or
'ggmap'
Explore complex data by embedding subplots within plots
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 the 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
Generalized Iterative Proportional Fitting for Relational Models
The giRaph package for graph representation in R
an R package for quantification of pinned microbial culture
Constructing panels of population pyramid plots based on lattice
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) in R
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
Fitting Generalized Linear Models Subject to Constraints
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
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
Fitting and Testing Generalized Logistic Distributions
Generalized Logrank Tests for Interval-censored Failure Time
Data
Generalized Least Squares with Measurement Error
Fast Estimation of Gaussian Mixture Copula Models
Graph Based Multiple Comparison Procedures
Generalized Minimum Distance of distributions
Predicting and Forecasting Time Series via GMDH-Type Neural
Network Algorithms
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
Model-diagnostics based on cumulative residuals
Testing Goodness-of-Fit with the Kernel Density Estimator
Tests of Fit for some Probability Distributions
Classical Goodness-of-Fit Tests for Univariate Distributions
Generalized Orthogonal GARCH (GO-GARCH) models
Easy Authentication with Google OAuth2 APIs
Working with Google Public Data Explorer DSPL Metadata Files
Visualization of Functional Analysis 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
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 Testing
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
GraphPCA, Graphical tools of histogram PCA
Cluster Detection with Hypothesis Free Scan Statistic
Inference in Graphical Gaussian Models with Edge and Vertex
Symmetries
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
Bayesian semi and nonparametric growth curve models that
additionally include multiple membership random effects
Bayesian non-parametric dependent models for time-indexed
functional data
Bayesian reconstruction of growth velocity
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
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
Group Sequential Design in Equivalence Studies
Download Google Sheets Using Just the URL
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
Maps, data and methods related to Guerry (1833) "Moral
Statistics of France"
Implementation of Sampling Formulas for the Unified Neutral
Model of Biodiversity and Biogeography, with or without Guild
Structure
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
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
Genome-wide significance for whole genome sequencing studies
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
Haplotype Inference and Statistical Analysis of Genetic
Variation
Graphical Tests 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
Hawkes process simulation and calibration toolkit
Damage functions from FEMA's HAZUS software for use in modeling
financial losses from natural disasters
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
Use known groups in high-dimensional data to derive scores for
plots
Hierarchical DECOmposition of Entropy for Categorical Map
Comparisons
Statistical Analysis Tools for High Dimension Molecular Data
(HDMD)
Nomograms for High-Dimensional Cox Models
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
Package for robust estimation using heavy-tailed distributions
Visualizing Hypothesis Tests in Multivariate Linear Models
Hierarchical Exponential-Family Random Graph Models
Marker-Based Estimation of Heritability Using Individual Plant
or Plot Data
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
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
Hierarchical Multiplicative Partitioning of Complex Phenotypes
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
Determining and Evaluating High-Risk Zones
Simultaneous Critical Values for t-Tests in Very High Dimensions
Estimation of Heritability in Linear Mixed Models
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
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: Modeling, Visualization, and
Two-Group Comparison
Flux Estimation with Static Chamber Data
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
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 Huber Loss Regression and Quantile
Regression Penalized by Lasso or Elastic-Net
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
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 sequencing (HTS) data
compute HUM value and visualize ROC curves
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
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
Work with Hyperspectral Data, i.e. Spectra + Meta Information
(Spatial, Time, Concentration, ...)
High-Dimensional Kernel Density Estimation and Geometry
Operations
Macroevolutionary phylogentic analysis of species trees and gene
trees
Confidence Intervals and Tests of Statistical Hypotheses
Tools for Modeling Rate-Dependent Hysteretic Processes and
Ellipses
The Irvine Robustness Assessment for Qualitative Comparative
Analysis
Model selection for index of asymmetry distribution
Functions to use with data from the Implicit Association Test
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
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
Facilitating Estimation of the Intraclass Correlation
Coefficient
Multilevel model intraclass correlation for slope heterogeneity
Tools for Working with ICD-9 Codes, and Finding Comorbidities
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
Estimation of number of clusters and identification of atypical
units
Inequality constrained inference in linear normal situations
Integrative clustering of multiple genomic data types
Tools for Exploring Multivariate Data via ICS/ICA
A package for semiparametric regression analysis of
interval-censored data
Jacquard Condensed Coefficients of Identity
Utilities of Institute of Data Analyses and Process Design
(www.idp.zhaw.ch)
Imprecise Dirichlet Process for Survival Analysis
Identify Turtles by their Plastral Biometries
R Analysis package for iDynoMiCS Simulation Results
Functions to set and get the IEEE rounding mode
An integrative factor analysis model for drug-pathway
association inference
Toolkit for Item Factor Analysis with OpenMx
Italian Fiscal Code ('Codice Fiscale') Utilities
Incremental Feature Selection Algorithm accelerated by GPU
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
Lee-Carter Mortality Models using Iterative Fitting Algorithms
Identifying Causal Effect for Multi-Component Intervention Using
Instrumental Variable Method
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
Mixture models for longitudinal count data
Nonparametric tests of independence between random vectors
A simple R Wrapper for the indico set of APIs - http://indico.io
Relationship Between Species and Groups of Sites
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
Case Influence in Structural Equation Models
Information Decomposition of Two-phase Experiments
Performance Analysis and Companion Functions for Accuracy
Improvement for Binary Classification Problems
Sequence Statistics for Relational Event Models
Functions to Inline C, C++, Fortran Function Calls from R
Convert inline comments to documentation
insideRODE includes buildin functions with deSolve solver and
C/FORTRAN interfaces to nlme, together with compiled codes
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
Iterated Convex Minorant Algorithm for interval censored event
data
Tests for marginal interactions in a 2 class response model
interactive network analysis and visualization
Compute Chi-Square Measures with Corrections
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
linear programming solver by the interior point method and
graphically (two dimensions)
methods for analyzing introgression between divergent lineages
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
Manipulate, Validate and Resolve IP Addresses
Regression methods for interval-valued variables
Classes and Methods for Seismic Data Analysis
Fast partial SVD by implicitly-restarted Lanczos
bidiagonalization
Various Coefficients of Interrater Reliability and Agreement
Simple interface to the estimation and plotting of IRT models
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
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
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
A Fast Parameter Estimation Method for Evolutionary Biology
Non-parametric Jackstraw for Principal Component Analysis
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 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 Modeling of Longitudinal and Survival Data - Power
Calculation
Joint modelling of repeated measurements and time-to-event data
Penalized Likelihood Estimation under the Joint Cox Models
Between Tumour Progression and Death for Meta-Analysis
Joint Approximate Diagonalization of a set of square matrices
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
Methods for population-based cancer survival analysis
A Robust, High Performance JSON Parser and Generator for R
Package to identify and sort genes overexpressed
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
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
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
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
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 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
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
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
Kolmogorov-Zurbenko Fourier Transform and Applications
Kolmogorov-Zurbenko Spatial Smoothing and Applications
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
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
Analyze and Gaussianize Heavy-Tailed, Skewed Data
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"
Local Average Response Functions for Instrumental Variable
Estimation of Treatment Effects
Least Angle Regression, Lasso and Forward Stagewise
Likelihood Analysis of Speciation/Extinction Rates from
Phylogenies
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 and Other Tools
Collapsed Gibbs sampling methods for topic models
Multivariate Condition Matching by Backwards Elimination Using
Linear Discriminant Analysis
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
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
Likelihood Estimation of Admixture in Parents From Offspring
Genotypes
latent effect adjustment after primary projection
Functions for Learning Bayesian Inference
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
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
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
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
Tools for Communication with Lightning-Viz Server
Methods for Maximum Likelihood Estimation
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)
Tools for Generating, Visualizing, and Analysing Link
Communities in Networks
Linkage information based genotype imputation method
Interactive Interpretation of Linear Regression Models
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
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
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
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
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"
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
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 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 for 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
Different types of estimators to deal with multicollinearity
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
American options pricing with Least Squares Monte Carlo method
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
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
Accurate Estimation of Clonal Coincidences and Abundances from
Biological Replicates
Binary and Multiclass Boosting Algorithms
Class prediction based on microarray data and clinical
parameters
A Flexible Microarray Data Simulation Model
Pretty Scientific Plotting with Minor-Tick and log Minor-Tick
Support
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
Access and Process Data and Documents of the Manifesto Project
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
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
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
Structural Estimators and Algorithms for the Analysis of Stable
Matchings
MatchIt: Nonparametric Preprocessing for Parametric Casual
Inference
Combining Matching and Linear Regression for Causal Inference
Measuring Association and Testing Independence Efficiently
Sparse and Dense Matrix Classes and Methods
Collection of functions for matrix calculations
Matrix eQTL: Ultra fast eQTL analysis via large matrix
operations
Modelling with Sparse And Dense Matrices
Matrix-based Partial Least Squares estimation
Methods that Apply to Rows and Columns of Matrices (and to
Vectors)
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
Model species distributions by estimating the probability of
occurrence using presence-only data
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
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
Global optimization using Monte Carlo and Quasi Monte Carlo
simulation
Monte Carlo hypothesis tests with Sequential Stopping
IRT models for multiple choice items (mcIRT)
Normal Mixture Modelling for Model-Based Clustering,
Classification, and Density Estimation
Posterior Distribution of Extreme Value Models in R
Bayesian analysis of multivariate counts data
Multiple Criteria Optimization Algorithms and Related Functions
Conjoint Analysis through Averaging of Multiple Analyses
Multiple comparisons using normal approximation
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
Mixture and Flexible Discriminant Analysis
Multivariate Data Analysis for Chemometrics
Measuring the Difference Between Two Empirical Distributions
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
Interactive model exploration using GGobi
Spatial pattern detection in genetic distance data using Moran's
Eigenvector Maps
Tools for Management of Survey Data, Graphics, Programming,
Statistics, and Simulation
Data sets from Mixed-effects Models in S
Tools for Analyzing Mixed Effect Regression Models
Meta-Analysis for Diagnostic Test Studies
Meta-analysis of genome-wide SNP association results
Probabilistic latent variable models for metabolomic data
Analysis of the "Elements of Metacommunity Structure"
MetaDE: Microarray meta-analysis for differentially expressed
gene detection
Metapopulation simulations for conserving salmon through
portfolio optimization
Comprehensive Research Synthesis Tools for Systematic Reviews
and Meta-Analysis
Inference in Meta Analysis and Meta Regression
A Tool for 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
MetaPCA: Meta-analysis in the Dimension Reduction of Genomic
data
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
Meth27QC: sample quality analysis, and sample control analysis
Functions for Analysis of Agreement in Method Comparison Studies
Detection of Differentially Methylated Regions using
MethylCap-Seq Data
Statistical Methods for Normalizing Metabolomics Data
Create Interactive Charts with the JavaScript 'MetricsGraphics'
Library
GUI Tool for Estimating Sample Sizes for Metabolomic Experiments
A Fixed Memeory Moving Expanding Window Average
Marginal Effects, Odds Ratios and Incidence Rate Ratios for GLMs
Mixed GAM Computation Vehicle with GCV/AIC/REML Smoothness
Estimation
Model Averaging for Multivariate GLM with Null 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
Inference for Hidden Markov and Semi-Markov Models
Multiple Hypothesis Testing for Variable Selection in
High-Dimensional Linear Models
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
Utilities for Official Spanish Microdata
Implementing dispersal into species distribution models
Methods for the Indirect Estimation of Bilateral Migration
Graphical User Interface to the 'mi' Package
Data Augmentation and Multiple Imputation for Interval Censored
Data
Two Stage Least Squares with Model Implied Instrumental Variable
Search
MIcrosimulation Lung Cancer (MILC) model
Mixture summary method for multiple imputation
Data sets included in Utts and Heckard's Mind on Statistics
minerva: 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
Multidimensional Iterative Proportional Fitting and Alternative
Models
Mutant Identification through Probabilistic High throughput
Enabled NOrmalization
Computerized Adaptive Testing with Multidimensional Item
Response Theory
'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
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
Tools for Discrete Multivariate Mixed Membership 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
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
Predictive Toxicity Assessment of Chemical Mixtures
Mixture Models for Clustering and Classification
Multi-species sIZE spectrum modelling in R
2D and 3D movement-based kernel density estimates (MKDEs)
Routines for Fitting Kinetic Models with One or More State
Variables to Chemical Degradation Data
Efficient multi-level k-circulant supersaturated designs
Latent Class Item Response Theory Models Under 'Within-Item
Multi-Dimensionality'
Machine Learning-based Differential Network Analysis of
Transcriptome Data
Exploratory Data Analysis and Manipulation of Multi-Label Data
Sets
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
A package for Multilinear Regression Model Population Analysis
Use the MLS Junk Generator Algorithm to Generate a Stream of
Pseudo-Random Numbers
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
MMELN : 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
Model-Based Clustering and Classification with Mixtures of
Modified t Factor Analyzers
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
Multiscale Analysis for Density Functions
Model-free estimation of a psychometric function
Creates Random Forest and Stochastic Gradient Boosting Models,
and applies them to GIS .img files to build detailed prediction
maps
A Model Object Framework for Regression Analysis
Tools and Classes for Statistical Models
R tools for processing Level 2 Cloud Mask products from MODIS
Community Structure Detection via Modularity Maximization
Modelling temperature effects using time series data
Moment-Matching Methods for Weighted Sums of Chi-Squared Random
Variables
Moments, cumulants, skewness, kurtosis and related tests
Monotone Multi-Layer Perceptron Neural Network
Geometric Morphometric Analysis of Monogenean Anchors
Estimation for multivariate normal and Student-t data with
monotone missingness
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
Project MOSAIC (mosaic-web.org) data sets
Mountain Plots, Folded Empirical Cumulative Distribution Plots
Mouse-Tracking Measures from Trajectory Data
Visualizing and Analyzing Animal Track Data
Mixtures of von Mises-Fisher Distributions
Multi-Patient Analysis of Genomic Markers
Data sets and scripts for Modeling Psychophysical Data in R
The package can implement the network-based metabolite pathway
identification of pathways
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
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)
Management, Display, and Processing of Medical Imaging Data
An R package for conditional maximum likelihood estimation in
mixed Rasch models
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
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
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
Multi-state Markov and Hidden Markov Models in Continuous Time
Functions and Datasets for "Methods of Statistical Model
Estimation"
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
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
Hazard Function Estimation in Survival Analysis
Exploring Data with Tree Data Structures
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
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
A Package to Test for Pleiotropic Effects
Variable Importance Analysis with Population Intervention Models
Weighted Cox-Regression for Nested Case-Control Data
Analysis of Multiple Social Networks with Algebra
Calculate Multivariate Richness via UTC and sUTC
Bias, Precision, and Power for Multi-Level Random Regressions
MultiSV: an R package for identification of structural
variations in multiple populations based on whole genome
resequencing
Simultaneous manipulation of multiple arrays of data, with
data.list objects
Common Multiple Testing Procedures and Gatekeeping Procedures
Metabolomics Univariate and Multivariate Analysis
Interpolate Munsell Renotation Data from Hue/Chroma to CIE/sRGB
Conversion of Nuclear Magnetic Resonance spectrum in audio file
A Graphical User Interface for the MuToss Project
An Introduction to Applied Multivariate Analysis with R
Statistical Methods for Analysing Multivariate Abundance Data
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 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
Multivariate outlier detection based on robust methods
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
Causal Inference in Spatiotemporal Event Data
Multichannel Wavelet Deconvolution with Additive Long Memory
Noise
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
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
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
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
Network Generator for Combinatorial Graph Problems
Estimating network indices, including trophic structure of
foodwebs in R
Network Meta-Analysis using Frequentist Methods
NetWeAvers: Weighted Averages for Networks
Tools for using network reporting estimators
Simulate Bipartite Graphs with Fixed Marginals Through
Sequential Importance Sampling
Visualization and Analysis Tools for Neural Networks
Read, Write, and Process Brain Imaging 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
Nonlinear least squares examples from NIST
Fundamental Physical Constants and Unit Conversions from NIST
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
Higher Order Inference for Nonlinear Heteroscedastic Models
Fitting Structural Equation Mixture Models
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 for regression parameters
Algorithms and Framework for Nonnegative Matrix Factorization
(NMF)
Numerical Methods and Optimization in Finance
Feed-Forward Neural Networks and Multinomial Log-Linear Models
Non-Negative Lasso and Elastic Net Penalized Generalized Linear
Models
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
Biplot representations of categorical data
U.S. Census Regional and Demographic Data
Nonparametric Methods for Measuring Efficiency and Productivity
Model Checking and Variable Selection in Nonparametric
Regression
Stratification and matching by the propensity score
Detecting, Combining and Filtering Isotope, Adduct and Homologue
Series Relations in High-Resolution Mass Spectrometry (HRMS)
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
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
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
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
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
Convenience Functions and Tests for Working With the Net
Promoter Score (NPS)
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
Numeric Routines for Optically Stimulated Luminescence Dating
Audioscrobbler data for "R in a Nutshell"
R functions for NetWorkSpaces and Sleigh
Data about flights departing NYC in 2013
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
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
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
Efficient Authenticated Interaction with the O*NET API
Opasnet Modelling Environment Utility Functions
Option Pricing and Estimation of Financial Models in R
Tools for the Analysis of Air Pollution Data
A System for 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
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
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
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
Miscellaneous functions for (primarily) finance / credit risk
analysts
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
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
Converting Odds Ratio to Relative Risk in Cohort Studies with
Partial Data Information
Collection of functions for orthogonal and orthonormal
polynomials
Design and analysis of observational studies
Optimal Trees Ensembles for Regression, Classification and Class
Membership Probability Estimation
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
Plot the Australian Coastline and States
Posterior Predictive Checks of Coalescent Models
Performance Attribution for Equity Portfolios
PAC-Bayesian Estimation and Prediction in Sparse Additive
Models
A few useful functions for statisticians
A Dependency Management System for Projects and their R Package
Dependencies
Procrustes Application to Cophylogenetic Analysis
Attributable Fraction Function for Censored Survival Data
Nonparametric Estimation of Preferential Attachment and Node
Fitness in Temporal Complex Networks
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
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
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 Sample Selection Models for Panel Counting
Data
A Toolbox for Writing 'knitr', 'Sweave' or Other 'LaTeX'-Based
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
A Parallel-Voting Version of the Support-Vector-Machine
Algorithm
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
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
Classification using biological pathways as prior knowledge
Basic functions for drawing path diagrams
Pathmox Approach of Segmentation Trees in Partial Least Squares
Path Modeling
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 of pbd 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
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
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
Methods for Graphical Models and Causal Inference
Semiparametric regression analysis of panel count data using
monotone splines
Preconditioned Conjugate Gradient Algorithm for solving Ax=b
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
Proximal/distal modeling framework for Pavlovian conditioning
phenomena
PDQ Functions via Gram Charlier, Edgeworth, and Cornish Fisher
Approximations
Panel Data Regression: Threshold Model and Unit Root Tests
Positive definite sparse covariance estimators
Periodogram Peaks in Correlated Time Series
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
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
Package for Periodic Time Series Analysis
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
permPGU: Using GPUs in Statistical Genomics
Functions for Generating Restricted Permutations of Data
Resampling-based prediction error estimation for regression
models
Permutation of Species During Turnover Events
Analysis of single serving and composite pesticide residue
measurements
Simulation and Reconstruction of PET Images
Phylogenetics for the Environmental Sciences
Generalized Least Square in comparative Phylogenetics
Recursive method for construction of nested resolvable designs
and uniform designs associated
Discover Probable Duplicates in Plant Genetic Resources
Collections
Large-Scale Analysis of 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
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
R interface to Geochemical Modeling Software
Panel Data Analysis with Heterogeneous Time Trends
PhViD: an R package for PharmacoVigilance signal Detection
Marks periods of sleep in Actigraph accelerometer 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 Function-Valued and Other
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
Phylogenetic Tree Topological Properties Evaluator
Implements the Phylogenetic Regression of Grafen (1989)
Process Physical Activity Accelerometer Data
Calculate Physiological Characteristics of Adults and Children
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
Dual-Agent Dose Escalation for Phase I Trials using the PIPE
Design
Tools for Harnessing MLBAM Gameday Data and Visualizing PITCHf/x
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
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
Modelling and Analysis of Leaf Gas Exchange Data
Partially Linear Additive Quantile Regression
Dynamic Updating Methods For Player Ratings Estimation
Probabilistic Feature Analysis of Two-Way Two-Mode Frequencies
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
Plot scatter points for two groups of values
Plotting multi-dimensional data - using rgl
Plot Spatial or Spatio-Temporal Data Over Google Maps
Visualization of Spatial and Spatio-Temporal Objects in Google
Earth
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 latent variable interactions in SEMM
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)
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
Tools for Splitting, Applying and Combining Data
Calculate Pairwise Multiple Comparisons of Mean Rank Sums
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
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
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
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
Polytomous logistic regression for fixed and mixed effects
Bootstrapped Basis Regression with Oracle Model Selection
Statistical Inference for Partially Observed Markov Processes
Construction and analysis of matrix population models
Provides Tools For Demographic Modelling Using Projection
Matrices
Population (and Individual) Optimal Experimental Design
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
Routines 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
Framework for simulating equity portfolio strategies
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
Precipitation Intensity, Concentration and Anomaly Analysis
Prediction Intervals for Three Basic Statistical Models
Calculate Predicted Means for Linear Models
Classification rule based on Bayesian mixture models with
feature selection bias corrected
Utilities to fit paired comparison models for preferences
Dirichlet Process Bayesian Clustering, Profile Regression
R Interface for PreSens Fiber Optic Data
Probability-Scale Residuals and Residual Correlations
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
Functions and data for A Primer of Ecology with R
Fits a Principal Curve in Arbitrary Dimension
Finding and plotting simple basis vectors for multivariate data
Protocol Inspection and State Machine Analysis
Differentially Private Regularized Logistic Regression
Estimation of Prevalence Ratios using Logistic Models
Elementary Probability on Finite Sample Spaces
Statistical Tools for Probing Moderation Effects
Probabilistic weather forecast using the GOP method
probsvm: Class probability estimation for Support Vector
Machines
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
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
Various confidence interval methods for proportions
Analyzing Combination of Proportions and Relative Risk
Feature (gene) selection based on the Proportional Overlapping
Scores
Propensity score methods for assigning treatment in randomized
trials
Miscellaneous functions for processing and sample selection of
vis-NIR diffuse reflectance data
Optimization of a multi-stage proteomic study
Statistical Analysis of High Throughput Proteomics Data
Protein (identification and) quantification based on peptide
evidence
Generating Various Numerical Representation Schemes of Protein
Sequence
Visualizing and Analyzing Mass Spectrometry Related Data in
Proteomics
Statistical Toolbox for Sedimentary Provenance Analysis
Precision-Recall and ROC Curves for Weighted and Unweighted Data
Test of periodicity using response surface regression
Bootstrapping for Propensity Score Analysis
Penalized Semiparametric Bayesian Cox 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
A package to download regularly maintained political science
data sets and make commonly used, but infrequently updated
variables based on this data
Parameter Space Exploration with Latin Hypercubes
Projected Spatial Gaussian Process (psgp) methods
Build Panel Data Sets from PSID Raw Data
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
Computational models for prospect theory and other theories of
risky decision making
Performs simulation study to look for publication bias, using a
technique described by Ioannidis and Trikalinos; Clin Trials.
2007;4(3):245-53
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
Computes phylogenetic eigenvectors regression (PVR) and
phylogenetic signal-representation curve (PSR) (with null and
Brownian expectations)
An R package to interact with the Project Vote Smart API for
scientific research
Penn World Table (Versions 5.6, 6.x, 7.x)
Yet another package for Qualitative Comparative Analysis
Tests for Type I Error in Qualitative Comparative Analysis (QCA)
Quality Control of Genome Wide Association Study results
Robust Estimation of Gaussian Mixture Models
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
Pricing of Vanilla and Exotic Option Contracts
Graph Plotting Methods, Psychometric Data Visualization and
Graphical Model Estimation
Tools for Quantitative Genetics Data Analyses
Utility Sparse Matrix Functions for Quantitative Language
Comparison
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
Self Calibrating Quantile-Quantile Plots for Visual Testing
Tools that Create D3 JavaScript Force Directed Graph from R
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
Quantile Regression for Nonlinear Mixed-Effects Models
Quantitative Structure Activity Relationship (QSAR) Data Sets
Tools for mapping multiple complex traits
Tools for mapping of quantitative traits of genetically related
individuals and calculating identity coefficients from a
pedigree
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
Regularized sparse inverse covariance matrix estimation
Fits Psychometric Functions for Multiple Groups
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
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
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
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
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
A platform for the study of macroecology of life history traits
Model-based clustering for multivariate partial ranking data
Ranking Responses in a Single Response Question or a Multiple
Response Question
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
Interfaces to Linux and AppArmor security methods
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
R wrapper of ARPACK for large scale eigenvalue/vector problems,
on both dense and sparse matrices
Range Ancestral State Estimation for Phylogeography and
Comparative Analyses
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
An R Package for Reading and Writing BAM (Binary Alignment)
Files
The Beta Random Number and Dirichlet Random Vector Generating
Functions
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
Loglinear Models for Capture-Recapture Experiments
This package builds maps with a full cartographic layout
Large, Sparse Optimal Matching with Refined Covariate Balance
RCEIM - R Cross Entropy Inspired Method for Optimization
Microscopy Based Cytometry Data Analysis Package
Conjugate Gradient Minimization of Nonlinear Functions
Discrete Choice (Binary, Poisson and Ordered) Models with Random
Parameters
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
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
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' Integration for 'GNU GSL' Vectors and Matrices
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
Toolbox for Regression Discontinuity Design ('RDD')
Robust Data Envelopment Analysis (DEA) for R
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
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
Suite of Functions to Flexibly Read Data from Files
Read, Write, Manipulate and Convert GenAlEx-Format Genotype
Files
Reading Machine Learning Benchmark Data Sets in Different
Formats
Reads Mass Spectrometry Data in mzXML Format
Read ODS files and puts them into data frames
Empirical Bayes Estimation and Inference in R
R Client for the eBird Database of Bird Observations
Rough - Enhanced - Bayesian Finite Mixture Modeling
Build Regular Expressions in a Human Readable Way
Relevant Component Analysis for Supervised Distance Metric
Learning
Access U.S. Federal Government Recall Data
Redundancy Control in Pathways databases
Ordination Methods for the Analysis of Beta-Diversity Indices
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”
Markov Chain Monte Carlo Methods for Redistricting Simulation
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
Wavelet-Domain Regression with Functional Data
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
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
Extensible Markov Model for Modelling Temporal Relationships
Between Clusters
Regularized Multivariate Regression for Identifying Master
Predictors
Empirical Orthogonal Teleconnections in R
Renewal Method for Extreme Values Extrapolation
Reordering the dendrogram according to the class labels
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
Renewable Energy Probability Resource Assessment Tool (REPRA)
Determine the representativity of two multidimensional data sets
Reproduce Statistical Analyses and Meta-Analyses
General Purpose Client for 'ERDDAP' Servers
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
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 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
Multivariate Analysis of Metabolomics Data using Random Forests
Graphics for Spherical Distributions and Earthquake Focal
Mechanisms
RForcecom provides the connection to Force.com and
Salesforce.com from R
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)
Build, Import and Export GEXF Graph Files
R Interface to Global Biotic Interactions
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
Ridge Regression with automatic selection of the penalty
parameter
R Package for Ridge Fusion in Statistical Learning
Ridit Analysis (An extension of the Kruskal-Wallis Test.)
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
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
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
Mann-Kendall Test, Seasonal and Regional Kendall Tests
Data Exchange Between R and LabKey Server
Package for the Analysis of Lake Physics
R interface to RNG with multiple streams
Ensemble Empirical Mode Decomposition (EEMD) and Its Complete
Variant (CEEMDAN)
A Toolbox for Non-Tabular Data Manipulation
Rank-based Estimation and Prediction in Random Effects Nested
Models
Exact (Restricted) Likelihood Ratio tests for mixed and additive
models
'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
Read and Write MAT Files and Call MATLAB from Within R
An R Package for Mediation Analysis Confidence Intervals
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 Dirichlet process 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
Root-mean-square goodness-of-fit test for simple null hypothesis
Distributions, Statistics and Tests derived from Random Matrix
Theory
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
EUtils libraries for use in the R environment
Obtain, Organize, and Visualize NCEP Weather Data
Provides an Interface to the Agent-Based Modelling Platform
NetLogo
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
Medical Image Registration Using the NiftyReg Library
An Interface to the NOAA Operational Model Archive and
Distribution System
UK National River Flow Archive Data from R
Robust Estimation for Compositional Data
Optimally robust influence curves and estimators for location
and scale
Infinitesimally robust estimators for preprocessing omics data
Robust Periodogram and Periodicity Detection Methods
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 logWeibull case
Robust Mixture Modeling Fitted via Spatial-EM Algorithm for
Model-Based Clustering and Outlier Detection
An Object Oriented Solution for Robust Factor Analysis
Robust Estimation for Generalized Additive Models
Robust methods for high-dimensional data
Robust estimation of the generalized log gamma model
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 estimation and adaptation to the
relative survival context
Non-parametric estimation of ROC curves without Gold Standard
Test
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
Optimally robust estimation - old version
Optimally robust estimation for regression-type models
OCI Based Oracle Database Interface for R
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
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
R interface to the iPlant Discovery Environment
Interface to the Search 'API' for 'PLoS' Journals
Graphical User Interface (GUI) for Interactive R Analysis
Sessions
R interface to the PostgreSQL database system
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
Functions for Working with 'Eprime' Text Files
rpubchem - Interface to the PubChem Collection
R Interface to the Pushbullet Messaging Service
Statistical Methods for the Randomized Response Technique
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
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
Tools, Classes, and Methods for Interfacing with SaTScan
Stand-Alone Software
An R Package for Stepwise Cluster Analysis
Bi-Directional Interface Between R and Scala with Callbacks
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
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
Download 'Socrata' Data Sets as R Data Frames
Port of sofia-ml (http://code.google.com/p/sofia-ml/) to R
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
A Collection of Methods for Singular Spectrum Analysis
Persistent Fast Amortized Stack and Queue Data Structures
Access to the Digital Universe Data set API
Random orthonormal matrix generation on the Stiefel manifold
Simulate and Develop Streaming Processing in [R]
Suite of Nonlinear Differential Algebraic Equations Solvers in R
Interface to 'Sunlight' Foundation 'APIs'
Design and Analysis of Disease Surveillance Activities
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
Interpolation of Data with Variable Spatial Support
Triangle - A 2D Quality Mesh Generator and Delaunay Triangulator
T-Distributed Stochastic Neighbor Embedding using Barnes-Hut
Implementation
Implementation of Unobserved Components Model (UCM) in R
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
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
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 wrapper around the Yahoo! Weather, Google Weather and NOAA
APIs
R x C Ecological Inference With Optional Incorporation of Survey
Information
Functions to Compute Chemical Reaction Similarity
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
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
Functions for University of Auckland Course STATS 201/208 Data
Analysis
Set of Common Tools for Model Diagnostics
Biclustering via sparse singular value decomposition
incorporating stability selection
Sabermetrics Functions For Baseball Analytics
Detection of Fixations in Eye-Tracking Data
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
Sensitivity Analysis for Functional Input
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
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
A Package to Score Behavioral Questionnaires
Score Persons Using the Generalized Graded Unfolding Model
SCORER 2.0: an algorithm for distinguishing parallel dimeric and
trimeric coiled-coil sequences
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
Species Distribution Modelling Tools: Tools for processing data
associated with species distribution modelling exercises
Create virtual species for species distribution modelling
Soft Discretization-based Bayesian Network Inference
Scale-Dependent Hyperpriors in Structured Additive
Distributional Regression
Measures of Risk for the Compound Poisson Risk Process with
Diffusion
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
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
Predict Information Cascade by Self-Exciting Point Process
Fast Rolling Functions for Seismology using Rcpp
KoNLP static dictionaries and Sejong project resources
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
Parametric and semi-parametric analysis of semi-competing risks
data
Identifiability of linear structural equation models
Semiparametric 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 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 (PEM) algorithm
Thurstonian Models for Sensory Discrimination
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
Biological Sequences Retrieval and Analysis
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
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
SetMethods: A Package Companion to "Set-Theoretic Methods for
the Social Sciences"
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
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
An R Package for the Calculation and Visualization of 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
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 for Bayesian Models
SHrinkage covariance Incorporating Prior knowledge
Convert a SpatialLinesDataFrame object to a "igraph-class"
object
Global, Parameterwise and Joint Post-Estimation Shrinkage
The shuffle estimator for explainable variance
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
Simulation of Ecological (and Other) Dynamic Systems
SIMEX- and MCSIMEX-Algorithm for measurement error models
Subnetwork Integration for Multi-Modal Signatures
Simulation of Event Histories for Multi-State Models
Statistical Inference for MOdular NEtworks (SIMoNe)
Tools for Simulating and Plotting Quantities of Interest
Estimated from Cox Proportional Hazards Models
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
Numerical integration of functions over simplices
Simulation of Synthetic Populations for Survey Data Considering
Auxiliary Information
Simulations to predict the number of loci expected in RAD and
GBS approaches
Linear Model Data Simulation and Design of Computer Experiments
Tools for Simulation Studies in Parallel with R
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
Estimate sparse dynamic graphs using the Smooth Incremental
Graphical Lasso Estimation (SINGLE) algorithm
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
Format a number to a string with SI prefix
Sensitivity Indices with Dependent Inputs
Six Sigma Tools for Quality and Process Improvement
Data Transformation and Labelled Data Utility Functions
Data Visualization for Statistics in Social Science
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.com
channels/users
Estimation and Use of the Quantile-Based Skew Logistic
Distribution
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
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
Generates social networks based on distance
Social Position Indicators Construction Toolbox
Functions and Examples for "Software for Data Analysis"
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
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
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
An R client for the OGC Sensor Observation Service
Stochastic Ordering Using Permutations (and Pairwise
Comparisons)
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
The sparr package: SPAtial Relative Risk
Sparse Biclustering of Transposable Data
Sparse and Regularized Discriminant Analysis
Scaling Count and Binary Data with Sparse Factor Analysis
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 Time Series Chain Graphical Models
Simulation Parameter Analysis R Toolkit ApplicatioN: Spartan
Spatio-Temporal Modeling of Large Data Using a Spectral SPDE
Approach
Functions for Kriging and Point Pattern Analysis
Computation of Spatial Covariance Matrices for Data on
Rectangles
Methods and Data for Spatial Epidemiology
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 Principal Component Analysis for Spatial Data
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
Spatial Coverage Sampling and Random Sampling from Compact
Geographical Strata
Sparse Estimation of a Covariance Matrix
Spatial Dependence: Weighting Schemes, Statistics and Models
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
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
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
Spatial Stochastic Frontier models estimation
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
Prediction and variable selection using spike and slab
regression
Bayesian Variable Selection and Model Choice for Generalized
Additive Mixed Models
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
Semiparametric Maximum Likelihood for Mother-Child Designs
Interface to Species Occurrence Data Sources
Semiparametric proportional odds rate model
Statistical Package for Reliability Data Analysis
Calculate Species Richness and Extrapolation Metrics
Framework for Screening Prognostic Interactions
Sparse and Non-Sparse Partial Robust M Regression
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"
Squared extrapolation methods for accelerating fixed-point
iterations
Color-Based Plots for Multivariate Visualization
Statistical Ranking Color Scheme for Multiple Pairwise
Comparisons
Nonparametric Smooth ROC Curves for Continuous Data
The Stepwise Response Refinement Screener (SRRS)
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
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
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 4 parameters of stable law using different methods
Stylized concatenation of data.frames or ffdfs
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
Tools Inspired by Stata to Manipulate Tabular Data
Extract Statistics from Articles and Recompute P Values
Statistical Analysis for Environmental Data
statebins is 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
Tools for Inference with Set-Theoretic Comparative Methods
Testing Steepness of Dominance Hierarchies
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
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
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
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 Haplotypic and
Genotypic Data
Univariate Stratification of Survey Populations
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
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
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
Identify Metabolic Subpathways Mediated by MicroRNAs
Unconstrained Optimization using the Subplex Algorithm
Computes copula using ranks and subsampling
Sub-Score Computing Functions in Classical Test Theory
An Ensemble Method for Combining Subset-Specific Algorithm Fits
Cluster analysis to find molecular subtypes and their assessment
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
Implements the supervised multidimensional scaling (superMDS)
proposal of Witten and Tibshirani (2011)
Basic Functions for Supporting an Implementation of Best-Worst
Scaling
Basic Functions for Supporting an Implementation of Choice
Experiments
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
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
Simulation of Simple and Complex Survival Data
Power Calculations for SNP Studies with Censored Outcomes
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
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)
cycle-Free Flux balance analysis: Efficient removal of
thermodynamically infeasible cycles from metabolic flux
distributions
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
SYNCSA - Analysis of functional and phylogenetic patterns in
metacommunities
Interface to The Synergizer service for translating between sets
of biological identifiers
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
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
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
Estimate the Probability in the Upper Tail of the Aggregate Loss
Distribution
Time Course Analysis of Variance for Microarray
Flexible Tree Taper Curves Based on Semiparametric Mixed Models
Collection of utility and convenience functions
Earthquake Traveltime Calculations for 1-D Earth Models
Provides various portfolio optimization strategies including
random matrix theory and shrinkage estimators
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
Advanced Data Analysis of T Cell 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
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
Methods for Temporal Disaggregation and Interpolation of Time
Series
Advanced tensors arithmetic with named indices
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
Tests and checks characteristics of R objects
GUI for Entering Test Items and Obtaining Raw and Transformed
Scores
Statistical tests to compare two survival curves with recurrent
events
A mocking, stubbing, and file testing framework extending
testthat
Treatment Effect eXplorer for Microbial Ecology eXperiments
(using Sequence Counts)
Conversion of R Regression Output to LaTeX or HTML Tables
Textual Data Analysis Package used by the TXM Software
n-gram Text Regression, aka Concise Comparative Summarization
Technology Forecasting using DEA (Data Envelopment Analysis)
Efficient and accurate P-value computation for Position Weight
Matrices
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
Represent Precise Coordinates in Three Words
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
A Grammar for Turning 'JSON' into Tidy Tables
Easily Tidy Data with spread() and gather() Functions
Hidden Markov Models for ChIP-on-Chip Analysis
Characterization of functional genes in complex microbial
communities using tiling DNA microarrays
Rmetrics - Chronological and Calendar Objects
Time Delay Estimation for Stochastic Time Series of
Gravitationally Lensed Quasars
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
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
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
Automated measure-based classification for flint tools
Titration analysis for mass spectrometry data
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
Targeted Learning of a NP Importance of a Continuous Exposure
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
tnet: Software for Analysis of Weighted, Two-mode, and
Longitudinal networks
Total Operating Characteristic Curve and ROC Curve
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
Experimental design for binary toxicity tests
Estimation of Transition Probabilities in Multistate Models
A Tool for Downloading Functional Traits Data for Plant Species
Reconstruct animal tracks from magnetometer, accelerometer,
depth and optional speed data
A package for reading, manipulating and visualising magnetic
resonance images
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
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
Estimating birth and death rates based on phylogenies
Exact and Asymptotic K Sample Permutation Test
Simulating trees under the birth-death model
Simulating Phylogenetic Trees under a General Model
Methods for Tree-based Local Adaptive Thresholding
Non-Parametric Trend Tests and Change-Point Detection
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
Likelihood-ratio Tests for Two-Sample Comparisons
Nonlinear Time Series Models with Regime Switching
Two-dimensional peak sentinel tool for GC x GC-HRTOFMS
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
T-distributed Stochastic Neighbor Embedding for R (t-SNE)
Transposable Sphering for Large-Scale Inference with Correlated
Data
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
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
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
Lumped Hydrological Model for Education Purposes
Toolkit for Weighting and Analysis of Nonequivalent Groups
Interactive manipulation of R expressions
Nonparametric test of equality between two copulas
Compute thresholds and power for two-stage gwas
Conditional logistic regression: A two-step estimation method
Functions to Simulate and Conduct Dose-Escalation Phase I
Studies
UC Berkeley graduate division thesis template
Helper Functions for Structural Equation Modelling in OpenMx
Function estimation via Unbalanced Haar wavelets
Tools for Creating Universal Numeric Fingerprints for Data
Stereological Unfolding for Spheroidal Particles
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
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
Vectorised Tools for URL Handling and Parsing
Historical Boundaries of the United States of America, 1629-2000
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
Data Sets, Etc. for the Text "Using R for Introductory
Statistics", Second Edition
Model-based clustering via mixtures of unrestricted skew-t
factor 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
Variational inference for Bayesian variable selection
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
Testing of genotypic variance heterogeneity to detect
potentially interacting SNP
Variable Selection for Model-Based Clustering using the
Integrated Complete-Data Likelihood of a Latent Class Model
Pricing a variance swap on an equity index
Transform Definition of Variables to R Scripts
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
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
Vector Generalized Linear and Additive Models
Discrimination/Classification in very high dimension with linear
and quadratic rules
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
Generation of Virtual Species Distributions
Network Visualization using 'vis.js' Library
Graph Probability Distributions with User Supplied Parameters
and Stats
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
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
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
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
Weaning Age Reconstruction with Nitrogen isotope analysis
Visualisation and analysis of output files of the hydrological
model WASIM
An R Package for Retrieval, Analysis, and Anomaly Calculation of
Daily Hydrologic Time Series Data
Fetch and Analyze Data from WaterML or CUAHSI WaterOneFlow Web
Service
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
Basic wavelet routines for one-, two- and three-dimensional
signal processing
Wild Binary Segmentation for Multiple Change-Point Detection
Multiple Change-Point Detection for Nonstationary Time Series
Detection of QTL effects in a small mapping population
World Development Indicators (World Bank)
Tools for Handling and Scrapping Instant Weather Forecast Feeds
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
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
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
Fitting many skinny linear models to a single data set
Penalized Regression with Polynomial Basis Expansions
Functions and datasets of the german WikiBook "GNU R"
Public Subject Attention via Wikipedia Page Access Statistics
Wilcoxon-based variable selection in cross-validation
Calculate Indices of Dynamic Interaction for Wildlife Telemetry
Data
windex: Analysing convergent evolution using the Wheatsheaf
index
This package fits eyewitness data using Clark's (2003) WITNESS
model
Convert Between Spatial Objects and Well-Known Binary (WKB)
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
Matches words in one file with words in another file
Classical word pools used in studies of learning and memory
Wright Map: 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
Functions for working with Worldwide Reference System (WRS)
Weighted Subspace Random Forest for Classification
Weighted SVM with boosting algorithm for improving accuracy
Competing risks regression models with covariate-adjusted
censoring weight
R Wrapper for the 'Wufoo.com' - The Form Building Service
Wegener Center Climate Uncertainty Explorer
x12 - wrapper function and structure for batch processing
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
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
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
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
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
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
Dynamic Plots for Time Series Forecasting
Zebra-Striped Tables in LaTeX and HTML Formats
'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
https://r-forge.r-project.org/projects/rnomads/ (subversion
repository)
http://www.unc.edu/~haksaeng/rNOMADS/rNOMADS_dods_examples.pdf
(GrADS-DODS examples)
http://www.unc.edu/~haksaeng/rNOMADS/rNOMADS_grib_examples.pdf
(grib examples)
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 2012-07-18 as the original maintainer, Romain Francois <romain@r-enthusiasts.com>, is unresponsive.
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 2015-05-29 as non-cross-platform calls to iconv() were not corrected by the original maintainer (and have been by the CRAN team).
Orphaned on 2014-12-07 as maintainer address <erika.cule05@imperial.ac.uk> bounced.
Orphaned on 2015-06-20 as incomplete maintainer address was not corrected despite reminders.
Orphaned on 2014-08-15 as requested by the original maintainer.
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, GhcnDaily, hyperdirichlet, informR, interplot, LSDinterface, magic, MetStaT, mlogitBMA, multicon, MultiPhen, multipol, mvmesh, mvProbit, plfm, QCAGUI, RcmdrPlugin.EACSPIR, RcmdrPlugin.EBM, RcmdrPlugin.epack, simSummary, spBayes, synbreed, wux, zoib
ade4TkGUI, adegenet, adehabitat, adehabitatHR, adehabitatHS, adehabitatLT, adephylo, cati, DDD, ecospat, ENiRG, FactoClass, FD, genoPlotR, hierfstat, oncomodel, pamctdp, PBD, rmetasim, seqinr, sideChannelAttack
adhoc, apex, apTreeshape, BAMMtools, bayou, BioGeoBEARS, caper, cati, Claddis, coalescentMCMC, convevol, corHMM, DAMOCLES, DDD, DiscML, distory, diversitree, ecospat, evobiR, expoTree, FD, geiger, graphscan, GUniFrac, HAP.ROR, hisse, HMPTrees, HyPhy, ips, iteRates, laser, MCMCglmm, MPSEM, mvMORPH, mvSLOUCH, OUwie, paleotree, pastis, PBD, pegas, perspectev, pez, phangorn, phyclust, phyloclim, phylolm, phylotools, phyloTop, phytools, picante, PVR, RADami, RAM, rase, recluster, rmetasim, RNeXML, RPANDA, Rphylip, Rphylopars, Rsampletrees, SeqFeatR, spider, strap, surface, TESS, treebase, TreePar, TreeSim, windex
arulesNBMiner, arulesSequences, arulesViz, ibmdbR, recommenderlab
BaM, bayesMCClust, compositions, ocomposition, siar
BinNonNor, GNE, LIHNPSD, mederrRank, NPCD, PoisBinNonNor, PoisBinOrdNonNor, PoisNonNor, RobPer
bigalgebra, biganalytics, bigpca, bigrf, bigtabulate
bnstruct, cdb, CHCN, cherry, couchDB, GENEAread, geozoo, muma, R4CouchDB, RCurl
aods3, attribrisk, BACprior, bootES, boottol, cardidates, catenary, CircStats, classyfire, Comp2ROC, Compind, CovSel, cramer, dawai, DCluster, dhglm, DLMtool, equivalence, eventstudies, experiment, fishmethods, fishmove, frailtypack, gb, HPbayes, IUPS, joineR, laeken, LCAextend, MDSGUI, mem, mixtools, nFactors, Oncotree, ordinalCont, pastecs, plsgenomics, popKorn, prLogistic, PsumtSim, QuantPsyc, quickpsy, R2WinBUGS, randomLCA, random.polychor.pa, reglogit, relaimpo, rich, sampSurf, simboot, simpleboot, SiZer, survrec, TestSurvRec, timesboot, titan, tlm, truncSP, verification, Zelig
AtelieR, fit4NM, gWidgetsRGtk2, meta4diag, MetSizeR, PKgraph, playwith, rsgcc, RunuranGUI, sdcMicroGUI, WMCapacity
AER, alr3, alr4, ARTool, bartMachine, bgmm, candisc, CrypticIBDcheck, DAMisc, Deducer, DiagTest3Grp, DistatisR, epr, extRemes, genridge, granova, heplots, hysteresis, ibd, lmSupport, mosaic, muma, mvinfluence, papeR, pequod, phia, quantification, Rcmdr, RcmdrMisc, RcmdrPlugin.SM, ryouready, seeg, specificity, stepp, systemfit
adabag, caretEnsemble, conformal, fscaret, ordBTL
cmrutils, crn, ensembleBMA, ensembleMOS, ImportExport, Interpol.T, kerdiest, MicSim, RH2, RMAWGEN, StreamMetabolism
CircOutlier, depth, isocir, localdepth, NPCirc, SOPIE, wle
clv, ddalpha, EILA, geneSignatureFinder, KODAMA, kohonen, longitudinalData, mda, Modalclust, msr, protoclass, svapls
abodOutlier, AdaptFit, AssocTests, bios2mds, ccChooser, clustergas, clusterSim, clv, clValid, COMMUNAL, CORM, dbstats, divo, dpmixsim, FunCluster, gclus, geneSignatureFinder, GLDEX, ICGE, isopam, knnGarden, maptree, MSeasy, NMF, nomclust, optpart, pamr, popgen, qrfactor, RPMM, spa, tclust, TraMineRextras, treeClust, TSclust, WeightedCluster
kml, kml3d, longitudinalData, MOCCA, wskm
adaptMCMC, adaptsmoFMRI, anominate, B2Z, BaM, BANOVA, bayesDccGarch, BayesFactor, bayesGARCH, BayesLCA, bayespref, BayesSAE, bayesSurv, Bayesthresh, bayou, BAYSTAR, Bergm, bisoreg, bmk, boral, coalescentMCMC, codadiags, cplm, dclone, eiPack, elrm, embryogrowth, endorse, FME, gemtc, HelpersMG, HSROC, HybridMC, hzar, iFad, IsotopeR, MasterBayes, mcgibbsit, MCMCglmm, 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, WMCapacity, zic, zoib
biclust, BiplotGUI, coloc, frontiles, ips, mixAK, msr, prefmod, R2BayesX, RcmdrPlugin.SM, snpStatsWriter, spacodiR, tourrGui, VIM, W2CWM2C
AssocTests, BayClone2, bayess, bgmm, fcd, FLR, forensic, GameTheory, genetics, MetaDE, NSM3, PoissonSeq, prob, QuACN, RMallow, SNPmaxsel, symmoments
gskat, iGasso, MiST, pedgene, rvTDT, skatMeta
cgam, ConSpline, DoubleCone, isotonic.pen, ShapeSelectForest
BivarP, CoClust, CoImp, HAC, HiDimMaxStable, lcopula, RGENERATEPREC, RMRAINGEN, SemiParSampleSel, vines
arf3DS4, BinNonNor, BinNor, care, clustrd, EDISON, FRB, FRCC, GeneNet, GLSME, Hotelling, HPbayes, idm, jackstraw, kcirt, leapp, longitudinal, MAVTgsa, mgpd, miRtest, MultiOrd, mvMORPH, mvSLOUCH, netgsa, OrdNor, penalizedSVM, PoisBinNonNor, PoisBinOrd, PoisBinOrdNonNor, PoisBinOrdNor, PoisNonNor, PoisNor, qtlhot, sda, sideChannelAttack, SMFI5, st, ttScreening
CovSel, spatialTailDep, SphericalCubature, stppResid, symmoments, yuima
cvAUC, edgeRun, greport, lookupTable, orgR, panelaggregation, psidR, Rbitcoin, sdcMicro, simPop, slackr, splitstackshape, ttwa, vardpoor, VIM
ilc, Interpol.T, kerdiest, modiscloud, RcmdrPlugin.survival, relsurv, RMAWGEN, ROCt
archivist, biglm, datamap, filehashSQLite, MonetDB.R, ODB, ora, RecordLinkage, RJDBC, RMySQL, ROracle, 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, bvpSolve, DAISIE, DAMOCLES, DDD, deTestSet, diffEq, DivE, diversitree, ecolMod, ecosim, embryogrowth, EpiModel, expoTree, FME, hgm, hisse, insideRODE, neuRosim, nlmeODE, pauwels2014, PBD, phaseR, primer, PSM, ReacTran, RPANDA, scaRabee, simecol, SoilR, TDCor, TESS, TreePar, tseriesChaos, ZeBook
DiceEval, DiceOptim, DiceView, fanovaGraph, GPareto, KrigInv, MuFiCokriging
blockmodels, ElstonStewart, gWidgets2, gWidgets2tcltk, gWidgetstcltk, LLSR, MonetDB.R, OpenMx, traitr
arqas, 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, GenCAT, iFes, JAGUAR, OmicKriging, perspectev, PTE, randomGLM, sdcTarget, SDDE, sms, turboEM, unbalanced, VTrack
emil, GenCAT, ggmcmc, manifestoR, mosaic, openair, PogromcyDanych, poplite, quickpsy, radiant, SEERaBomb, tcR, turfR
BayesLCA, bayesMCClust, bios2mds, BSDA, classyfire, ClueR, clustrd, conformal, eegAnalysis, flip, gskat, InventorymodelPackage, KODAMA, MAclinical, mlDNA, msr, 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, ergm.count, ergm.graphlets, ergm.userterms, hergm, latentnet, lvm4net, statnet, statnetWeb, tergm, VBLPCM, xergm.common
condmixt, crackR, ddst, evt0, mgpd, Renext, ROptEstOld, SimCorMultRes, truncdist
ClustGeo, EnQuireR, Factoshiny, missMDA, RcmdrPlugin.FactoMineR, RSDA, 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, rsgcc, Statomica
Actigraphy, CCA, CollocInfer, cyphid, fdatest, fda.usc, FDRreg, Funclustering, funFEM, funHDDC, GPFDA, mar1s, pencopula, pendensity, penDvine, RFgroove, sde, sft, switchnpreg, vows
DBGSA, DiffCorr, ERP, GeneCycle, GeneNet, sda, st, TBEST
BayesSummaryStatLM, biglars, dualScale, ETLUtils, ffbase, PopGenome, propagate, RecordLinkage, sprint
distrRmetrics, fExtremes, fNonlinear, gogarch, mleur
ASMap, BaySIC, CCA, chillR, cmsaf, crqa, eegAnalysis, EMD, Geneland, geosptdb, gptk, gwrr, highriskzone, ibeemd, LatticeKrig, LSC, mgpd, phenology, phylotools, ProbForecastGOP, R2GUESS, sGPCA, SpatialVx, SpatPCA, SpherWave, spThin, stilt, SynchWave, TIMP, TrackReconstruction, verification, Voss, wux
BANFF, clustvarsel, DNMF, doMC, doMPI, doParallel, doRedis, doRNG, doSNOW, fdasrvf, GA, gam, gamsel, GenCAT, glmnet, gpmap, hdlm, hzar, icenReg, iFes, localgauss, MAVTgsa, MetaPCA, MetaQC, missForest, multicon, parfossil, PAWL, penDvine, permGPU, perspectev, PortfolioAnalytics, QuantumClone, randomGLM, remote, sdcTarget, SDDE, selfingTree, sms, spatial.tools, SurvRank, survSNP, turboEM, unbalanced, vacem, VTrack
caschrono, demography, expsmooth, fma, forecTheta, fpp, ftsa, hts, ilc, MAPA, Mcomp, RcmdrPlugin.epack, Rssa, StMoMo, TSPred, ZRA
AnDE, BaM, epiDisplay, psidR, rsubgroup, Rz, shapefiles, UScensus2000cdp, UScensus2000tract, UScensus2010, vegdata
BayesGESM, BayesSAE, brnn, clusterSEs, Demerelate, detect, DirichletReg, games, gmnl, Hmisc, kaps, mhurdle, mlogit, MRSP, mvctm, OutlierDC, plm, plmm, quint, Rchoice, rdd, sharx, simplexreg, smbinning, spBayes, ssym, StratSel, threg, zoib
DoE.wrapper, FrF2.catlg128, pid, RcmdrPlugin.DoE, simrel
CausalGAM, ecospat, 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, ecospat, gbm2sas, mma, ModelMap, twang
cccrm, chromoR, Claddis, COMBIA, compareGroups, enaR, genetics, iCluster, ImportExport, joineR, LeLogicielR, mixexp, mpMap, NanoStringNorm, nCal, nonparaeff, PF, pSI, TRSbook, weights
diffdepprop, DTComPair, gskat, JGEE, mmm, mmm2, repolr, saws
bayou, convevol, DAMOCLES, evobiR, iteRates, laser, surface, TreeSim, windex
boostSeq, forensic, introgress, luca, MasterBayes
BinOrdNonNor, OrdNor, PoisBinOrd, PoisBinOrdNonNor, PoisBinOrdNor
alphashape3d, contoureR, curvHDR, disp2D, EDFIR, FD, Maeswrap, modQR, munsellinterpol, mvmesh, nonparaeff, RadOnc, YplantQMC
aqfig, FeedbackTS, geoRglm, lmenssp, LS2Wstat, PrevMap, StatDA
ClimClass, geospacom, move, MUCflights, osmar
alphahull, AmpliconDuo, aoristic, apsimr, arqas, bcrm, bde, benchmark, biomod2, bootnet, brms, caret, catenary, chemosensors, CINOEDV, cjoint, ClimClass, climwin, clustrd, coefplot, conformal, COPASutils, cowplot, Crossover, dae, Deducer, DepthProc, dfexplore, diffeR, dMod, dotwhisker, dslice, dtwclust, DynNom, earlywarnings, eeptools, ESGtoolkit, fbroc, fishmove, freqparcoord, gapmap, GenCAT, gettingtothebottom, ggmap, ggmcmc, ggROC, ggsn, ggswissmaps, ggtern, ggthemes, GOplot, gpmap, granovaGG, gsDesign, GSE, Hmisc, hyperSpec, idm, ifaTools, interplot, learnstats, likeLTD, likert, lmms, localgauss, lsbclust, MCMC.OTU, MCMC.qpcr, mcprofile, MergeGUI, meteogRam, MissingDataGUI, MIXFIM, mixOmics, mlr, mlxR, mosaic, MRMR, multilevelPSA, ncappc, NeatMap, nullabor, orgR, OriGen, OutbreakTools, PairedData, PASWR2, pauwels2014, PAWL, pbdPROF, PedCNV, pequod, perry, perspectev, PhaseType, pid, pipe.design, pitchRx, PKgraph, PKreport, pointRes, PopED, popgraph, PPtreeViz, precintcon, prevR, PRISMA, profileR, ProgGUIinR, PSAboot, QCAtools, quadrupen, QualInt, quickpsy, radiant, RAM, Rcell, RcmdrPlugin.KMggplot2, rfPermute, RGraphics, RIGHT, RJafroc, rms, robustHD, rorutadis, rotations, rplos, RSA, RSDA, Rz, SciencesPo, season, selfea, sglr, shinystan, simmr, slackr, SmarterPoland, SMFI5, snht, soc.ca, sparkTable, SparseFactorAnalysis, sparsereg, spcosa, spikeSlabGAM, spoccutils, sprm, statebins, SWMPr, synthpop, tcR, tdr, timeline, TriMatch, TripleR, tspmeta, useful, userfriendlyscience, varian, vdg, waffle, walkr, xkcd, YourCast, zooaRch
hglasso, lassoscore, MInt, netgsa, rrlda, rsggm, spaceExt, sparseBC, Tsphere
bigdata, BigTSP, BioMark, CAM, cosso, covTest, DivMelt, EstHer, fcd, FindIt, glmnetcr, glmvsd, Grace, hdi, hdlm, InvariantCausalPrediction, lassoscore, MESS, mht, MMMS, MMS, msr, netgsa, oblique.tree, parcor, PAS, PRIMsrc, refund.wave, relaxnet, RVtests, selectiveInference, SIMMS, SIS, SML, sparsenet, SubLasso, widenet
logmult, multgee, prefmod, StMoMo, vcdExtra
DeducerPlugInScaling, EMMAgeo, PCovR, sdmvspecies, tsfa
allanvar, ARTIVA, bayesMCClust, bayess, cellVolumeDist, DandEFA, datautils, DiagTest3Grp, FLLat, ghyp, iCluster, MetabolAnalyze, metabolomics, Meth27QC, muma, PRISMA, reGenotyper, rehh, ReorderCluster, rnaseqWrapper, ROCR, rsgcc, SubLasso, swamp, YplantQMC
climwin, dotwhisker, ESGtoolkit, GOplot, HH, ncappc, pbdPROF, PPtreeViz, primerTree, rorutadis, snht, sparkTable, statebins, strvalidator, tcR
aws, evmix, mbbefd, metacor, palinsol, pgs, QRM, rGammaGamma
ASMap, bayesMCClust, ConsRank, crossdes, dice, GameTheory, genetics, GESTr, GSM, hierfstat, hier.part, HUM, iCluster, IDPSurvival, interferenceCI, iteRates, JASPAR, likeLTD, MAMA, MasterBayes, MetabolAnalyze, modMax, muma, mvtmeta, ordBTL, orQA, PairViz, pipe.design, RCPmod, REQS, RI2by2, rmetasim, rnaseqWrapper, rpsychi, rvHPDT, sensory, Skillings.Mack, SRRS, trioGxE, WMCapacity
apt, bayesDem, dbConnect, fit4NM, gWidgetsRGtk2, gWidgetstcltk, MetSizeR, nCal, pmg, RenextGUI, reshapeGUI, rsgcc, RunuranGUI, sdcMicroGUI, tourrGui, traitr, WMCapacity
AtelieR, bayesDem, FAiR, fit4NM, iBUGS, MergeGUI, MetSizeR, MicroStrategyR, MissingDataGUI, PKgraph, playwith, pmg, reshapeGUI, RQDA, rsgcc, RunuranGUI, sdcMicroGUI, VIMGUI, WMCapacity
BOG, COMBIA, GABi, HAP.ROR, KoNLP, orderbook, rpartitions
acid, anesrake, aspace, caschrono, cg, colorscience, compareGroups, crackR, EBMAforecast, ENmisc, EstCRM, etable, FRESA.CAD, FunCluster, greport, greyzoneSurv, gset, ImportExport, its, lawstat, lordif, MEET, MicroDatosEs, nbpMatching, nonparaeff, polytomous, PredictABEL, PRIMsrc, prLogistic, pse, RcmdrPlugin.mosaic, rms, Scale, tables, UsingR, visualFields, weights
couchDB, GAR, indicoio, LightningR, Rcolombos, Rfacebook, RGoogleAnalytics, rHealthDataGov, Rlinkedin, slackr, SmarterPoland, TMDb, tumblR, whoapi, WikipediR
agop, ARTIVA, bc3net, BDgraph, c3net, camel, cccd, CePa, CINOEDV, clickstream, cooptrees, corclass, 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, lcd, linkcomm, locits, loe, micropan, mlDNA, modMax, mRMRe, netassoc, netgsa, nets, netweavers, optrees, OutrankingTools, packdep, PAGI, pathClass, phyloTop, picasso, popgraph, PROFANCY, qtlnet, RCA, ReliabilityTheory, rEMM, rgexf, RNetLogo, ror, RWBP, sand, SDDE, secrlinear, SEMID, sglasso, shp2graph, SINGLE, SOMbrero, spacejam, SubpathwayGMir, synRNASeqNet, tcR, TDA, timeordered, tnet
Bchron, BMA, cxxfunplus, imprProbEst, mkin, rstan
clustvarsel, doMC, doMPI, doParallel, doRedis, doSNOW, GA, hdlm, itertools, MetaQC, parboost, SDDE, spatial.tools
GAR, jSonarR, leafletR, rHealthDataGov, slackr, TMDb, WikipediR
CVST, kappalab, netClass, pathClass, probsvm, SVMMaj
CHsharp, DiagTest3Grp, EMMIXskew, gammSlice, GenKern, GoFKernel, ICE, IsoCI, ks, MEET, mpm, mpmi, qualV, stpp, TPmsm
ElstonStewart, Familias, fat2Lpoly, LCAextend, MasterBayes, paramlink, pedantics, pedgene
BrailleR, EasyHTMLReport, OutbreakTools, PopGenReport, sdcMicro, SOMbrero, spThin, svSweave, tufterhandout
aml, covTest, cumSeg, elasticnet, ExactPath, FeaLect, FindIt, GPC, gwrr, monomvn, multiPIM, PAGWAS, pass, relaxo, RXshrink, scalreg, sealasso, sisVIVE, sparseLDA, spikeslab
abcdeFBA, abd, Actigraphy, adaptTest, agsemisc, ASMap, assist, backtest, barcode, bayespref, BayesSAE, bc3net, bgmm, biclust, bifactorial, bigdata, BSDA, camel, cardidates, caret, cem, coalescentMCMC, COMBIA, compeir, ConvergenceConcepts, Cubist, cvTools, cwhmisc, DAAG, DATforDCEMRI, DCL, deseasonalize, Devore7, DMwR, DoseFinding, dualScale, eHOF, ELT, EMMIXskew, EngrExpt, equivalence, erboost, EstCRM, factorQR, fastclime, FAwR, FitAR, fit.models, flare, flexclust, flexmix, FTICRMS, gammSlice, gbm, gcbd, Giza, gsbDesign, hett, hgam, HH, Hmisc, hotspots, HSROC, huge, hyperSpec, ICEinfer, iCluster, IDPmisc, iGasso, insideRODE, irtProb, jagsUI, joineR, kwb.hantush, kzs, latticeExtra, lfstat, loa, Maeswrap, mapStats, MCPMod, McSpatial, MDR, memisc, mice, mirt, mirtCAT, mixexp, mixOmics, mleur, MM2S, MOJOV, MortalitySmooth, mosaic, mritc, msme, nFactors, nlmeODE, odfWeave, OLScurve, optiscale, orderbook, PairedData, paleoMAS, PASWR, PASWR2, pbo, pencopula, pendensity, penDvine, phenmod, phmm, picasso, PKgraph, PKreport, playwith, pmg, portfolio, portfolioSim, primer, PROFANCY, pscl, qtlhot, R2MLwiN, R330, randomLCA, rapport, rasterVis, RcmdrPlugin.plotByGroup, RcmdrPlugin.temis, rCUR, REPPlab, RGraphics, rmatio, Rmisc, rms, robfilter, robust, RSA, RxCEcolInf, rysgran, scaRabee, SEL, semPLS, SetMethods, sExtinct, simFrame, simPop, sme, smint, SML, soilprofile, solaR, spuRs, sse, survSNP, svdvisual, sybil, synthpop, TDboost, tdr, titan, TROM, twang, unmarked, vegan, VHDClassification, violinmplot, VizOR, vwr, wgaim, wskm, xpose4
COMBIA, DCL, ELT, HH, lfstat, pencopula, rasterVis, solaR, twang, vwr, wskm
bmem, coefficientalpha, EffectLiteR, eqs2lavaan, fSRM, gimme, influence.SEM, lavaan.survey, MIIVsem, profileR, psytabs, RAMpath, RMediation, RSA, rsem, semTools, simsem, stremo
BACprior, bestglm, BMA, FitAR, Kpart, MAR1, pampe, R330, reams, speff2trial, TSA
ATmet, DiceOptim, mtk, netgen, penalizedSVM
BCE, EMMAgeo, LIM, MLCIRTwithin, MultiLCIRT, spaceExt
afex, agRee, aods3, ArfimaMLM, arm, ARTool, Bayesthresh, BBRecapture, blme, boss, BradleyTerry2, cAIC4, carcass, CLME, difR, gamm4, GWAF, iccbeta, influence.ME, JAGUAR, lmerTest, longpower, marked, MEMSS, merTools, Metatron, mixAK, mlmRev, nonrandom, pamm, PBImisc, pbkrtest, pedigreemm, polytomous, predictmeans, prLogistic, robustlmm, TcGSA, ZeligMultilevel
AER, cjoint, dcv, erer, fpp, frontier, ivlewbel, ivpack, mfx, micEconAids, MRMR, rdd, systemfit, vars
abc, BBRecapture, curvetest, DATforDCEMRI, ELT, EMD, mcll, McSpatial, nlts, SimpleTable, TSA
cherry, clime, EDFIR, goalprog, ibd, imprProbEst, irr, kappalab, linprog, mcclust, modQR, mpcv, nonparaeff, pathClass, RcmdrPlugin.sampling, StatMatch, WhatIf
Benchmarking, boostSeq, GameTheory, qVarSel, safeBinaryRegression, sdcTable, TFDEA
difR, infutil, irtoys, kequate, lordif, PerFit
archivist, MRMR, orgR, radiant, RGoogleAnalytics, seawaveQ, TimeProjection, weatherr
DMR, geometry, MM, sdcTarget, SNSequate, SODC, spBayes
etasFLP, FeedbackTS, geo, M3, swfscMisc, ternvis, vmsbase
cope, FeedbackTS, fields, fossil, geo, GeoLight, HBSTM, letsR, M3, mapdata, mapproj, muRL, NightDay, OIdata, openair, OriGen, paleobioDB, phytools, ramps, RNCEP, s2dverification, speciesgeocodeR, ternvis, vmsbase, warbleR
cshapes, DeducerSpatial, Digiroo2, geospacom, GISTools, GWmodel, helsinki, KappaV, lakemorpho, mapStats, McSpatial, micromap, Nippon, pycno, qrfactor, rCarto, shp2graph, STMedianPolish, StreamMetabolism, ternvis, UScensus2000cdp, UScensus2000tract, UScensus2010
adaptMCMC, adaptsmoFMRI, agop, ahaz, arm, arules, BayesFactor, bayesGDS, bc3net, BCE, BDgraph, bigdata, BinNonNor, BinNor, bnstruct, boss, cAIC4, CAM, camel, cherry, CLSOCP, covLCA, CoxBoost, Coxnet, cplm, crqa, crrp, CVST, cvxbiclustr, cvxclustr, DAGGER, dcGOR, dhglm, distrom, dmm, dosresmeta, DoubleCone, dualScale, EMMREML, epoc, excursions, expm, FAiR, fanc, fastclime, fastcox, fda, fExpressCertificates, FindIt, flare, frailtyHL, FSInteract, FTICRMS, GAMBoost, gamlr, gamm4, gcdnet, gdistance, geeM, genlasso, GenOrd, GeoDE, geostatsp, gettingtothebottom, glmm, glmnet, gptk, GPvam, GrassmannOptim, growthrate, grpreg, gskat, gvcm.cat, gwerAM, hglm, hglm.data, highriskzone, HiPLARM, hts, huge, ibmdbR, inarmix, IPMpack, isotonic.pen, ivmodel, kinship2, klin, lassoscore, ldr, lfe, lme4, lmerTest, loe, logcondiscr, longpower, LPmerge, LSC, lsgl, mapfit, mclogit, MCMCglmm, MDPtoolbox, mediation, MEET, mefa4, MESS, metafor, Metatron, mht, mi, MIIVsem, minque, MMS, msda, msgl, msr, multiAssetOptions, MultiOrd, mvglmmRank, nadiv, nonlinearTseries, optimbase, ORDER2PARENT, orderedLasso, OrdNor, PBImisc, PCovR, pedgene, pedigree, pedigreemm, penDvine, phmm, picasso, PivotalR, PoisBinNonNor, PoisBinOrd, PoisBinOrdNonNor, PoisBinOrdNor, PoisNonNor, PoisNor, PRISMA, PROFANCY, qgtools, qlcMatrix, qpcR, QRM, quadrupen, R2STATS, ramps, rCUR, RealVAMS, REBayes, recommenderlab, reglogit, RFGLS, RGENERATEPREC, rmatio, Rmosek, RMRAINGEN, robustlmm, rsggm, sdwd, sensory, sglasso, sglOptim, sGPCA, SINGLE, skatMeta, smam, SML, softImpute, SOR, spacejam, sparseHessianFD, sparseMVN, spatialprobit, SpatioTemporal, spdep, speedglm, ssfa, StableEstim, svcm, sybil, sybilccFBA, sybilcycleFreeFlux, sybilEFBA, sybilSBML, systemfit, textir, TimeProjection, tmvtnorm, TreePar, trustOptim, wfe
Bayesthresh, BioPhysConnectoR, dualScale, fdasrvf, HRM, MRSP, pom, rrlda, semGOF, Skillings.Mack, zoib
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, sgt, spfrontier, ssfa, truncreg
CAM, expectreg, FDboost, gamboostLSS, globalboosttest, InvariantCausalPrediction, parboost
Bclim, BiSEp, clustvarsel, CNprep, CNVassoc, EMCC, GESTr, LifeTables, MetabolAnalyze, msos, npde, prabclus, qclust, robustDA, Simpsons, SQN, tclust, Traitspace, upclass
adaptsmoFMRI, anominate, bacr, BayesMed, bayespref, CoinMinD, cudia, gset, HMP, HSROC, hzar, miscF, NHMM, PhViD, R2GUESS, RxCEcolInf, SimpleTable, uskewFactors
bgeva, CAM, dlmap, dsm, DSsim, eHOF, fda.usc, gamlss.add, gamlss.spatial, gamm4, gammSlice, gvcm.cat, icaOcularCorrection, iRegression, ismev, itsadug, labdsv, logistf, MAPLES, modTempEff, mombf, MPINet, multipleNCC, nontarget, ordPens, R2BayesX, reams, robustgam, scam, season, SemiParBIVProbit, SemiParSampleSel, semsfa, STAR, trioGxE, TSA, ZeligGAM
BaM, CALIBERrfimpute, genpathmox, HardyWeinberg, hot.deck, logistf, miceadds, roughrf, SYNCSA
AquaEnv, cellVolumeDist, HydroMe, micEconCES, mkin, onls, propagate, qpcR, Ritc, tumgr
brainR, curvHDR, grt, kml3d, ks, longitudinalData, mritc, ptinpoly, VecStatGraphs3D
DIFlasso, FRESA.CAD, intReg, IQCC, lmmlasso, maxLik, polywog
bayesMCClust, bayess, DiceOptim, ERP, FAMT, MaXact, mdsdt, PAGWAS, PLordprob, qtlhot, Rgbp, siar, StratSel, Sunder
earlywarnings, irtProb, LambertW, LIHNPSD, spfrontier
ATmet, BaSTA, BVS, CEoptim, eiPack, hysteresis, lordif, ltm, NEff, NHMM, RM2, score, spatial.gev.bma, Surrogate, trioGxE
bifactorial, BSagri, factorplot, HH, MAVTgsa, medflex, mixlm, mutossGUI, nparcomp, RcmdrPlugin.coin, RcmdrPlugin.doex
adaptsmoFMRI, AdMit, asd, AssocTests, AssotesteR, B2Z, BACprior, BAEssd, bayesGARCH, Bayesianbetareg, Bayesthresh, BAYSTAR, bcrm, Bergm, bglm, bgmm, bifactorial, BinNonNor, BinNor, Bmix, bnormnlr, BNPTSclust, CAMAN, caper, CDM, condMVNorm, CPMCGLM, crawl, cslogistic, cudia, dawai, depend.truncation, distrEllipse, dmt, DoseFinding, DunnettTests, edrGraphicalTools, EMC, EMMIXskew, emulator, FactMixtAnalysis, FAmle, faoutlier, fdasrvf, fExpressCertificates, fgof, ForImp, freqparcoord, genetics, GenForImp, GenOrd, GGMselect, glmm, glmpathcr, GLSME, growthrate, gset, hbim, hdrcde, hglasso, HPbayes, hsmm, hyperSpec, ICS, ICSNP, IMIS, kcirt, ks, lava.tobit, lawstat, LCAextend, lmec, lmenssp, LogConcDEAD, logcondiscr, lordif, LSMonteCarlo, mada, MAMS, mc2d, MCPMod, mediation, MetabolAnalyze, metamisc, MetSizeR, mhsmm, miscF, miscFuncs, MitISEM, MIXFIM, mixsmsn, mmcm, Modalclust, mombf, MRsurv, multcomp, multinomRob, MultiOrd, multxpert, muma, mutoss, mvProbit, mvSLOUCH, netgen, nicheROVER, nlsem, nparcomp, OptInterim, OrdNor, PairedData, paleoTS, pamm, parallelMCMCcombine, party, PAWL, plgp, PoisBinNonNor, PoisBinOrd, PoisBinOrdNor, PoisNor, polycor, powerGWASinteraction, psbcGroup, qclust, QRM, R2GUESS, RAD, reglogit, RidgeFusion, RxCEcolInf, SamplerCompare, schwartz97, selectiongain, SeleMix, SemiParSampleSel, SEMModComp, simboot, snipEM, SNPassoc, SNPmaxsel, sp23design, spate, spatialnbda, spatialprobit, spatialTailDep, spfrontier, sscor, ssmrob, SSsimple, Stem, symmoments, tclust, texmex, tlmec, tmvtnorm, TTmoment, uskewFactors, wbsts, weightedScores, yuima
Bergm, Blaunet, blkergm, enaR, ergm, ergm.count, ergm.graphlets, ergm.userterms, haplotypes, hergm, latentnet, lvm4net, mpa, ndtv, networkDynamic, networkDynamicData, networksis, OutbreakTools, statnet, statnetWeb, tergm
EpiModel, ndtv, networkDynamicData, statnet, tergm
alphaOutlier, drgee, GNE, likelihoodAsy, sigloc, SPmlficmcm
abd, AdaptFit, AdaptFitOS, assist, BiDimRegression, cati, cccrm, CorrMixed, CpGassoc, dlmap, DPpackage, far, FlexParamCurve, gamlss, goric, HydroMe, insideRODE, ipdmeta, IPMpack, JM, JMbayes, joineR, JointRegBC, JoSAE, likelihood, lmenssp, lmeSplines, lmfor, longpower, LoopAnalyst, LVMMCOR, meboot, MethComp, mgcv, MSwM, multilevel, mvctm, nlmeODE, nlsem, orQA, pheno, picante, plmm, portfolio, prc, predictmeans, ProfileLikelihood, psychometric, qrLMM, ramps, REEMtree, RepeatedHighDim, sae, sitar, SPREDA, TapeR
CCpop, corHMM, episplineDensity, MaxPro, OUwie, parma
abc, BaM, CBPS, depmixS4, epiDisplay, factorplot, gamlss.add, gamlss.mx, HIest, HydeNet, ImpactIV, introgress, LOGICOIL, MDM, partialOR, pocrm, roughrf, synthpop
CovSel, DepthProc, rddtools, semsfa, stam
alabama, B2Z, bayesDccGarch, bnormnlr, catIrt, CBPS, CompLognormal, compound.Cox, copCAR, dhglm, DOBAD, fdasrvf, fgof, fracprolif, frailtyHL, ghyp, HPbayes, lbfgsb3, lmeNB, ltbayes, mederrRank, mgpd, mipfp, mvglmmRank, mvSLOUCH, optextras, PSM, QRM, RCPmod, SemiMarkov, SpeciesMix, ssym, stremo, ThresholdROC, turboEM
brainR, COMBIA, cudaBayesreg, dcemriS4, dpmixsim, fslr, mritc
AtelieR, frmqa, hpcwld, iteRates, MM, NSM3, rTableICC
evtree, NHEMOtree, psychotree, quint, smbinning, vcrpart
pbdBASE, pbdDEMO, pbdDMAT, pbdSLAP, pmclust
DIFlasso, DIFtree, lmmlasso, multiPIM, ROC632, subtype, uplift
indicspecies, rich, Storm, Traitspace, vegan
astro, audiolyzR, cytoDiv, DIFtree, dupiR, EasyStrata, epade, GeneticTools, lba, magicaxis, MetFns, mutossGUI, optpart, plotmo, SeqFeatR, simplexreg, surv2sampleComp
autopls, BioMark, ChemometricsWithR, chemosensors, chillR, dbstats, dmm, lspls, MetStaT, mixlm, monomvn, muma, obliqueRF, RcmdrPlugin.NMBU, RVtests, svapls
abctools, bcpa, bmk, boottol, BSGS, chemosensors, ClustGeo, CPMCGLM, cshapes, EBMAforecast, EIAdata, evolqg, fishmove, gcbd, gpmap, gsDesign, imager, ivlewbel, JAGUAR, Kernelheaping, MRMR, NAPPA, ONETr, plotSEMM, PMA, psytabs, pxR, rapport, rcbalance, Rcell, RDSTK, remix, reshapeGUI, RForcecom, Rmisc, RSAGA, RStorm, selfea, smatr, SSrat, statcheck, timeordered, wordmatch
IM, imager, indicoio, measuRing, pid, RXKCD
adhoc, embryogrowth, gaussquad, kza, kzft, orthopolynom, rationalfun
colorscience, crqa, episplineDensity, likelihoodAsy, mixlm, mousetrack, RAHRS, TapeR, TDD, VideoComparison
DistatisR, ExPosition, InPosition, MExPosition, TExPosition, TInPosition
argparse, AtelieR, benchmark, DescribeDisplay, gsubfn, MetaQC, nls2, PKgraph, pmg, R2STATS, Rcell, SparseFactorAnalysis, sqldf, traitr
cba, ConsRank, dtw, dtwclust, kst, recommenderlab, rEMM, smdc, StatMatch, stream, TSdist
BinNor, Compind, DeducerPlugInScaling, GAabbreviate, HDMD, multicon, MultiOrd, nFactors, nonparaeff, orddom, PoisBinOrdNor, psytabs, random.polychor.pa, Rz, Scale, SODC, SSDforR, SubLasso
ASMap, dlmap, eqtl, mpMap, mQTL, pheno2geno, qtlbook, qtlhot, qtlnet, wgaim, xoi
BLCOP, BSquare, cosso, DAGGER, directlabels, FRAPO, gtop, iterLap, kappalab, kinship2, ldlasso, MonoPoly, pencopula, popbio, SEL, SPIn, ternvis, wSVM
abc, alphaOutlier, AOfamilies, BSquare, cqrReg, EILA, emplik, genpathmox, GeoXp, lss, McSpatial, mvctm, OutlierDC, pheno, plaqr, qrjoint, quantregGrowth, Rfit, riv, RobPer, rqPen, turboEM, vdg
Agreement, FFD, HTMLUtils, psytabs, RcmdrPlugin.EACSPIR, STAR
DSpat, Geneland, GeoGenetix, LS2Wstat, ProbForecastGOP
AUCRF, bartMachine, BigTSP, Boruta, conformal, D2C, interpretR, MAVTgsa, missForest, mlDNA, ModelMap, partitionMap, quantregForest, RFgroove, rfPermute, rfUtilities, roughrf, spikeslab, sprint, trimTrees, varSelRF
celestial, McSpatial, RapidPolygonLookup, RWBP, StatMatch
biomod2, cmsaf, crawl, diffeR, dismo, dynatopmodel, ENiRG, ENMeval, FedData, gdistance, gdm, geostatsp, geotopbricks, gfcanalysis, hsdar, kissmig, letsR, lulcc, mapmisc, maxlike, meteoForecast, MigClim, ModelMap, modiscloud, move, OpenStreetMap, paleobioDB, phyloclim, PopGenReport, PrevMap, rasterVis, remote, rts, sampSurf, satellite, ShapeSelectForest, sirad, SpatialPosition, spatial.tools, spdynmod, TOC, usdm, virtualspecies
EnQuireR, RcmdrPlugin.BCA, RcmdrPlugin.coin, RcmdrPlugin.depthTools, RcmdrPlugin.doex, RcmdrPlugin.EBM, RcmdrPlugin.EcoVirtual, RcmdrPlugin.epack, RcmdrPlugin.mosaic, RcmdrPlugin.MPAStats, RcmdrPlugin.plotByGroup, RcmdrPlugin.pointG, RcmdrPlugin.ROC, RcmdrPlugin.seeg, RcmdrPlugin.SM, RcmdrPlugin.steepness, RcmdrPlugin.UCA
ASMap, bayespref, beadarrayFilter, DeducerText, ENmisc, FieldSim, GISTools, GOplot, introgress, latticeExtra, LeLogicielR, linkcomm, LSC, MDSGUI, micromap, msr, mvtsplot, PF, phenmod, profileR, PST, qdap, qPCR.CT, RArcInfo, rCarto, RcmdrPlugin.pointG, RcmdrPlugin.SM, RFLPtools, statebins, TrackReconstruction, TraMineRextras, TRSbook, wordcloud
AdaptiveSparsity, Amelia, ASPBay, BaBooN, bcpa, bfp, bifactorial, blockmodels, brms, CARBayes, CARBayesST, ccaPP, clogitL1, ClustMMDD, ConConPiWiFun, copCAR, cqrReg, dbmss, dendextendRcpp, DepthProc, dils, diversitree, dslice, ecp, EditImputeCont, emIRT, EPGLM, fastGHQuad, FBFsearch, FCNN4R, FDGcopulas, FRESA.CAD, FSInteract, fugeR, gdm, GeneticTools, GENLIB, glmgraph, Gmisc, gMWT, growcurves, growfunctions, GSE, GUTS, HUM, hypervolume, IBHM, IsingSampler, JAGUAR, kergp, kmc, lm.br, matchingR, mice, miscF, Mposterior, MRIaggr, MVB, NetSim, ngspatial, nonlinearTseries, NPBayesImpute, oem, OneArmPhaseTwoStudy, orQA, PedCNV, PerMallows, PoweR, propagate, quadrupen, Rborist, Rclusterpp, rcppbugs, RcppClassicExamples, RcppExamples, RcppOctave, RcppXts, remote, rexpokit, Rmalschains, Rmixmod, RmixmodCombi, robustgam, rotations, RoughSets, RSNNS, RSofia, Rsomoclu, rstan, rtkpp, RVowpalWabbit, satellite, sdcTable, seismicRoll, sequences, simFrame, snipEM, SOD, spacodiR, sparseHessianFD, StMoSim, survSNP, tagcloud, tbart, treeclim, trustOptim, unmarked, VideoComparison, waffect, WideLM, wsrf, zic
FBFsearch, FisHiCal, miscF, MVB, PedCNV, prospectr, resemble, robustgam, zic
anametrix, aqr, brewdata, CHCN, couchDB, crn, factualR, fds, helsinki, jSonarR, kintone, LightningR, notifyR, OIdata, ONETr, osmar, psidR, pullword, pumilioR, R4CouchDB, rbitcoinchartsapi, RDSTK, restimizeapi, RForcecom, rHpcc, Rjpstatdb, Rlabkey, rLTP, rneos, ROMIplot, ropensecretsapi, rPlant, RSelenium, RStars, Rtts, RYoudaoTranslate, scrapeR, shopifyr, sos4R, sotkanet, source.gist, SPARQL, streamR, support.CEs, SynergizeR, tibbrConnector, tumblR, VideoComparison, zendeskR
biomod2, emme2, gcbd, Giza, lctools, PAWL, pedigree, PhaseType, profileR, rapportools, Rcell, RcmdrPlugin.EACSPIR, reportRx, RSAP, SMFI5, unmarked, wux
afex, chemosensors, CINOEDV, ClimClass, COPASutils, ESGtoolkit, gapmap, gdm, ifaTools, MRMR, pbdPROF, pxR, reshapeGUI, STMedianPolish, tcR, TriMatch, wordmatch
DeducerSpatial, diffeR, divagis, FedData, hsdar, landsat, M3, mgraph, micromap, ModelMap, modiscloud, move, OpenStreetMap, prevR, r2dRue, rangeMapper, ShapeSelectForest, spatial.tools, SPODT, TOC, UScancer
anchors, DiceOptim, FAiR, KrigInv, multinomRob, RobPer
DivE, expp, geospacom, GISTools, Grid2Polygons, highriskzone, ibeemd, KappaV, pycno
abcdeFBA, alphashape3d, animalTrack, bios2mds, BiplotGUI, bpca, brainR, ConsRank, curvHDR, depth, DiceView, directPA, DirichletReg, dti, edrGraphicalTools, eegkit, etasFLP, FieldSim, foodweb, frontiles, fso, gdimap, geomorph, GeoXp, GGEBiplotGUI, graphscan, grt, hgam, hiPOD, hypervolume, kml3d, ks, longitudinalData, LSAfun, Maeswrap, MDSGUI, MSQC, msr, mtk, mvmesh, nat, nat.nblast, nat.templatebrains, NeatMap, nonlinearTseries, optBiomarker, pavo, plot3Drgl, qpcR, QuantifQuantile, R330, RadOnc, RcmdrPlugin.TeachingDemos, ROCS, rotations, Rpdb, SEERaBomb, Sim.DiffProc, sphereplot, tkrgl, tolerance, VDA, VecStatGraphs3D, YplantQMC
abcdeFBA, cosso, DAGGER, FRAPO, LPmerge, rorutadis, sdcTable, sparkTable
fit4NM, gWidgets2RGtk2, gWidgetsRGtk2, HomoPolymer, MenuCollection, meta4diag, PKgraph, rattle, RGtk2Extras, tourrGui
BANOVA, BaySIC, dcmle, HydeNet, metamisc, pcnetmeta, prevalence, PurBayes, R2jags, simmr, zoib
arulesNBMiner, bartMachine, Crossover, edeR, ENMeval, extraTrees, gemtc.jar, glmulti, gMCP, helloJavaWorld, iplots, JGR, KoNLP, mallet, MSIseq, mwa, OpenStreetMap, rcdklibs, rChoiceDialogs, rDNA, REPPlab, RH2, RImpala, rJavax, RJDBC, rJPSGCS, RJSDMX, rJython, rkafka, rkafkajars, RMOA, RMongo, RNCBIEUtilsLibs, RNetLogo, ror, RSQLServer, rsubgroup, SBRect, scagnostics, sjdbc, spcosa, streamMOA, venneuler, x.ent, xlsx, xlsxjars
couchDB, df2json, edeR, indicoio, kintone, notifyR, RDSTK, Rfacebook, rJython, Rlabkey, rPlant, RYoudaoTranslate, SmarterPoland, source.gist, Storm, streamR, tibbrConnector, zendeskR
audiolyzR, factualR, LightningR, pxR, R4CouchDB, rbitcoinchartsapi, restimizeapi, ropensecretsapi, rPython, RSelenium, RStars, RXKCD, SynergizeR, tumblR, VideoComparison, WDI, weatherr
AMOEBA, CNprep, MicSim, pbdBASE, pbdDEMO, pbdDMAT, pbdMPI, pbdSLAP, pmclust, snowFT, sprint
ACTCD, CellularAutomaton, curvetest, DATforDCEMRI, GAD, GhcnDaily, NSA, R.oo
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, iFes, MEET, obliqueRF, pathClass, PredictABEL, RcmdrPlugin.ROC, rocc, sperrorest, subtype
ibmdbR, ImportExport, mixsep, RODBCext, RODM, stacomirtools
CellularAutomaton, curvetest, DATforDCEMRI, GhcnDaily, NPCD, NSA, plmDE, R.filesets, R.utils
bvpSolve, diffdepprop, diffEq, ecolMod, eel, FME, hsdar, kmc, LLSR, mkin, pbatR, prop.comb.RR, ReacTran, weightedScores
biotools, erpR, gamlss.demo, GUIDE, LinRegInteractive, MDSGUI, optBiomarker, RVideoPoker, soilphysics, vows
ada, adabag, chemometrics, DStree, fda.usc, gamlss.add, GPLTR, maboost, maptree, multiPIM, NHEMOtree, PSAgraphics, quint, REEMtree, rpart.plot, rpartScore, rpart.utils, sperrorest, stima, treeClust
biwt, BMA, DepthProc, FAiR, FRB, groc, muma, riv, RobAStBase, robust, robustfa, rrcovHD, rrcovNA
alphaOutlier, depmixS4, DiscreteInverseWeibull, DiscreteLaplace, DiscreteWeibull, DNAtools, GEVStableGarch, GsymPoint, IDPSurvival, JOP, LDOD, likelihoodAsy, mipfp, robustDA, SemiMarkov
archivist, CITAN, filehashSQLite, gcbd, MUCflights, rangeMapper, RecordLinkage, refGenome, RQDA, SEERaBomb, snplist, sqldf, SSN
discrimARTs, DistributionUtils, FKF, futile.paradigm, GeneralizedHyperbolic, gsDesign, permGPU, rkafka, schwartz97, SkewHyperbolic, SoilR, VarianceGamma
acnr, aroma.affymetrix, aroma.cn, aroma.core, calmate, ENiRG, GhcnDaily, HyPhy, MSIseq, NSA, PubBias, tmle.npvi
AER, CADFtest, cjoint, COUNT, gmm, inference, ivpack, list, mediation, mfx, midasr, RcmdrMisc, rdd, strucchange, vars, Zelig
bios2mds, DeducerSpatial, dslice, precintcon, RSDA, statebins, TDA, TriMatch
bpca, CHsharp, GPCSIV, ISDA.R, lle, MDSGUI, poLCA, Sim.DiffProc, windex
bmem, dpa, faoutlier, qtlnet, semdiag, semGOF
CNOGpro, evobiR, MEET, mlgt, rPlant, sivipm
CryptRndTest, distr, ICEbox, lordif, modiscloud, plfm, polycor, simrel
alphahull, mvoutlier, RcmdrPlugin.seeg, seeg, StatDA
diagram, ecolMod, EMMAgeo, marelac, pathdiagram, ReacTran, sparsenet, spnet, symbols
adehabitat, aspace, BayesX, DSsim, fossil, RPyGeo, RSAGA
archivist, bde, CLME, DynNom, edgar, enviPick, Factoshiny, ifaTools, mirtCAT, phenology, plotSEMM, quipu, RJafroc, sglr, SHELF, shinystan, Sofi, sparkTable, statnetWeb
biogram, cherry, maptpx, qlcMatrix, RcmdrPlugin.temis, Rcplex, Rglpk
fpca, irtoys, magicaxis, mem, plmm, vioplot
bipartite, CEoptim, egonet, enaR, hergm, ndtv, NetCluster, Rambo, relevent, SSrat, statnet, VBLPCM
BioPhysConnectoR, CePa, doSNOW, snowfall, snowFT
AMOEBA, bmem, classyfire, DLMtool, fugeR, GlobalDeviance, graphscan, hsphase, kcirt, lle, megaptera, mglmn, MicSim, mlDNA, peperr, PIGE, R2GUESS, RMark, rsgcc, widals
adehabitat, adehabitatHR, adehabitatHS, adehabitatLT, adehabitatMA, automap, biomod2, CAMAN, cmsaf, colorscience, constrainedKriging, crawl, cshapes, DeducerSpatial, diseasemapping, dismo, divagis, DivE, ecospat, ENiRG, excursions, expp, FedData, FeedbackTS, fossil, frontiles, georob, geospacom, geosphere, geospt, geosptdb, geostatsp, GISTools, graphscan, graticule, Grid2Polygons, GWmodel, hsdar, ibeemd, INLABMA, intamap, KappaV, landsat, MapGAM, mapmisc, maptools, MBA, MetaLandSim, meteoForecast, micromap, modiscloud, move, MUCflights, Nippon, plotGoogleMaps, polyCub, prevR, pycno, r2dRue, RandomFields, RapidPolygonLookup, raster, rgdal, rgrass7, rtop, rts, rworldmap, rworldxtra, sampSurf, secrlinear, seg, sos4R, SpatialEpi, spdep, spgrass6, spgwr, splancs, spnet, SPODT, spsurvey, spTDyn, ssfa, SSN, stam, STMedianPolish, surveillance, tbart, trip, UScensus2000cdp, UScensus2000tract, UScensus2010, usdm, vec2dtransf, vegclust, vetools, wux
copCAR, excursions, fields, gamlss.spatial, GPFDA, latticeDensity, LatticeKrig, mvMORPH, smnet, spThin
evmix, hts, maxent, McSpatial, modelfree, pheno, quantreg, REBayes, rexpokit, rms, RTextTools
adaptsmoFMRI, alphahull, aoristic, BAT, dbmss, Digiroo2, dixon, DSpat, ecespa, ETAS, GriegSmith, latticeDensity, MetaLandSim, ppmlasso, RcmdrPlugin.seeg, seeg, selectspm, SGCS, siar, siplab, sparr, spatialsegregation, SpatialVx, stpp
AMOEBA, DCluster, Digiroo2, expp, GeoXp, ibeemd, latticeDensity, LS2Wstat, spatialprobit, splm, ssfa
alphahull, aspace, dixon, DSsim, ecespa, latticeDensity, PVR, soilprofile, stpp, stppResid
cond, CopulaREMADA, csampling, dglm, diffIRT, GHQp, h2o, joineR, lmeNB, marg, mcll, mixcat, MVR, nlreg, PCS, penalizedSVM, survsim
blkergm, ergm, ergm.count, ergm.graphlets, ergm.userterms, latentnet, tergm
AnDE, enaR, eqs2lavaan, evobiR, exsic, FRESA.CAD, fslr, geotopbricks, gsDesign, imager, indicoio, KoNLP, LindenmayeR, Maeswrap, mpoly, mtk, orgR, patchSynctex, PepPrep, pxR, QCAtools, quipu, recoder, RGENERATEPREC, RJafroc, rsgcc, ryouready, sdcTable, sqlutils, ssh.utils, tumblR, vardpoor
diversitree, hisse, mvMORPH, ouch, TreePar
cjoint, ICS, lavaan.survey, mapStats, MOJOV, odfWeave.survey, pedgene, relaimpo, samplingbook, sptm, ssfit, StatMatch, svyPVpack, twang, VIMGUI
AER, AF, ahaz, AHR, AIM, anoint, attribrisk, BaM, BayesMixSurv, bayesSurv, BGPhazard, BivarP, BMA, BSGW, bshazard, carcass, cchs, cmprsk, CNVassoc, coin, compound.Cox, concreg, cond, CoxBoost, coxinterval, coxme, coxphw, CoxRidge, coxrobust, CPE, crossmatch, crrp, crrSC, csampling, currentSurvival, distcomp, doBy, DPpackage, drgee, dynpred, dynsurv, eha, ELYP, epiDisplay, epiR, etm, flexsurv, frailtyHL, frailtypack, gamlss.cens, gamlss.nl, gbm, geneSignatureFinder, glmpath, globalboosttest, glrt, greyzoneSurv, GSAgm, gte, gtx, HapEstXXR, haplo.ccs, Hmisc, icenReg, IDPSurvival, InferenceSMR, intcox, interval, invGauss, JM, JMbayes, joineR, JointRegBC, kaps, kin.cohort, km.ci, kmconfband, kmi, lava.tobit, lcmm, LncMod, LogicReg, luca, marg, MetaDE, mfp, missDeaths, mmc, MMMS, MRH, mRMRe, MRsurv, mstate, multcomp, multipleNCC, NADA, NestedCohort, nlreg, NPHMC, NSM3, OIsurv, optmatch, OrdFacReg, OutlierDC, p3state.msm, packHV, paf, pamr, parfm, partDSA, pbatR, penalized, peperr, permGPU, PHeval, phmm, PIGE, plRasch, PRIMsrc, prognosticROC, PwrGSD, QoLR, QualInt, RcmdrPlugin.coin, RcmdrPlugin.survival, relsurv, remix, risksetROC, rms, RobustAFT, ROC632, ROCt, RPCLR, rsig, rstpm2, season, seawaveQ, seqDesign, seqMeta, SIMMS, simMSM, SIS, skatMeta, smcure, smoothHR, smoothSurv, SNPassoc, sp23design, speff2trial, SPREDA, sprinter, sptm, ssym, STAR, stepp, superpc, surv2sampleComp, survAccuracyMeasures, survAUC, survC1, survexp.fr, Survgini, survIDINRI, survivalMPL, survJamda, survMisc, SurvRank, survRM2, survSNP, threg, timereg, tnet, TraMineRextras, TransModel, TwoStepCLogit, uniCox
GlobalFit, RSeed, sybilccFBA, sybilcycleFreeFlux, sybilDynFBA, sybilEFBA, sybilSBML
AnthropMMD, BiplotGUI, forensim, MDSGUI, mixsep, SeqFeatR, SRRS, stosim
humanFormat, kergp, MInt, SortableHTMLTables, StableEstim
fArma, fAsianOptions, fAssets, fBasics, fBonds, fCopulae, fExoticOptions, fExtremes, fGarch, fImport, fMultivar, fNonlinear, fOptions, forecast, fPortfolio, fractalrock, fRegression, fTrading, fUnitRoots, TimeProjection, timeSeries
caschrono, 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, SyNet, VIMGUI
DeducerText, manifestoR, maxent, RcmdrPlugin.temis, smdc, tm.plugin.dc
fExpressCertificates, imputeLCMD, propagate, spatialprobit, spfrontier, uskewFactors
aster, cepp, dMod, glmm, iWeigReg, mcemGLM, MInt, relevent, UWHAM
TScompare, TSfame, TSmisc, TSMySQL, TSodbc, TSPostgreSQL, TSsdmx, TSSQLite
acp, CADFtest, CryptRndTest, earlywarnings, fma, fpp, Mcomp, nonlinearTseries, RcmdrPlugin.epack, RcmdrPlugin.UCA, TSA
dualScale, ENmisc, RcmdrPlugin.mosaic, RcmdrPlugin.SM, simPop, vcdExtra
analogue, BAT, betaper, BiodiversityR, bipartite, blender, cocorresp, CommunityCorrelogram, dave, FD, FreeSortR, gdm, GUniFrac, iDynoR, isopam, loe, mpmcorrelogram, palaeoSig, paleoMAS, PCPS, picante, RAM, rareNMtests, recluster, rich, simba, SYNCSA, vegan3d, vegclust
Bayesthresh, BSquare, EffectStars, GEVcdn, iteRates, lawstat, multgee, ordBTL, pheno2geno, prob, ZeligChoice
adwave, brainwaver, RHRV, W2CWM2C, wavemulcor, wmlf
binhf, costat, CVThresh, haarfisz, locits, LS2W, refund.wave, treethresh, waveband, WiSEBoot
dvfBm, eegAnalysis, RFgroove, TSclust, wbsts
aidar, anametrix, apsimr, biorxivr, brewdata, compareODM, EcoHydRology, EcoTroph, EIAdata, ESEA, gnumeric, grImport, iDynoR, ips, mseapca, mtk, MUCflights, odfWeave, ONETr, osmar, pmml, pumilioR, qat, R4CDISC, RDota, readODS, rentrez, rFDSN, RFinanceYJ, RForcecom, rgexf, rgrass7, rHpcc, Rjpstatdb, Rlinkedin, rneos, RSDA, RSelenium, RWeather, RXMCDA, scrapeR, sos4R, SPARQL, spgrass6, StatDataML, SubpathwayGMir, support.CEs, symbolicDA, weatherr, WikipediaR, XML2R
A3, acnr, AmpliconDuo, bayesMCClust, compareGroups, DATforDCEMRI, etable, FactoClass, fifer, gsDesign, IndependenceTests, klausuR, LeLogicielR, likert, LinRegInteractive, MAMA, multilevelPSA, pamctdp, PF, PIGE, quipu, RcmdrPlugin.NMBU, reporttools, rplotengine, rtable, sdcMicro, SeleMix, seqDesign, stacomirtools, surveillance, survSNP, TableMonster, TRSbook, twang
aqr, bsts, cotrend, dynatopmodel, egcm, EIAdata, eventstudies, FinancialInstrument, highfrequency, hydroTSM, IBrokers, PerformanceAnalytics, PortfolioAnalytics, Quandl, quantmod, RcmdrPlugin.epack, RcppXts, RFinanceYJ, rts, YieldCurve
acc, AER, AutoSEARCH, betategarch, bsts, changepoint, dyn, dynlm, egcm, EIAdata, EloRating, Evapotranspiration, eventstudies, fast, FinancialInstrument, FinTS, FLIM, forecast, fts, fxregime, gamlss.util, geotopbricks, gets, glogis, highfrequency, hydroGOF, hydroTSM, IBrokers, lgarch, lmtest, mar1s, meteoForecast, Modalclust, phenology, PortfolioAnalytics, PortRisk, QoLR, quantmod, RcmdrPlugin.temis, rdatamarket, reGenotyper, RelValAnalysis, RJSDMX, RObsDat, rts, sde, sirad, solaR, STMedianPolish, StreamMetabolism, strucchange, SWMPr, tgram, VideoComparison, wq, xts, yuima
arm, BayesComm, bayesPop, biomod2, brms, CFC, DMwR, gdimap, geostatsp, glmmBUGS, Gmisc, HH, latentnet, merTools, ncdf4.helpers, ncdf.tools, neuroim, OpenRepGrid, oro.nifti, pcalg, phylocurve, pssm, quantspec, R2jags, Rcmdr, RcmdrMisc, RCMIP5, RItools, RNCEP, RSDA, s2dverification, secr, secrdesign, SparseTSCGM, spatial.tools, spatstat, spectral.methods, treeclim
adegraphics, ads, clusterSim, entropart, Laterality, memgene, Momocs, msap, pez, phylobase, PopGenReport, poppr, RAM, RVAideMemoire, STEPCAM, symbolicDA, virtualspecies
adephylo, AFLPsim, apex, outbreaker, StAMPP
agricolae, conjoint, DoE.wrapper, radiant, SPOT, VdgRsm
anim.plots, gfcanalysis, phytools, spdynmod, srd, stream, TED
AutoModel, DTR, ExomeDepth, LogisticDx, mmeta, reportRx
adegenet, adephylo, betapart, BMhyd, BoSSA, CommT, evolqg, expands, gamclass, geomorph, gquad, GrammR, gromovlab, homals, kdetrees, lefse, markophylo, megaptera, Momocs, monogeneaGM, msap, nLTT, nodiv, outbreaker, OutbreakTools, P2C2M, PCPS, phyext2, phylobase, phylocurve, phyloland, PhyloMeasures, phyndr, poppr, primerTree, rdryad, Reol, rotl, sharpshootR, sidier, SigTree, STEPCAM, strataG, stylo, taxize, TKF
blmeco, carcass, CosmoPhotoz, eeptools, hbsae, mi, migui, mlVAR, rr
aemo, AntWeb, bigrquery, bnclassify, bold, boxr, broman, coala, datalist, dplyr, ecoengine, FastKNN, ggvis, gistr, managelocalrepo, neuroim, prettyunits, RDML, rdrop2, repra, reutils, rfisheries, rjstat, rprime, simcausal, solr, spareserver, tidyjson, USAboundaries
AzureML, d3heatmap, FastRWeb, gmailr, leaflet, MALDIquantForeign, R.devices, readMzXmlData, RSiteCatalyst, sendmailR, threejs, UNF
aftgee, antitrust, BinOrdNonNor, CatDyn, DSBayes, optimx, orsk
BatchExperiments, fail, metagen, parallelMap, ParamHelpers, RBPcurve, rsig, SwarmSVM, tspmeta, yakmoR
pcalg, plm, sortinghat, sparsediscrim, splm
biogram, DNAprofiles, ETLUtils, ffbase, MSBVAR, Stack
caTools, HierO, IgorR, nhlscrapr, oro.nifti, Pasha, rLiDAR
adegenet, bandit, biotools, bootLR, BSagri, btergm, Causata, circular, complmrob, CorrBin, crs, deming, DescTools, eggCounts, energy, frair, GeneralOaxaca, gsg, ic.infer, Kendall, lga, medflex, metaplus, MplusAutomation, multiwayvcov, np, pairwiseCI, perspectev, pgirmess, plsRbeta, plsRglm, polyapost, poppr, pse, pubmed.mineR, qat, R2OpenBUGS, referenceIntervals, refund, RVAideMemoire, SCBmeanfd, sem, sensitivity, shotGroups, simmr, sparkTable, SpatialVx, spdep, sprint, TraMineR, treeclim, xergm, yhat
BatchJobs, opencpu, Rook, roxygen2, tabplotd3
AutoModel, dotwhisker, HydeNet, pixiedust, radiant
MergeGUI, MissingDataGUI, plfMA, R2STATS, SeqGrapheR, vmsbase, x12GUI
afex, anacor, apaTables, apt, ART, AutoModel, bayesLife, BCA, caret, drc, drsmooth, dynlm, easyanova, EffectLiteR, ez, FactoMineR, fxregime, gamclass, gcmr, lessR, miceadds, micEconCES, mixlm, NHPoisson, panelAR, plsRglm, radiant, rasclass, RcmdrPlugin.BCA, referenceIntervals, rockchalk, rpubchem, RVAideMemoire, sdcMicro, sjPlot, translateSPSS2R, userfriendlyscience, VIM, zetadiv
bdynsys, caretEnsemble, climdex.pcic, diveMove, dtwclust, dynRB, gplots, NHMSAR, PharmacoGx, rmarkdown, RSelenium, RTextTools, sdPrior
BatchExperiments, BatchJobs, BBmisc, icd9, lasvmR, llama, mlr, parallelMap, ParamHelpers, RBPcurve, RcppShark, SwarmSVM, tspmeta, yakmoR
data.table, dga, Dominance, ncdf.tools, qdap, qdapTools, redcapAPI, rugarch, sqldf, vmsbase
chemometrics, classifly, classInt, clValid, DMwR, e1071, fpc, HistDAWass, ipred, lineup, mlearning, msSurv, RPEnsemble, stylo, supclust, wux
aoristic, FAOSTAT, mapStats, plotKML, questionr, rangeMapper, tmap
backShift, cds, DESnowball, JADE, lsbclust, movMF, pcalg, skmeans, stream
ADPclust, agricolae, Anthropometry, aqp, biplotbootGUI, clue, comato, convevol, CORElearn, DESnowball, disclapmix, EMA, FactoMineR, fpc, geophys, GrammR, gromovlab, Hmisc, hybridHclust, labdsv, monogeneaGM, multibiplotGUI, openair, optCluster, PANDA, PReMiuM, rainbow, randomUniformForest, recluster, relations, rEMM, rrcov, rrcovNA, sdcMicro, semiArtificial, SemiPar, SensoMineR, seriation, sharpshootR, skmeans, spatialEco, spikeSlabGAM, StatDA, stream, symbolicDA, TcGSA, traj, TSdist, vegan, vmsbase
agRee, arm, BaBooN, BANFF, BayesComm, bayescount, bayesLife, bayesmix, BayesSingleSub, bayesTFR, BayesX, Bchron, BEST, bfa, BRugs, btergm, btf, BTSPAS, CARBayes, CARBayesST, conting, dcmle, EasyMARK, eggCounts, eiwild, emdbook, EpiBayes, ergm, evolvability, geiger, geoBayes, hierarchicalDS, HLSM, hSDM, IFP, jagsUI, kobe, latentnet, list, lsmeans, marked, MfUSampler, mixAK, MplusAutomation, MRH, MSBVAR, multimark, networkTomography, nLTT, pcnetmeta, plotMCMC, polySegratioMM, pomp, qrjoint, R2admb, R2jags, R2OpenBUGS, r4ss, RcmdrPlugin.RMTCJags, redist, RMark, rr, runjags, SAVE, scape, SeqFeatR, simmr, sirt, sisus, slfm, sns, sparsereg, spBayesSurv, spdep, spikeSlabGAM, spTimer, sspse, stocc, TBSSurvival, tergm, tglm, xergm
AzureML, foreach, globals, lintr, multcomp, pkgmaker, PopED, pryr, svTools
afex, NPC, NSM3, pairwiseCI, party, shotGroups
anacor, BayesX, BiplotGUI, cds, circlize, DepthProc, effects, forecast, ftsa, gdimap, ggthemes, gpairs, HH, JBTools, mapStats, mcmcplots, metafolio, munsell, NMF, OpenRepGrid, plotKML, qgraph, rainbow, RcmdrMisc, semPlot, seriation, SGP, simPop, simsalapar, smacof, srd, TIMP, treemap, vcd, Wats
addreg, cem, CorrBin, DESnowball, DoE.base, isocir, klaR, label.switching, lllcrc, nettools, pcIRT, qualCI, Quor, ReliabilityTheory, sirt, survMisc, TraMineRextras
apt, cds, copulaedas, CryptRndTest, VineCopula
BinOrdNonNor, BMhyd, bootnet, cape, cate, corHMM, D2C, esaBcv, list, lymphclon, MCMCglmm, NORTARA, OUwie, parma, pcalg, perARMA, qgraph, r4ss, relaimpo, semPlot, sparsediscrim, spduration, tileHMM, wux
ALTopt, calibrator, dbmss, fMultivar, GB2, hyperdirichlet, kdecopula, np, planar, tseriesEntropy, vines
crunch, elastic, httr, random, readr, rio, rversions, V8
aLFQ, APSIM, benford.analysis, biomartr, Causata, chromer, clickstream, DataCombine, dataview, edmr, eeptools, emil, FAOSTAT, FedData, freqweights, gems, genderizeR, IAT, Kmisc, lar, ldamatch, lllcrc, LogisticDx, Luminescence, metaMix, miscset, OptiQuantR, optiRum, partialAR, PGRdup, PopGenReport, pxweb, qdapTools, quanteda, RAM, randomNames, RAPIDR, RbioRXN, rdrop2, RecordLinkage, repmis, repra, rerddap, retrosheet, rfisheries, rgauges, rgbif, rio, rlist, rplexos, RxnSim, SciencesPo, sdcTable, SGP, simcausal, simPH, solarius, SpaDES, statar, StatMeasures, strvalidator, survMisc, SWMPr, taxize, tcR, traits, translateSPSS2R, treebase, treemap, xgboost
BatchExperiments, BatchJobs, CITAN, db.r, dplyr, filehashSQLite, marmap, poplite, redcapAPI, refGenome, RObsDat, rplexos, RQDA, SEERaBomb, smnet, snplist, sqldf, sqliter, timeseriesdb, TScompare, TSdbi, TSfame, TSmisc, TSMySQL, TSodbc, TSPostgreSQL, TSsdmx, TSsql, TSSQLite, twitteR, UPMASK, vmsbase
cccd, MFHD, phonR, rLiDAR, spatstat, spdep, spsurvey
asbio, AssetPricing, bdynsys, capm, CollocInfer, EpiDynamics, flexsurv, geiger, HomoPolymer, httk, hypergeo, mkin, nLTT, pomp, spdynmod, stagePop, TIMP
bisectr, BrailleR, covr, creditr, demi, FedData, metacom, opencpu, pacman
aqp, archivist, BatchJobs, boxr, caretEnsemble, Crossover, devtools, distcomp, downloader, dplR, dpmr, ezsim, FeatureHashing, FSelector, fulltext, geiger, ggmap, ggplot2, harvestr, htmltools, httr, knitcitations, knitr, lintr, Luminescence, MALDIquantForeign, memoise, MTurkR, nat, nat.templatebrains, NMF, OpasnetUtils, optmatch, pander, pkgmaker, pomp, qmethod, R2MLwiN, Rbitcoin, Rcell, RCMIP5, RcppOctave, readMzXmlData, repmis, repo, rerddap, R.filesets, RLumShiny, rngtools, ROAuth, roxygen2, RSiteCatalyst, scidb, shiny, shinyjs, SpaDES, stashR, swirl, testthat, UNF
ecospat, GSIF, plotKML, PopGenReport, virtualspecies
distrDoc, logcondens.mode, RobLox, RobLoxBioC, ROptRegTS
ApacheLogProcessor, arqas, breakpoint, DNMF, EasyMARK, EFDR, enpls, EnsembleBase, EpiModel, GENLIB, GWLelast, hbm, Mediana, Morpho, mplot, myTAI, NMF, opentraj, parallelML, parallelSVM, parboost, penDvine, performanceEstimation, randomUniformForest, reval, RobustEM, rplexos, RRreg, semsfa, SGP, simPop, spatial.tools, StAMPP, SurvRank, timeSeq, VSURF, WGCNA
biomartr, MALDIquantForeign, PharmacoGx, SpaDES, stationaRy
ACDm, adegenet, ADPclust, aemo, assertr, AutoModel, backtestGraphics, bigrquery, biomartr, bootnet, boxr, broom, cdcfluview, choroplethr, chromer, COPASutils, DataCombine, datastepr, denovolyzeR, docxtractr, dotwhisker, ecoengine, EFDR, freqweights, gender, ggvis, gistr, googlesheets, gsheet, HydeNet, IATscores, internetarchive, laketemps, LocFDRPois, longurl, lookupTable, loopr, MazamaSpatialUtils, muir, myTAI, NCmisc, NPC, nullabor, peptider, pixiedust, pmc, PopED, poppr, pRF, qdap, qwraps2, randNames, rbison, rcicr, RCMIP5, rcrossref, RDML, rdrop2, rebird, repra, rerddap, rfishbase, rnoaa, rplexos, rplos, rPref, rvertnet, rwunderground, saeSim, SciencesPo, simPH, SimReg, sjPlot, sorvi, SpaDES, statar, stationaRy, SWMPr, taber, tidyjson, tidyr, Tmisc, traits, USAboundaries, vdmR, WufooR
bindata, cati, chemometrics, classInt, clusterfly, clusterSim, Deducer, dpcR, EnsembleBase, fungible, hda, hybridEnsemble, hydroTSM, lfl, LOST, MetaLandSim, mistral, MixGHD, mlearning, optBiomarker, PASWR2, ppiPre, rasclass, RcmdrMisc, RecordLinkage, rminer, RObsDat, RobustEM, RTextTools, sdcMicro, simPop, sprint, StatDA, stylo, SwarmSVM, symbolicDA, tableone, translateSPSS2R, TTAinterfaceTrendAnalysis, VIM, xseq
Bchron, convoSPAT, FactoMineR, flexCWM, mcmcse, mixOmics, MNM, pca3d, qgraph, RobustEM, SciViews, soc.ca
antitrust, cape, climwin, intamap, RecordLinkage, rtdists
BinaryEPPM, carcass, corHMM, CountsEPPM, ctmm, DAMOCLES, lymphclon, marked, markovchain, MCL, msm, MultiMeta, popdemo, rags2ridges, rugarch, SCGLR, switchnpreg, TKF
EMA, freqweights, GDAtools, GraphPCA, HistDAWass, pcaBootPlot
BLCOP, lefse, StableEstim, TTAinterfaceTrendAnalysis, userfriendlyscience
anacor, Ecfun, ftsa, hisemi, PerFit, refund
bootSVD, darch, IsoGene, rmgarch, SpaDES, Stack
ADPclust, astrochron, BayesLCA, bayesPop, bipartite, biwavelet, CARrampsOcl, convoSPAT, cope, dynatopmodel, earlywarnings, EGRET, etasFLP, GEOmap, geospt, hglasso, hht, letsR, lgcp, LICORS, LMERConvenienceFunctions, ltsk, ModelMap, popsom, prevR, qat, ramps, RNCEP, rNOMADS, RsimMosaic, rworldmap, sparseBC, SpatialExtremes, spatsurv, StMoMo, stocc, SurvCorr, TED, topologyGSA, vmsbase
Anthropometry, cccd, gstat, HighDimOut, hybridEnsemble, LICORS, unbalanced
ApacheLogProcessor, arqas, bigrf, blowtorch, boostr, breakpoint, caret, Causata, D2C, EasyMARK, EFDR, enpls, EnsembleBase, EpiModel, ezsim, gdalUtils, GENLIB, GWLelast, hbm, hdnom, HighDimOut, JBTools, ldamatch, lfl, lint, Mediana, Morpho, mplot, mvcwt, myTAI, NMF, opentraj, parallelML, parallelSVM, pec, performanceEstimation, polywog, primerTree, prospectr, proteomics, randomUniformForest, resemble, reval, RobustEM, rplexos, RRreg, RSNPset, semsfa, SGP, simPop, siRSM, spacom, spectral.methods, sperich, StAMPP, taxize, TED, timeSeq, tsDyn, TSMining, TSP, vardpoor, VSURF, WGCNA, YaleToolkit, ykmeans
acmeR, Amelia, DDIwR, Deducer, DescTools, EffectLiteR, fSRM, Hmisc, intsvy, lessR, maptools, miceadds, pmg, prevR, psData, R2MLwiN, RcmdrPlugin.BCA, retistruct, rio, rsatscan, sdcMicroGUI, Sofi, spsurvey, synthpop, translateSPSS2R, userfriendlyscience, VIMGUI, vmsbase, YourCast
AER, bdynsys, betareg, BinaryEPPM, CountsEPPM, crch, ExtremeBounds, fdaMixed, frontier, gcmr, glmx, greport, growcurves, HBglm, inferference, ivfixed, ivpanel, lfe, mnlogit, moult, npmv, oaxaca, plsRbeta, polywog, PResiduals, psychomix, psychotree, rddtools, sampleSelection, SCGLR, thsls, tosls, varian
COMMUNAL, nullabor, semiArtificial, stream, tspmeta
discSurv, hpoPlot, manifestoR, networkreporting, saeSim, sqliter, translate
darch, futile.matrix, ISOpureR, tawny, tawny.types
biomod2, bst, bujar, EnsembleBase, imputeR, inTrees, mvtboost
BioGeoBEARS, comato, DAMisc, Dominance, Ecfun, ENiRG, fheatmap, gmodels, gplots, likeLTD, lmms, LOST, MIPHENO, NetComp, polySegratio, qat, qdap, QTLRel, rAvis, RbioRXN, rdryad, rioja, rtematres, simSummary, sisus, TR8, TSmisc, vardpoor, wux
aftgee, CorrBin, Cprob, ipw, MethylCapSig
BMhyd, geomorph, lefse, phylocurve, pmc, RADami, Rphylopars
geophys, RFOC, rNOMADS, Rquake, RTOMO, s2dverification
betapart, cati, DepthProc, gdimap, hypervolume, pavo, pdfCluster, restlos, retistruct, rLiDAR, spaMM, STEPCAM, tmle.npvi
birdring, crimelinkage, diveMove, gfcanalysis, ggmap, GWLelast, lakemorpho, letsR, marmap
DescribeDisplay, MissingDataGUI, PopGenReport, robCompositions, userfriendlyscience, vdmR
OutbreakTools, RAM, sidier, spoccutils, SWMPr
ACDm, adegenet, alm, ANOM, antitrust, asremlPlus, asVPC, BACA, backShift, bamdit, BBEST, bdscale, bdvis, Biograph, BioStatR, blowtorch, bmmix, breakpoint, broman, BTSPAS, capm, caretEnsemble, Causata, ChainLadder, choroplethr, choroplethrAdmin1, classify, classyfire, clhs, clifro, CommT, complmrob, confidence, cooccur, cosinor, CosmoPhotoz, cplm, cutoffR, dcmr, DescribeDisplay, DFIT, diveRsity, dsm, DTR, DVHmetrics, dynsim, dynsurv, EasyHTMLReport, EcoGenetics, EffectLiteR, ega, egcm, emil, EpiDynamics, erer, evolqg, ez, ezsim, FAOSTAT, fheatmap, FinCal, forestFloor, fSRM, G2Sd, GERGM, gfcanalysis, GGally, ggdendro, ggenealogy, ggExtra, ggparallel, ggRandomForests, ggsubplot, gitter, googlesheets, GraphPCA, greport, growcurves, growfunctions, hierarchicalDS, HighDimOut, HistDAWass, HLMdiag, IAT, iNEXT, InformationValue, intsvy, kdetrees, kobe, llama, lmerTest, LocFDRPois, lsl, mapDK, marked, marmap, MAVIS, merTools, metagen, metaMix, Methplot, microbenchmark, micromap, mizer, Mobilize, multiDimBio, MultiMeta, myTAI, netgen, networkreporting, NeuralNetTools, ngramr, NMF, NORRRM, oaxaca, OpasnetUtils, optiRum, orderedLasso, P2C2M, pa, paleofire, partialAR, performanceEstimation, plot2groups, PlotPrjNetworks, plotROC, pmc, pogit, PopGenReport, poppr, predictmeans, PReMiuM, pRF, primerTree, proteomics, pscore, qdap, qgraph, qwraps2, rags2ridges, rAltmetric, randomUniformForest, rbison, rddtools, RDS, refund, repijson, repra, reproducer, rfigshare, rfisheries, RFmarkerDetector, rgauges, rgbif, rinat, rnoaa, RobustEM, robustlmm, RPPanalyzer, rSPACE, rvertnet, rWBclimate, rwirelesscom, saeSim, SCGLR, sdmvspecies, SemiParBIVProbit, SensMixed, SeqFeatR, sidier, simPH, SimReg, SixSigma, sjPlot, smoof, solarius, sorvi, SpaDES, statar, stcm, structSSI, strvalidator, survMisc, SurvRank, TcGSA, tigerstats, TreatmentSelection, treeclim, treemap, TSMining, tvm, UpSetR, USAboundaries, vdmR, vmsbase, Wats, wppExplorer, wq, x.ent
graphicalVAR, NHMSAR, qgraph, scout, SelvarMix, SparseTSCGM
anoint, c060, Causata, EnsemblePenReg, FADA, graphicalVAR, GWLelast, hdnom, hybridEnsemble, imputeR, IsingFit, knockoff, MGSDA, MPAgenomics, mpath, parboost, polywog, RSDA, rsig, RTextTools, sparsereg, stm, SurvRank, XMRF
bayesPop, MetaLandSim, mplot, RLumShiny, wppExplorer
Compind, mirt, OpenRepGrid, qmethod, radiant, TAM, traj, userfriendlyscience
cancerTiming, DNMF, fheatmap, GMD, JBTools, lmms, matie, MenuCollection, momr, monogeneaGM, msarc, MultiPhen, NCA, optCluster, plotMCMC, qat, quantable, r4ss, RAM, RPPanalyzer, seriation, sesem, shapeR, smart, SurvRank, TcGSA, TIMP, TopKLists, TROM, xhmmScripts
NMF, playwith, SGP, sidier, simsalapar, SpaDES, tmap, treemap
arqas, bamdit, brms, caretEnsemble, CommT, CosmoPhotoz, DTR, dynsim, forestFloor, fSRM, gdimap, granovaGG, Hmisc, likert, lmms, lsbclust, miscset, mosaic, pointRes, qdap, radiant, RAM, RDS, reproducer, rfPermute, rgauges, RSPS, shinystan, simPH, SimReg, soc.ca, sparsereg, spikeSlabGAM, survMisc, SWMPr, TriMatch, UpSetR, varian, vdg, waffle, YourCast
artfima, copula, dti, gdimap, geospt, geosptdb, LambertW, rtdists
automap, EFDR, GSIF, hydroTSM, intamap, intamapInteractive, meteo, plotKML, prevR, psgp, rtop
datamart, MplusAutomation, smbinning, SpecHelpers, vmsbase
cowplot, GGally, ggplot2, ggtern, gridExtra, Hmisc, ncappc, pheatmap, RcmdrPlugin.KMggplot2, strvalidator, tcR, waffle
alleHap, apmsWAPP, AutoModel, BayesFactor, bootnet, BradleyTerry2, CoClust, CoImp, conting, cooptrees, datautils, drc, eiwild, gdata, GGMselect, gplots, LINselect, LogicForest, MarkowitzR, metaMix, mixedMem, NSM3, paleobioDB, Pasha, PolyPatEx, polySegratioMM, qgraph, r4ss, randomUniformForest, RankAggreg, reservoir, RevEcoR, shinystan, sirt, sisus, smart, ss3sim, STEPCAM, supcluster, TcGSA, TROM
extremevalues, GrammR, metagear, playwith, plfMA, R2STATS, RQDA, SeqGrapheR, strvalidator, TR8, vmsbase
GrammR, metagear, PKgraph, plfMA, R2STATS, SeqGrapheR, strvalidator, vmsbase
ABCanalysis, aqp, BaBooN, bdynsys, choroplethr, Compind, datacheck, DeducerSpatial, Gmisc, HH, HistogramTools, hydroPSO, intsvy, lazyWeave, lmerTest, mapStats, MatchLinReg, mediation, momr, MXM, nhanesA, NSM3, PerFit, qgraph, rags2ridges, RAM, RcmdrMisc, redcapAPI, remix, rmngb, RPPanalyzer, scape, sdcMicroGUI, SDD, SensMixed, sharpshootR, smacof, soilDB, survMisc, SvyNom, TopKLists, translateSPSS2R, TTAinterfaceTrendAnalysis, VIMGUI, WGCNA, wppExplorer, wux, x12GUI, xkcd, xpose4
covr, DT, ggvis, htmlwidgets, leaflet, metricsgraphics, questionr, rmarkdown, shiny, shinybootstrap2, shinyBS, shinydashboard, shinyFiles, shinyjs
d3heatmap, DiagrammeR, DT, dygraphs, leaflet, metricsgraphics, networkD3, pairsD3, qrage, rhandsontable, scatterD3, svgPanZoom, threejs, visNetwork
boxr, opencpu, rfigshare, RGA, servr, shiny, spectrino, switchrGist, tabplotd3
abbyyR, alm, AntWeb, archivist, aRxiv, atsd, bigrquery, biomartr, bold, boxr, cdcfluview, chromer, covr, cranlogs, crunch, ddeploy, devtools, distcomp, dpmr, ecoengine, elastic, enigma, fitbitScraper, fulltext, gender, genderizeR, geocodeHERE, geojsonio, gistr, gmailr, googleAuthR, googlesheets, hoardeR, htmltab, imguR, internetarchive, knitcitations, longurl, manifestoR, miniCRAN, ngramr, opencpu, pdfetch, pollstR, primerTree, pushoverr, pvsR, pxweb, Quandl, randNames, rbhl, rbison, RBitly, rclinicaltrials, rcrossref, rdrop2, rebird, redcapAPI, REDCapR, rentrez, repmis, rerddap, rfigshare, rfishbase, rfisheries, rfoaas, RGA, rgauges, rgbif, rgeolocate, ridigbio, rinat, Rmonkey, rnbn, RNeXML, rnoaa, ROptimizely, rotl, rplos, RPublica, RSiteCatalyst, rsnps, RSocrata, rsunlight, rvertnet, rvest, rWBclimate, rwunderground, SocialMediaMineR, solr, SpaDES, spareserver, spocc, spoccutils, stmBrowser, stringgaussnet, swirl, SWMPr, taxize, threewords, traits, transcribeR, translateR, twitteR, WaterML, whoami, WikidataR, wikipediatrend, WufooR, yhatr
adegenet, aop, arulesViz, backShift, BANFF, betalink, bipartite, bnstruct, BoolNet, cape, causaleffect, CausalFX, CDVine, CIDnetworks, comato, crimelinkage, DCGL, degreenet, diffusionMap, Dominance, DSviaDRM, fbRanks, FCMapper, FedData, flows, FrF2, gemtc, ggenealogy, gRain, gRbase, gRim, gromovlab, intergraph, kknn, lintr, lvm4net, markovchain, MatchingFrontier, matie, mixOmics, nat, nat.templatebrains, netClass, netgen, nettools, networkTomography, outbreaker, pcalg, PGRdup, phangorn, poplite, poppr, ppiPre, qdap, qgraph, QuACN, rags2ridges, RcmdrPlugin.RMTCJags, RDS, restlos, RevEcoR, rPref, RQDA, semPlot, SeqGrapheR, sharpshootR, SID, sidier, sirt, smart, smnet, SpaDES, SSN, stringgaussnet, structSSI, synbreed, treemap, VineCopula, xergm, XMRF
mlearning, optBiomarker, RecordLinkage, RTextTools, SurvRank
arqas, blowtorch, boostr, doRNG, foreach, itertools2, ldamatch, lgcp, neuroim, polywog, prospectr, randomUniformForest, rcdk, resemble, scidb, semsfa, SGP, spacom, spatsurv, turboEM, YaleToolkit
Ecfun, geomorph, ggmap, gitter, HiveR, imguR, Momocs, qgraph, rcicr, readbitmap, RsimMosaic, shapeR, StereoMorph, zooimage
alm, autovarCore, AzureML, BEQI2, bigrquery, bold, boxr, broman, covr, cranlogs, crunch, daff, ddeploy, devtools, distcomp, dpmr, ecoengine, elastic, enigma, exCon, fulltext, gender, geojsonio, ggvis, gistr, gmailr, googleAuthR, htmlwidgets, httr, internetarchive, lawn, manifestoR, MBTAr, mongolite, ndtv, opencpu, pdfetch, polidata, pollstR, randNames, rbhl, rbison, RBitly, rcorpora, rcrossref, RDataCanvas, rdrop2, rebird, rentrez, repijson, rerddap, reutils, RGA, rgbif, rhandsontable, ridigbio, rinat, rio, rjstat, rlist, rmongodb, Rmonkey, rnoaa, ROptimizely, rotl, rplos, RPublica, RSiteCatalyst, rsnps, RSocrata, rsunlight, rvertnet, rWBclimate, SensusR, servr, SGP, shiny, shinybootstrap2, SocialMediaMineR, spectrino, spocc, stmBrowser, stmCorrViz, taxize, tidyjson, traits, V8, webchem, webutils, whoami, WikidataR, wikipediatrend, WufooR, x.ent, yhatr
COPASutils, fpc, fPortfolio, gkmSVM, kernelFactory, LinearizedSVR, mistral, pi0, plsRcox, qrjoint, rminer, SwarmSVM, Synth
adegraphics, BiplotGUI, diveMove, DVHmetrics, earlywarnings, gamclass, GeoXp, gplots, hdrcde, MSBVAR, prodlim, r2d2, rddtools, SCBmeanfd, SensoMineR, shotGroups, soil.spec, spd, synRNASeqNet, TSclust, TSdist
ADPclust, assertive, BEQI2, confidence, COPASutils, flowr, gistr, Gmisc, htmlTable, interAdapt, kfigr, Kmisc, knitLatex, knitrBootstrap, liftr, ncappc, opencpu, optiRum, pixiedust, qmethod, radiant, rchallenge, RcppFaddeeva, rite, rmarkdown, rNMF, rtable, ucbthesis, userfriendlyscience
birdring, cdcsis, feature, hdrcde, hypervolume, logcondens, rainbow, rugarch
futile.logger, futile.matrix, lambda.tools, tawny, tawny.types
chemometrics, CorReg, GGMselect, NHMSAR, plsRcox
adegraphics, agridat, AICcmodavg, aLFQ, ALTopt, analogue, ape, aqp, asbio, automap, bbmle, boolean3, c060, caretEnsemble, CDM, cg, ChainLadder, classify, coda, comato, copula, Cprob, cvTools, daewr, DAMisc, DBKGrad, dcmle, DepthProc, DOBAD, dplR, effects, eiwild, emdbook, EQL, eRm, etm, FactoMineR, faoutlier, fastR, FitAR, fungible, gamclass, GENLIB, Giza, Gmisc, gpairs, GPfit, greport, gstat, hexbin, hydroPSO, influence.ME, isa2, kdecopula, Kmisc, ldbounds, lga, lme4, locfit, lulcc, maptools, Matrix, mboost, metacom, mixPHM, mountainplot, MplusAutomation, MSBVAR, msSurv, mvna, mycor, nlme, openair, OUwie, paleofire, pedometrics, plotGoogleMaps, plotMCMC, polySegratioMM, PopGenReport, predictmeans, psychomix, qicharts, R2admb, R2STATS, RAM, rangeMapper, RcmdrPlugin.HH, refund, rioja, RItools, rminer, RobLox, RobLoxBioC, robustlmm, RPPanalyzer, rrcov, rrcovNA, RSPS, Rssa, runjags, scape, SetMethods, sharpshootR, SixSigma, slfm, sp, spacetime, SSN, stressr, stylo, Surrogate, synbreed, TAM, tiger, tigerstats, timeSeq, trajectories, tripEstimation, VBmix, VineCopula, visreg, waterData, x12GUI, YourCast, zoo
DAAG, gamclass, greport, Hmisc, hyperSpec, mosaic, openair, pedometrics, penDvine, qicharts, R2STATS, RcmdrPlugin.temis, sharpshootR, stressr, Surrogate, waterData
faoutlier, matrixpls, NlsyLinks, pscore, qgraph, semPlot, sesem, sirt, TAM, userfriendlyscience
assertr, datastepr, dplyr, emil, ggvis, loopr, mosaic, poplite, rex, rfishbase, simPH, statar, tidyr
FactoMineR, FitAR, HH, lessR, meifly, mixlm, mplot
DoE.wrapper, EasyABC, GPfit, hydroPSO, metagen
cds, geospt, geosptdb, networkTomography, pi0, restlos, walkr
blmeco, climwin, clusterPower, effects, ez, inferference, LMERConvenienceFunctions, lmSupport, mbest, mediation, metaplus, miceadds, mixlm, MixMAP, mlVAR, multiDimBio, MultiRR, R2STATS, refund, rockchalk, RVAideMemoire, RVFam, SensMixed, SoyNAM, spacom, Surrogate, xergm
AutoModel, betareg, chipPCR, clusterSEs, dynlm, earlywarnings, fRegression, gcmr, georob, glmx, mlogit, mnlogit, rddtools, termstrc, treeclim, vcd
CoImp, hdrcde, KATforDCEMRI, kdecopula, LICORS, paleofire
bmrm, Compind, ergm, label.switching, limSolve, matchingMarkets, mediation, netgen, QCA, sampling, systemicrisk
aemo, alm, aoristic, APSIM, apsimr, Biograph, clifro, climwin, cruts, dataRetrieval, decctools, ecoengine, EGRET, EGRETci, iki.dataclim, OptiQuantR, pdfetch, plusser, primerTree, RefManageR, rgauges, rnoaa, rplexos, rplos, SensusR, SpaDES, spocc, ss3sim, sweidnumbr, TTAinterfaceTrendAnalysis, USAboundaries, vetools, Wats
bgeva, GMMBoost, list, netmeta, refund, rlme, SemiParBIVProbit, SemiParSampleSel
datastepr, dendextend, dotenv, dplyr, dpmr, DT, dygraphs, emil, evolqg, FeatureHashing, fulltext, genderizeR, geojsonio, ggvis, gistr, gmailr, Gmisc, hpoPlot, htmlTable, HydeNet, igraph, IsingSampler, latex2exp, lawn, leaflet, loopr, metricsgraphics, NNTbiomarker, pixiedust, prettyunits, pRF, rdrop2, RevEcoR, rex, rgbif, rhandsontable, rvest, SciencesPo, searchable, sjPlot, spark, stcm, stringr, taber, visNetwork, xgboost
ggmap, openair, pavo, perspectev, rbison, s2dverification
bdvis, etasFLP, OIdata, r4ss, rinat, rvertnet, SpatialExtremes, SpatialVx, swfscMisc
aoristic, BayesX, capm, dynatopmodel, ecospat, eeptools, EMbC, geojsonio, ggsn, letsR, lgcp, MapGAM, MetaLandSim, opentraj, pgirmess, plotGoogleMaps, prevR, rangeMapper, rAvis, rworldmap, secrlinear, SpatialEpi, speciesgeocodeR, SSN, SWMPr, trip, USAboundaries, vdmR, vetools, vmsbase
BEQI2, confidence, datamart, DVHmetrics, Kmisc, knitr, knitrBootstrap, leaflet, mirtCAT, radiant, rite, shinystan
cwm, expands, KATforDCEMRI, markovchain, NPC, perARMA, rcicr, rwt
afex, AICcmodavg, apcluster, BinOrdNonNor, biom, btergm, btf, BTYD, cape, ChainLadder, coalescentMCMC, CollocInfer, comato, CompareCausalNetworks, copula, CorReg, coxinterval, coxme, CRF, Crossover, ctmm, ctsem, DESP, diffusionMap, discSurv, dmt, dnet, DNMF, doBy, dplR, EFDR, ergm, eRm, evolqg, expoRkit, ez, FDboost, FeatureHashing, GENLIB, gMCP, gnm, goric, graphicalVAR, gRbase, growfunctions, hbm, hbsae, hierarchicalDS, hisemi, HLMdiag, igraph, influence.ME, INLABMA, irlba, IsingFit, kknn, lavaan.survey, lgcp, LICORS, LMERConvenienceFunctions, lpbrim, ltmle, marked, markovchain, MatrixModels, mboost, medflex, metagear, metaMix, metaSEM, mgcv, midasr, mistral, mme, Morpho, moult, multibiplotGUI, multimark, MuMIn, netClass, nettools, neuroim, NORTARA, optBiomarker, optismixture, ordinal, pbkrtest, PEIP, perARMA, PerFit, pez, phangorn, phia, pi0, polywog, popgraph, pvclass, qgraph, qrjoint, quanteda, quantreg, R2MLwiN, rARPACK, RcppEigen, refund, RevEcoR, rmgarch, robustreg, rodd, RSiena, rsig, RVFam, scam, SCGLR, scidb, ScreenClean, SemiParSampleSel, seqMeta, SID, simcausal, sirt, smart, smint, SMNCensReg, spacom, spaMM, spatstat, spatsurv, sphet, splm, stm, stocc, strum, superbiclust, surveillance, SwarmSVM, synlik, threeboost, tmle.npvi, tsDyn, umx, varComp, VCA, xergm, xgboost, XMRF
backShift, BEDASSLE, discSurv, geesmv, ICsurv, MarkowitzR, matrixpls, PCDSpline, qrLMM, qrNLMM, RMark, rodd, sem, SharpeR
ACNE, aroma.affymetrix, aroma.cn, aroma.core, bdynsys, bingat, bnclassify, calmate, dplR, fslr, loo, Luminescence, MFHD, mmtfa, PSCBS, randomizationInference, statar, stm, WGCNA
DirichletReg, HiDimMaxStable, paramlink, rDEA, splm
apaTables, lessR, miceadds, replicationInterval, userfriendlyscience
bujar, DIFboost, gamboostMSM, imputeR, SurvRank
BANFF, Bchron, chemometrics, clustMD, CorReg, expands, flexCWM, fpc, msir, optCluster, semiArtificial, TipDatingBeast, VBLPCM, vscc
BayesLCA, BayesSingleSub, coarseDataTools, fdrDiscreteNull, HWEBayes, NSUM, PANICr, refund, sparsereg, spikeSlabGAM
MAVIS, metagear, metagen, NSM3, RcmdrPlugin.MA, reproducer
AdaptFitOS, analogue, apsimr, car, cSFM, demography, discSurv, drsmooth, DSpat, ez, FDboost, fRegression, funreg, FWDselect, gamclass, groc, gsg, Haplin, HLMdiag, landsat, LMERConvenienceFunctions, mirt, mrds, openair, palaeoSig, pitchRx, QRM, QuasiSeq, RcmdrPlugin.HH, refund, reldist, rioja, rlme, RLRsim, rstpm2, secr, SEERaBomb, sesem, simPH, slp, snht, spatstat, spsmooth, StatDA, tripEstimation, tsDyn, vegan, vows, WhiteStripe, zetadiv
gmailr, httr, markdown, RSocrata, servr, shiny
DBKGrad, FatTailsR, FME, Luminescence, Rquake, TIMP
cplm, geosptdb, glmmLasso, GMMBoost, GxM, lme4, optimx
feature, multiDimBio, NPCirc, plot3D, prim
censReg, frontier, LOST, micEcon, micEconAids, micEconCES, micEconSNQP, mvProbit, sampleSelection, yhat
BayesCR, bayou, cSFM, dma, EasyABC, EMbC, FADA, flexCWM, HiDimMaxStable, lavaan, mixAK, phytools, pmcgd, psych, SIBER, sn, tsDyn, VBmix
betareg, coin, dtwclust, eaf, flexmix, PSAboot, psychomix, topicmodels
BrailleR, cSFM, expands, frontier, MVN, nullabor, PDQutils, qat, royston, semsfa, sisus
Biograph, breakpoint, CIDnetworks, clustMD, decisionSupport, gems, gmnl, httk, iBATCGH, optBiomarker, parfm, phytools, Rchoice, RMark, rriskDistributions, rtdists, sparsereg, TAM
ANOM, cg, coin, Crossover, Deducer, dpcR, drc, drsmooth, gMCP, lsmeans, MCPAN, mutoss, rms, sensR, SimComp, TTAinterfaceTrendAnalysis
asbio, BayesComm, BayesCR, BayesFactor, BayesSingleSub, bayesTFR, bcpmeta, bindata, binMto, BinOrdNonNor, BMhyd, boolean3, boral, BSagri, CALIBERrfimpute, CCTpack, CDVine, CIDnetworks, clinfun, clusteval, clustMD, coin, conting, cope, copula, copulaedas, CorrBin, CorReg, CosmoPhotoz, csn, decisionSupport, DescTools, DFIT, discSurv, drsmooth, ETC, evolqg, FastGP, flexsurv, fMultivar, fpc, freestats, fungible, funreg, geiger, gMCP, goric, graphicalVAR, growfunctions, gsg, hierarchicalDS, hmmm, HWEBayes, hyperdirichlet, ic.infer, ifa, intamap, interAdapt, latentnet, LICORS, LINselect, list, lsmeans, MARSS, matie, maxstat, MCPAN, mcprofile, Mediana, merTools, MESS, miceadds, mistral, MixGHD, mratios, MSBVAR, msm, MTS, multicon, multimark, MultiMeta, multivator, nonnest2, OPDOE, optismixture, pcaPP, pez, plsRbeta, plsRglm, pomp, PopED, PowerTOST, protiq, qrLMM, qrNLMM, random.polychor.pa, rase, RobustEM, rpf, rrcov, SimComp, simexaft, sirt, SmoothHazard, sns, sortinghat, sparsediscrim, SparseTSCGM, spikeSlabGAM, SQDA, supcluster, TAM, tglm, timeROC, tsbridge, umx, uniReg, varComp, VineCopula
cruts, lgcp, marmap, meteoForecast, rerddap
BANFF, bingat, btergm, degreenet, EpiModel, intergraph, sidier, SparseTSCGM, xergm
agricolae, AICcmodavg, ape, arm, BayesLCA, caret, cem, cg, CLME, coxme, cplm, dlnm, dsm, easyanova, eba, FindMinIC, gcmr, geesmv, georob, GxM, investr, lme4, lmms, lqmm, lsmeans, lucid, MARSS, MultiSV, nlmeU, OPDOE, plm, PopED, psychometric, rareGE, refund, rlme, rms, robustlmm, secr, SemiPar, SMPracticals, spacom, spaMM, spdep, sphet, splm, Surrogate, tergm, TTAinterfaceTrendAnalysis, urca, varComp, vcrpart
NLPutils, openNLP, qdap, syuzhet, textreg, tm.plugin.alceste, tm.plugin.dc, tm.plugin.europresse, tm.plugin.factiva, tm.plugin.lexisnexis, tm.plugin.mail, tm.plugin.webmining
BaBooN, BayesTree, biomod2, car, chemometrics, CoImp, DAMisc, EffectLiteR, effects, EnsembleBase, flexmix, forecast, fRegression, gnm, Hmisc, hybridEnsemble, ipred, ipw, IsingSampler, mice, mlearning, NeuralNetTools, oblique.tree, pvsR, rasclass, RcmdrPlugin.BCA, RecordLinkage, rminer, RTextTools, RVAideMemoire, semiArtificial, simPop, spectral.methods, spls, tsDyn, VIM
Anthropometry, hybridEnsemble, isotone, mboost, phangorn, rNMF, smacof, TIMP
AID, BrailleR, earlywarnings, momr, moonBook, MVN, myTAI, NSM3, royston, SixSigma
antitrust, bbmle, BinaryEPPM, BMhyd, boolean3, CIDnetworks, condGEE, corHMM, CountsEPPM, ctmm, discSurv, DoubleExpSeq, ExtDist, FDGcopulas, finiteruinprob, flexCWM, GB2, geostatsp, GPvam, gsg, HAC, inferference, kergp, lava, marked, markophylo, metaplus, metRology, mets, midasr, mirt, MixGHD, mpath, MPTinR, mrds, nlWaldTest, optimx, OUwie, phytools, pi0, pssm, Rcgmin, RealVAMS, Renext, robustvarComp, rodd, rstpm2, rugarch, sdprisk, sensR, sn, sns, StableEstim, stochprofML, timereg, TKF, umx, VCA, vcrpart
BioGeoBEARS, boolean3, CatDyn, ExtDist, invGauss, marked, mrds, rankdist, Synth
dti, gdimap, oro.dicom, oro.pet, RNiftyReg, vows, WhiteStripe
EcoGenetics, multilevelPSA, PSAboot, rminer, synthpop
activity, BayesFactor, caretEnsemble, cdcfluview, longurl, warbleR
afex, ARTool, car, lmSupport, predictmeans
chemometrics, CosmoPhotoz, ftsa, lcopula, OutlierDM, rmgarch, rrcov, rrcovHD, smart, sprm
mmod, PopGenReport, poppr, readGenalex, strataG
bipartite, cwm, expands, NPC, pRF, RAM, randomizationInference, rankdist, VdgRsm
coalescentMCMC, CommT, corHMM, markophylo, OUwie, paleotree, phytools, poppr, RADami, RAM, recluster, SeqFeatR, timetree, TKF
BMhyd, evolqg, geomorph, hisse, monogeneaGM, OUwie, phylocurve, RAM, rase, recluster, Rphylopars, TKF
betapart, DAMOCLES, lefse, nodiv, PCPS, pez, recluster
asbio, plotKML, shapeR, sparkTable, VBmix
ABCanalysis, aqp, asbio, bdvis, BioGeoBEARS, cncaGUI, convoSPAT, coreNLP, drc, gmnl, HTSCluster, JBTools, KernSmoothIRT, kineticF, LogicForest, marmap, mutoss, ncdf.tools, NPCirc, PCPS, phonR, phytools, plotKML, plotSEMM, PReMiuM, qdap, Rchoice, rminer, SimReg, vmsbase, xhmmScripts, yhat
chemometrics, EasyABC, enpls, groc, imputeR, LINselect, miceadds, plsRcox, resemble, rminer, robCompositions, rrcovHD, RVAideMemoire, soil.spec, spls
colourlovers, d3heatmap, dplR, ggmap, ggsn, HiveR, imguR, iplots, leaflet, loa, qgraph, rAltmetric, rcdk, readbitmap, retistruct, RgoogleMaps, StereoMorph, zooimage
AssetPricing, hwwntest, iterpc, OPDOE, partitions, smacof, tsoutliers, untb
bdynsys, dpcR, GUILDS, IRISMustangMetrics, IRISSeismic, PEIP, QuasiSeq, soundecology
biomod2, FAMILY, LogisticDx, mlDNA, randomUniformForest, SCGLR
ipred, ModelGood, pec, riskRegression, SmoothHazard
coefplot, DTR, ggmap, ggplot2, ggsubplot, ggtern, ggthemes, Hmisc, multilevelPSA, statar, synthpop
cccd, HighDimOut, LDAvis, quanteda, spaMM, vdg
broom, CCTpack, CDM, CorrMixed, CTTShiny, likert, lmSupport, manifestoR, matrixpls, multilevelPSA, MVN, OpenRepGrid, PSAboot, qgraph, qmethod, qrLMM, qrNLMM, radiant, sdmvspecies, sirt, sjPlot, TAM, traj, TriMatch, userfriendlyscience
bootnet, diveRsity, graphicalVAR, IATscores, IsingFit, mlVAR, semPlot, sirt
BB, chemosensors, dti, earlywarnings, expectreg, FinCovRegularization, fPortfolio, GENLIB, goric, gromovlab, hmmm, hybridEnsemble, ic.infer, lavaan, limSolve, list, mboost, mcprofile, nodeHarvest, npbr, npsp, orderedLasso, parma, penDvine, phangorn, pi0, rodd, ROI.plugin.quadprog, ScreenClean, simPH, tseries, uniReg, varComp
creditr, DMwR, tawny, tawny.types, TSmisc
apTreeshape, car, chipPCR, cobs, crs, diveMove, georob, MAVIS, NCA, NSM3, OutlierDM, pez, qrLMM, qrNLMM, quantspec, rlme, rms, RPPanalyzer, SGP, sitar
agRee, bamdit, boral, classify, SeqFeatR
bigrquery, choroplethr, coala, datastepr, data.tree, distcomp, dplyr, googleAuthR, httr, loopr, progress, PythonInR, RDML, shiny, shopifyr, simcausal, vmsbase
constrainedKriging, geoR, georob, lgcp, SpaDES, spatsurv
abcrf, aCRM, aLFQ, bagRboostR, biomod2, CALIBERrfimpute, cem, ecospat, EnsembleBase, FSelector, gamclass, hybridEnsemble, kernelFactory, LINselect, mice, mlearning, NAM, nodeHarvest, optBiomarker, OTE, pRF, rasclass, RFmarkerDetector, rminer, RTextTools, SPOT, stcm, VSURF
bfast, birdring, clhs, cruts, ctmm, EcoGenetics, ecospat, graticule, GSIF, hddtools, ipdw, lakemorpho, leaflet, lgcp, Luminescence, marmap, memgene, MetaLandSim, meteo, mkde, ncdf.tools, nodiv, opentraj, paleofire, plotGoogleMaps, plotKML, rangeMapper, rAvis, rLiDAR, rSPACE, sdmvspecies, secr, SpaDES, spatialEco, spatsurv, speciesgeocodeR, spectral.methods, tmap, trip, wrspathrow
aroma.affymetrix, aroma.cn, aroma.core, fulltext, PSCBS, repmis, R.filesets, R.rsp, scholar
betapart, CausalFX, hitandrun, pavo, sisus
BCA, BiodiversityR, learnstats, RcmdrPlugin.DoE, RcmdrPlugin.EACSPIR, RcmdrPlugin.EZR, RcmdrPlugin.FactoMineR, RcmdrPlugin.HH, RcmdrPlugin.IPSUR, RcmdrPlugin.KMggplot2, 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, chemosensors, clifro, edgar, EMbC, EpiModel, fheatmap, granovaGG, HH, HiveR, leaflet, LICORS, loa, LogisticDx, lpbrim, LPStimeSeries, mapStats, micromapST, MKmisc, msarc, MSG, mstate, multiDimBio, MultiPhen, mvcwt, mvtboost, myTAI, ncdf.tools, NMF, openair, OutbreakTools, pcaBootPlot, PharmacoGx, pheatmap, plotKML, pqantimalarials, psd, PubMedWordcloud, quantable, rafalib, RAM, rangeMapper, rasterVis, rbefdata, RcmdrPlugin.KMggplot2, RcmdrPlugin.temis, reproducer, RNCEP, RobLox, RobLoxBioC, RSA, scales, sharpshootR, SigTree, sisus, smoof, solaR, SOMbrero, sorvi, spatsurv, spectral.methods, spoccutils, statnetWeb, SWMPr, tagcloud, tdr, tmap, TraMineR, treemap, TROM, waffle, Wats, WeightedCluster, xseq
archivist, atsd, AzureML, bigml, biomartr, blsAPI, Causata, clifro, creditr, dams, datamart, dataRetrieval, decctools, demography, devtools, dvn, Ecfun, FedData, federalregister, FinCal, gfcanalysis, gProfileR, GuardianR, h2o, hddtools, HierO, imguR, interAdapt, IRISMustangMetrics, IRISSeismic, MODISTools, MTurkR, neotoma, ngramr, nhlscrapr, OAIHarvester, Ohmage, OIdata, OpasnetUtils, OutbreakTools, paleobioDB, plusser, polidata, pubmed.mineR, PubMedWordcloud, qdap, qdapTools, r4ss, RAdwords, rainfreq, rAltmetric, rAvis, rbefdata, RbioRXN, Rbitcoin, rClinicalCodes, RCryptsy, rdatamarket, rdryad, rDVR, recalls, RefManageR, Reol, retrosheet, reutils, rglobi, rite, RKlout, RLumShiny, Rmonkey, rNOMADS, rnrfa, ROAuth, RProtoBuf, rpubchem, RPublica, rsdmx, rsnps, rtematres, rYoutheria, scidb, SocialMediaMineR, soilDB, spatialEco, stringgaussnet, swirl, taRifx.geo, Thinknum, tm.plugin.webmining, TR8, translate, translateR, treebase, umx, W3CMarkupValidator, warbleR, webchem, wikipediatrend, XML2R, yhatr
hybridEnsemble, mmand, RNiftyReg, soma, tractor.base
alm, aqp, arqas, automap, benchmark, Biograph, bold, climwin, CommT, contoureR, denovolyzeR, dynsurv, ezsim, GGally, intsvy, kobe, likert, Methplot, MissingDataGUI, multilevelPSA, MultiSV, opentraj, PopGenReport, rags2ridges, RAM, rapport, simTool, snht, spikeSlabGAM, SurvRank, timeSeq, TTAinterfaceTrendAnalysis, WGCNA, WRS2
adegenet, agridat, aLFQ, algstat, alm, aoristic, AppliedPredictiveModeling, apsimr, backShift, BBEST, BEQI2, bmmix, brms, capm, caret, cda, ChainLadder, classify, clhs, clifro, clusterfly, coefplot, cooccur, cplm, Cubist, cutoffR, dataRetrieval, data.table, dcmr, decctools, DescribeDisplay, dtwclust, DVHmetrics, EasyHTMLReport, EcoGenetics, EEM, EpiDynamics, evolqg, ez, fheatmap, FinCal, flows, fSRM, G2Sd, ggenealogy, ggmap, ggparallel, ggplot2, ggRandomForests, ggtern, granovaGG, growcurves, growfunctions, hazus, HH, HLMdiag, IATscores, imputeR, jaatha, laketemps, lmms, lsbclust, lsl, mapStats, marmap, medicalrisk, mizer, mlr, Mobilize, mosaic, MultiMeta, myTAI, ncappc, neotoma, networkreporting, NeuralNetTools, ngramr, NMF, oaxaca, OpasnetUtils, openair, orderedLasso, OutbreakTools, pdfetch, planar, PlotPrjNetworks, poppr, PPtreeViz, pqantimalarials, pRF, proteomics, PSAboot, pscore, qdap, qgraph, quadrupen, rAltmetric, RAM, RCMIP5, RDS, repra, rgauges, rivr, RNeXML, rplos, rWBclimate, rYoutheria, SEERaBomb, SensMixed, SGP, sharpshootR, shinystan, simcausal, simmr, simPH, SimReg, SixSigma, sorvi, SoyNAM, sprm, ss3sim, StMoMo, strataG, structSSI, SWMPr, taRifx, taxize, TcGSA, tidyr, timeseriesdb, timma, treebase, TripleR, TSMining, tvm, vardpoor, wppExplorer, wq, YourCast
aoristic, birdring, capm, ctmm, dynatopmodel, EcoGenetics, geojsonio, geotopbricks, gfcanalysis, GSIF, hddtools, lakemorpho, landsat8, letsR, MazamaSpatialUtils, meteo, OasisR, OpasnetUtils, opentraj, paleofire, pgirmess, plotGoogleMaps, plotKML, PopGenReport, rAvis, rnoaa, rnrfa, rWBclimate, sperich, taRifx.geo, tmap, tripEstimation, wrspathrow, wux
birdring, constrainedKriging, DSpat, dynatopmodel, FedData, geojsonio, GeoXp, gfcanalysis, hierarchicalDS, lakemorpho, lgcp, MazamaSpatialUtils, MetaLandSim, OasisR, pgirmess, rangeMapper, RSurvey, spatialEco, spatsurv, spsurvey, taRifx.geo, tmap, USAboundaries, wildlifeDI, wrspathrow, wux
anacor, analogueExtra, Anthropometry, biplotbootGUI, ChemoSpec, clusterSim, cncaGUI, COMMUNAL, crs, emdbook, feature, forestFloor, GrammR, homals, HUM, KernSmoothIRT, labdsv, lfda, LMERConvenienceFunctions, Luminescence, mixOmics, monogeneaGM, Morpho, multibiplotGUI, nanop, NPCirc, OceanView, OpenRepGrid, pca3d, pi0, prim, rase, restlos, retistruct, rLiDAR, RnavGraph, RockFab, Rquake, rsml, SDD, shapes, shinyRGL, sparr, spatsurv, SPOT, StatDA, Surrogate, symbolicDA, termstrc, vegan3d
CRF, fPortfolio, HotDeckImputation, MCDA, networkTomography, npbr, parma, ROI.plugin.glpk
bayesDem, CITAN, clusterfly, GrammR, PKgraph, playwith, rggobi, RQDA, Rz, strvalidator, VIMGUI, WMCapacity, x12GUI
bamdit, bayescount, bayesmix, BTSPAS, CCTpack, EasyMARK, jagsUI, SIBER, StatMethRank
BACA, boilerpipeR, coreNLP, Deducer, DeducerExtras, expands, G2Sd, hive, llama, mailR, mpoly, mutossGUI, Myrrix, Myrrixjars, openNLP, openNLPdata, OpenStreetMap, rcdk, ReporteRs, ReporteRsjars, RFreak, RKEA, RKEAjars, RMOAjars, RWeka, RWekajars, RxnSim, TSsdmx, wordnet, XLConnect, XLConnectJars
AntWeb, aop, argparse, AzureML, BerlinData, blsAPI, Causata, d3Network, db.r, geonames, GetoptLong, ggmap, h2o, helsinki, james.analysis, mpoly, networkD3, ngramr, nhlscrapr, OpasnetUtils, OutbreakTools, paleobioDB, RAdwords, rbefdata, rClinicalCodes, rfisheries, rglobi, RIGHT, rnrfa, solr, sotkanet, StereoMorph, stmBrowser, structSSI, twitteR, vdmR, visNetwork, warbleR, yhatr
bigml, biom, colourlovers, datamart, FAOSTAT, federalregister, fitbitScraper, googleVis, gridSVG, GuardianR, knockoff, LDAvis, neotoma, Ohmage, plusser, pxweb, rAltmetric, Rbitcoin, RCryptsy, rdatamarket, rdryad, recalls, RedditExtractoR, RefManageR, rfigshare, RgoogleMaps, rpubchem, RPushbullet, rYoutheria, shinyFiles, shopifyr, stringgaussnet, switchrGist, tabplotd3, taRifx.geo, Thinknum, timeseriesdb, tm.plugin.webmining, translate, translateR, WaterML
BrailleR, caRpools, gistr, liftr, rchallenge
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, tmle.npvi
bujar, Daim, ecospat, greport, haplo.stats, hdnom, lodGWAS, LogisticDx, mztwinreg, pec, plsRcox, PResiduals, riskRegression, shrink, spatialEco, SvyNom, VizOR
CerioliOutlierDetection, chemometrics, chipPCR, complmrob, cvTools, ergm, fAssets, fpc, fPortfolio, georob, GeoXp, groc, MKmisc, MVN, mvoutlier, pcalg, rlme, robustlmm, robustloggamma, robustvarComp, sdcMicro, shotGroups, StatDA, tergm, VIM
aLFQ, AutoModel, btergm, DMwR, EMP, hybridEnsemble, lulcc, mlDNA, MXM, netClass, OmicKriging, RFmarkerDetector, xergm
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, condGEE, fbati, nettools, RadTran, rodd, sdprisk, StMoMo
BCA, biomod2, bnclassify, bst, CORElearn, CorReg, DMwR, gamclass, Harvest.Tree, Hmisc, hybridEnsemble, imputeR, ipred, MergeGUI, mice, PSAboot, RcmdrPlugin.BCA, RecordLinkage, rminer, rms, rotationForest, SPOT, supclust, survMisc, SurvRank, synthpop, vcrpart, VSURF
GEOmap, geophys, ProfessR, RFOC, Rquake, RSEIS, RTOMO
ACDm, clickstream, fPortfolio, mrds, rmgarch, rugarch, TBSSurvival
BatchExperiments, BatchJobs, db.r, marmap, poplite, rplexos, SciencesPo, SGP, smnet, sqliter, TSSQLite, UPMASK, vmsbase
ACNE, aroma.apd, Causata, demi, dplR, edgar, EEM, fslr, gdalUtils, hoardeR, mailR, MPAgenomics, PopGenReport, PSCBS, qrcode, R.cache, R.devices, R.filesets, R.huge, R.matlab, R.rsp, SDMTools, snplist, SpaDES, TBSSurvival
bayesPop, birdring, SensusR, spoccutils, virtualspecies, wux
Frames2, popgraph, RRTCS, Sofi, SurvRank
betareg, censReg, clusterSEs, fxregime, gcmr, glmx, glogis, MarkowitzR, maxLik, medflex, multcomp, multiwayvcov, nonnest2, party, plm, rddtools, systemfit, termstrc, vcrpart
aqp, backtestGraphics, bdscale, benchmark, choroplethr, clhs, clifro, coefplot, complmrob, d3heatmap, Deducer, DescribeDisplay, drc, EasyHTMLReport, EpiBayes, ez, FAOSTAT, FinCal, fslr, fSRM, ggmap, ggplot2, ggsubplot, ggtern, ggthemes, GraphPCA, growcurves, growfunctions, Hmisc, leaflet, ncappc, NeuralNetTools, ngramr, optiRum, OutbreakTools, paleobioDB, pheatmap, plotKML, primerTree, qdap, quadrupen, quantable, RAM, rAvis, RcmdrPlugin.KMggplot2, RDS, rgauges, rnoaa, SciencesPo, sharpshootR, sjPlot, soc.ca, spikeSlabGAM, strvalidator, useful, vetools
anacor, arulesViz, asbio, caRpools, diffusionMap, FactoMineR, fractal, FrF2, GraphPCA, homals, PharmPow, phytools, pi0, RSDA, shapes, SOMbrero, vegan3d
lefse, NORRRM, raincpc, rainfreq, spatialEco, sperich
adegenet, aLFQ, apmsWAPP, caRpools, gkmSVM, gquad, megaptera, signalHsmm
CDM, Demerelate, distrMod, FrF2, lokern, mcmcplots, mirt, pcalg, random.polychor.pa, ReliabilityTheory, simsalapar, sirt, TAM, xseq
cape, circlize, diffEq, dynatopmodel, EpiBayes, Luminescence, marmap, NPCirc, OceanView, plspm, RBPcurve, rmgarch, vows
Anthropometry, biplotbootGUI, cncaGUI, LOST, Momocs, multibiplotGUI, provenance, symbolicDA
adegenet, backtestGraphics, BBEST, capm, chipPCR, cosinor, CosmoPhotoz, CTTShiny, datacheck, distcomp, diveRsity, dpcR, dropR, DVHmetrics, EffectLiteR, flora, G2Sd, ggvis, HH, interAdapt, IRTShiny, learnstats, MAVIS, merTools, mldr, mlr, mplot, mwaved, NNTbiomarker, pairsD3, plotROC, poppr, pqantimalarials, questionr, radiant, rgpui, RIGHT, RLumShiny, rtable, SDR, SensMixed, shinyAce, shinybootstrap2, shinyBS, shinydashboard, shinyFiles, shinyjs, shinyRGL, shinythemes, shinyTree, signalHsmm, SOMbrero, StereoMorph, timeseriesdb, treemap, wppExplorer
biosignalEMG, chipPCR, dpcR, IRISMustangMetrics, IRISSeismic, perARMA, psd, tuneR
fPortfolio, lpmodeler, movMF, parma, rDEA, relations, ROI, ROI.plugin.quadprog, ROI.plugin.symphony, skmeans, stm, textcat, tm, tm.plugin.dc, topicmodels, wordcloud
caRpools, DAMisc, DepthProc, rase, SDD, sirt
btergm, latentnet, OutbreakTools, qgraph, statnetWeb, xergm
georob, meteo, quantspec, rags2ridges, XMRF
adegraphics, aoristic, aqp, BayesX, bfast, birdring, capm, CARBayes, CARBayesdata, clhs, cruts, csrplus, ctmm, DSpat, dynatopmodel, EcoGenetics, EEM, EFDR, EMbC, flows, gcmr, gdalUtils, gdistance, geoBayes, geojsonio, geoR, geoRglm, gfcanalysis, ggtern, GSIF, gstat, GWLelast, hddtools, helsinki, hydroPSO, hydroTSM, ipdw, kineticF, lakemorpho, landsat8, leaflet, letsR, lgcp, mapStats, marmap, MazamaSpatialUtils, meteo, mkde, Momocs, nodiv, OpasnetUtils, opentraj, perspectev, pgirmess, plotKML, PopGenReport, popgraph, r2d2, rangeMapper, rasterVis, rAvis, rbison, redist, repijson, retistruct, rgeos, rLiDAR, RNCEP, rnrfa, RObsDat, rSPACE, RSurvey, rWBclimate, secr, SensusR, sharpshootR, soilDB, soil.spec, soiltexture, spacetime, SpaDES, spatialEco, SpatialPosition, spatsurv, spcosa, speciesgeocodeR, sperich, sphet, spoccutils, spsann, spTimer, taRifx.geo, tmap, trajectories, tripEstimation, USAboundaries, VIM, vmsbase, VTrack, wildlifeDI, wkb, wrspathrow
gstat, meteo, plotKML, RObsDat, trajectories, VTrack
CARBayes, CARBayesST, CollocInfer, dynatopmodel, earlywarnings, growfunctions, nat.nblast, splm
baseline, cobs, DESP, expoRkit, pawacc, RItools, SwarmSVM
ads, dpcR, ecospat, hht, highriskzone, intamapInteractive, lgcp, polyCub, rase, replicatedpp2w, RImageJROI, rLiDAR, smacpod, spatialEco, spatsurv, surveillance, swfscMisc, trip
adegenet, agricolae, CARBayes, INLABMA, Momocs, OasisR, pgirmess, redist, saeSim, spacom, spatialEco, SpatialEpi, spfrontier, sphet
ExceedanceTools, GEOmap, geoR, GeoXp, kineticF, pgirmess, phonR, PrevMap, RCALI, RFOC, RTOMO, seg, tspmeta
Bclim, cda, ChainLadder, cplm, dsm, equateIRT, flexCWM, hoa, LogisticDx, mlogit, multimark, mvabund, npmlreg, PanelCount, pglm, planar, R2STATS, RVAideMemoire, x.ent
btergm, ndtv, networkDynamic, statnet, xergm
CITAN, dplR, Ecfun, mapDK, PGRdup, qdapRegex, quanteda, RcmdrPlugin.temis, retrosheet, rplexos, rprime, searchable, SpaDES, stringr, tidyr
acs, aemo, afex, algstat, alm, APSIM, aqp, BatchJobs, BayesFactor, beepr, BerlinData, betalink, biomartr, bold, boostr, boxr, broom, Causata, choroplethr, CLME, commentr, COPASutils, cruts, cymruservices, datacheck, db.r, decctools, detector, DiagrammeR, distcomp, docopt, dotwhisker, dplR, EasyMARK, eeptools, evaluate, ez, fbRanks, fitbitScraper, fungible, games, genderizeR, GERGM, gfcanalysis, GGally, ggsubplot, googlesheets, gsheet, HistogramTools, hoardeR, htmlTable, httr, HydeNet, IATscores, io, IRISMustangMetrics, IRISSeismic, ISOweek, knitr, latex2exp, liftr, lint, lubridate, mailR, managelocalrepo, markophylo, MazamaSpatialUtils, metagear, muir, netgen, networkreporting, neuroim, ngramr, nhanesA, nlWaldTest, NMF, NNTbiomarker, OpenRepGrid, optiRum, P2C2M, pathological, pkgmaker, plotKML, polywog, primerTree, profr, pryr, PubMedWordcloud, pxweb, qrcode, rAvis, RbioRXN, RBitly, rClinicalCodes, RcppOctave, rdryad, redcapAPI, RefManageR, reportRx, reshape2, RevEcoR, rlme, rngtools, rNOMADS, rnrfa, roxygen2, rprime, rprintf, RSiteCatalyst, rsnps, rsunlight, rUnemploymentData, scholar, SciencesPo, searchConsoleR, selectr, simcausal, simPH, SpaDES, spanr, spatsurv, sqliter, srd, Stack, statar, stm, surveydata, sweidnumbr, swirl, taxize, TcGSA, translateSPSS2R, tspmeta, ucbthesis, vetools, vows, wikipediatrend, wux, x12, x12GUI, x.ent, xgboost, yhatr
GWRM, Haplin, NSM3, PHENIX, userfriendlyscience
capm, EffectLiteR, GB2, rareGE, SemiParBIVProbit, sirt, SvyNom, tab, tableone
addhazard, aftgee, AIM, binequality, Biograph, c060, cg, compareGroups, controlTest, coxphf, CP, DStree, DTR, EGRET, EMA, epoc, FHtest, fitdistrplus, gamlss, ggRandomForests, greport, hdnom, hoa, ilc, ipred, ipw, landpred, lodGWAS, mboost, Mediana, mets, MIICD, mixPHM, mlr, mombf, moonBook, msm, MST, muhaz, MXM, party, partykit, pec, plsRcox, pmml, powerSurvEpi, prodlim, rankhazard, RcmdrPlugin.KMggplot2, reportRx, riskRegression, RVFam, sensitivityPStrat, shrink, simexaft, simPH, smcfcs, SMPracticals, spanr, spatsurv, spBayesSurv, srd, SSRMST, Surrogate, SurvCorr, SvyNom, tab, TBSSurvival, WCE, WGCNA, xpose4
svHttp, svIDE, svSocket, svTools, svWidgets
ChainLadder, erer, micEconAids, micEconCES, micEconSNQP, sampleSelection
biplotbootGUI, cncaGUI, dynBiplotGUI, fSRM, HierO, multibiplotGUI, Rcmdr, RcmdrPlugin.KMggplot2, RcmdrPlugin.sos, RcmdrPlugin.temis, rite, rSPACE, stylo, TTAinterfaceTrendAnalysis
Ecfun, geospt, hwriterPlus, palaeoSig, RBPcurve
growcurves, lintr, ncappc, SixSigma, swirl, testthatsomemore
dse, EvalEst, TScompare, TSdbi, tsfa, TSfame, TSmisc, TSMySQL, TSodbc, TSPostgreSQL, TSsdmx, TSsql, TSSQLite
TSfame, TSmisc, TSodbc, TSPostgreSQL, TSsdmx, TSsql, TSSQLite
broom, EFDR, emil, eurostat, evolqg, googlesheets, pixiedust, pmc, qdap, radiant, RDML, rfishbase, rnoaa, rplexos, rtable, sjPlot, statar, SWMPr, translateSPSS2R
BLCOP, FatTailsR, GEVStableGarch, semiArtificial, tframePlus, TTAinterfaceTrendAnalysis
asbio, biplotbootGUI, cncaGUI, dynBiplotGUI, Interatrix, MareyMap, multibiplotGUI, rriskDistributions
edgar, fulltext, genderizeR, PubMedWordcloud, qdap, rClinicalCodes, reproducer, RKEA, RTextTools, textreg, tm.plugin.alceste, tm.plugin.europresse, tm.plugin.factiva, tm.plugin.lexisnexis, tm.plugin.mail, tm.plugin.webmining, topicmodels
clustMD, copulaedas, gmnl, hierarchicalDS, marked, parma, PrevMap, rDEA, SparseFactorAnalysis, stocc, tglm
AID, conting, egcm, erer, forecast, lfl, partialAR, PCA4TS, SDD, tsDyn, TSmisc
apt, autovarCore, CommonTrend, egcm, erer, partialAR, termstrc, tsDyn
daff, geojsonio, js, lawn, minimist, rgbif, rjade, spocc
arulesViz, DoE.base, gpairs, HH, pcalg, SciencesPo, sdcMicroGUI, STEPCAM, TIMP, VIM
cati, Demerelate, evolqg, forams, lefse, memgene, metacom, nodiv, paco, pez, PopGenReport, poppr, provenance, rioja, RVAideMemoire, shapeR, sharpshootR, soundecology, tspmeta, xergm, zetadiv
AICcmodavg, cg, ExomeDepth, HiDimMaxStable, list, lllcrc, MXM, poweRlaw, sads, SemiParBIVProbit, SemiParSampleSel, smcfcs, SparseFactorAnalysis, sparsereg, staTools
d3Network, dendextend, devtools, ecoengine, flowr, fulltext, rgbif, rplos, spocc
edgar, Mobilize, msarc, PubMedWordcloud, qdap, quanteda, radiant, rbefdata, reproducer, SOMbrero
caRpools, G2Sd, lar, ODMconverter, psData, qdap
abbyyR, acs, archiDART, aRxiv, BerlinData, BIGDAWG, biomartr, bold, BoolNet, causaleffect, Causata, clifro, colourlovers, comato, coreNLP, creditr, datamart, dataRetrieval, DDIwR, decctools, dplR, dvn, Ecfun, edgar, gemtc, googlePublicData, googlesheets, GRANBase, graphicsQC, gridSVG, hddtools, HierO, hive, hoardeR, htmltab, IRISMustangMetrics, IRISSeismic, letsR, Luminescence, MALDIquantForeign, megaptera, miniCRAN, mldr, mlxR, MODISTools, MTurkR, myepisodes, OAIHarvester, ODMconverter, OpenRepGrid, optiRum, PBSmodelling, pdfetch, plotKML, primerTree, pubmed.mineR, PubMedWordcloud, pvsR, qdap, qdapTools, rAvis, rbefdata, rbhl, rClinicalCodes, rclinicaltrials, rcrossref, RDML, rdryad, readMLData, readMzXmlData, RefManageR, Reol, retrosheet, reutils, RevEcoR, rfigshare, rgbif, rio, rlist, RNeXML, rnoaa, rNOMADS, rpubchem, rsdmx, rsml, rsnps, rtematres, rvest, Ryacas, scholar, selectr, semPlot, soilDB, solr, sss, stcm, stressr, svIDE, SWMPr, taxize, TCGA2STAT, TFX, timetree, tmod, tm.plugin.europresse, tm.plugin.factiva, tm.plugin.lexisnexis, tm.plugin.webmining, TR8, traits, treebase, ustyc, vegdata, W3CMarkupValidator, waterData, WaterML, webchem, WMCapacity
cdcfluview, docxtractr, fulltext, googlesheets, rerddap, rversions
AICcmodavg, BEQI2, BioGeoBEARS, BrailleR, confidence, Correlplot, Crossover, DAMisc, descr, EasyHTMLReport, EMA, hierarchicalDS, inTrees, IsoGene, lfe, MAMA, miscset, MplusAutomation, MSBVAR, ncappc, NNTbiomarker, OpasnetUtils, pkgmaker, PopGenReport, qmethod, RecordLinkage, reportRx, reproducer, RItools, robustlmm, SensMixed, shiny, shinystan, sparkTable, spduration, StableEstim, StatDA, summarytools, userfriendlyscience, x.ent
backtestGraphics, creditr, DMwR, dygraphs, hydroGOF, pdfetch, qrmtools, rmgarch, RObsDat, rugarch, shinystan, spacetime, stressr, tawny, tawny.types, timeseriesdb, TSdist, TSmisc, TTR, vetools
Causata, htmlwidgets, knitr, liftr, nat, NCA, rfigshare, rlist, rmarkdown, swirl
ACDm, acss, bfast, creditr, DMwR, dygraphs, FDboost, gstat, hddtools, hydroPSO, iki.dataclim, lfl, LICORS, manifestoR, mlogit, partialAR, party, pdfetch, PerformanceAnalytics, plm, plotKML, psd, Quandl, quantspec, rasterVis, rmgarch, rnrfa, rugarch, sandwich, scidb, snht, spacetime, STI, survMisc, tableone, tawny, tawny.types, TED, termstrc, timeseriesdb, translateSPSS2R, trib, tripEstimation, TSdist, tseries, TSmisc, TSsql, TTR, vcrpart, Wats
bigalgebra, biganalytics, bigmemory, bigrf, bigtabulate, Boom, BoomSpikeSlab, bsts, ddalpha, DescTools, dfcomb, dfmta, dplyr, dynsurv, EPGLM, FeatureHashing, fts, FunChisq, GERGM, haven, iptools, lsgl, MBA, mixedMem, msgl, mvnfast, nabor, odeintr, OpenMx, pcalg, PReMiuM, Rblpapi, RcppBDT, rcppbugs, RcppMLPACK, RcppShark, RcppStreams, readr, rstan, sgd, sglOptim, SSN, synchronicity, xml2
blkergm, ergm.count, ergm.graphlets, ergm.userterms, tergm
AdaptiveSparsity, AHR, Amelia, ASPBay, BaBooN, BayesComm, bayesm, bayou, bcp, bfa, BIFIEsurvey, BIPOD, blockmodels, bvarsv, ccaPP, cccp, cda, CDM, cladoRcpp, coala, coneproj, copCAR, cqrReg, Crossover, DepthProc, dfcomb, dfmta, emIRT, EPGLM, EstHer, FastBandChol, fastM, FBFsearch, fdaMixed, FDRreg, fICA, FisHiCal, flip, forecast, FRESA.CAD, gaselect, GeneticTools, geoCount, GERGM, glcm, glmgraph, GMCM, gMWT, GPvam, graphicalVAR, gRbase, gRim, growcurves, growfunctions, GSE, hawkes, HLMdiag, hsphase, hypervolume, iBATCGH, icamix, iccbeta, kdecopula, Langevin, lpme, lsgl, markophylo, markovchain, MAT, matchingMarkets, matchingR, mcemGLM, mcIRT, mcmcse, metafolio, mets, mev, miceadds, mirtCAT, miscF, mixedMem, mmand, Morpho, mp, Mposterior, MRIaggr, msgl, MVB, mvnfast, ngspatial, oem, onlinePCA, PanelCount, pcalg, PedCNV, planar, PoweR, PPtreeViz, prospectr, psd, psgp, quadrupen, quanteda, Rborist, rcppbugs, RcppDE, RcppMLPACK, RealVAMS, redist, resemble, revealedPrefs, rgam, rmgarch, robustgam, robustHD, robustreg, rotations, Rphylopars, rstpm2, rugarch, sbmSDP, SBSA, SelvarMix, sgd, sglOptim, sirt, slfm, snipEM, SparseFactorAnalysis, sparsereg, SpatialEpi, SpatialTools, SpatPCA, spBayesSurv, spduration, stm, stochvol, strum, survAccuracyMeasures, SVMMatch, synlik, TAM, timma, treeclim, unmarked, VarSelLCM, zic
BayesFactor, blockcluster, btf, clere, CorReg, Coxnet, DetMCD, FastGP, FastHCS, FastPCS, FastRCS, Funclustering, gRbase, hts, ISOpureR, lme4, MPTinR, nabor, oapackage, OpenMx, PReMiuM, Rankcluster, rARPACK, Rclusterpp, rpf, RSNPset, rstan, Rvcg, saturnin, spaMM, sparseHessianFD, sparseLTSEigen, tmg, trustOptim, walkr
dfcomb, dfmta, DNAprofiles, GCPM, lsgl, matchingMarkets, msgl, sglOptim
Anthropometry, cpca, multivator, plyr, RcmdrPlugin.EZR, RcmdrPlugin.IPSUR, RcmdrPlugin.NMBU, RcmdrPlugin.pointG, tableplot
fitdistrplus, GeneralizedHyperbolic, HyperbolicDist, IPSUR, PhaseType
ChemometricsWithR, fscaret, mlr, pmml, rattle
biomod2, Guerry, GUniFrac, polysat, RcmdrPlugin.pointG
EcoGenetics, hierfstat, HWxtest, memgene, polysat, readGenalex
agridat, censReg, glmx, gmnl, LinRegInteractive, lmtest, micEconCES, mlogit, partykit, plm, REEMtree, sandwich, vcdExtra
adegenet, asbio, BayesX, BiodiversityR, DiceEval, dynaTree, EDR, erpR, evd, fBasics, fMultivar, fractal, gam, kobe, laGP, locfit, oce, plgp, portes, quantreg, R2BayesX, rgr, rpanel, sm, taRifx.geo, VdgRsm, vegdata
ChemoSpec, hamlet, kselection, pmml, rattle, REPPlab
cem, miceadds, MKmisc, semTools, simsem, Zelig
EFDR, heplots, MSG, pitchRx, plotKML, RGraphics, surveillance
ade4, aqp, dcGOR, dendextend, GLSME, hierfstat, HSAUR, HSAUR2, HSAUR3, igraph, jaatha, MVA, ouch, paco, polysat, readGenalex, rncl, rphast, sand, scrm, structSSI, symmoments
BayesFactor, fscaret, GGally, medflex, multitable, optmatch, sjmisc, sjPlot, subsemble, SuperLearner
exams, httr, matrixStats, repijson, R.rsp
biganalytics, broom, ff, ffbase, leaps, optmatch
bio3d, matpow, mlDNA, nat.nblast, NMF, PopGenome, rsgcc
dcemriS4, GGIR, hashFunction, rattle, XML
abd, AER, aod, asbio, CaDENCE, car, CARBayes, ChemometricsWithR, cond, crossReg, DAAG, doRedis, EffectsRelBaseline, ElemStatLearn, emplik, EnvStats, GEVcdn, gMCP, GSIF, gsubfn, harvestr, hoa, HSAUR, HSAUR2, HSAUR3, IPSUR, ipw, lme4, logmult, marg, matrixpls, MBESS, meboot, mirt, mistat, nlreg, npsm, optmatch, R2HTML, rms, robustbase, semGOF, semPLS, simTool, Wats
bcrm, BTSPAS, dclone, gemtc, MethComp, R2WinBUGS
aroma.core, corclass, R2SWF, R.devices, shiny
apt, gWidgets2RGtk2, mlDNA, ProgGUIinR, rattle, retistruct, Rz
abd, agridat, betareg, bglm, BIFIEsurvey, BiodiversityR, bnormnlr, chemosensors, compareGroups, Ecdat, Ecfun, fastR, fscaret, gmm, gmnl, HH, HistData, lmtest, lsmeans, McSpatial, meboot, medflex, mistat, mlogit, Morpho, multcomp, NPC, pedometrics, perturb, pglm, plm, polywog, pscl, QCAGUI, R2MLwiN, Rchoice, RcmdrPlugin.EZR, RcmdrPlugin.IPSUR, RcmdrPlugin.pointG, rddtools, REdaS, sand, sandwich, SenSrivastava, sla, Sleuth3, SMIR, strucchange, tableplot, vcdExtra
AppliedPredictiveModeling, Cubist, doParallel, doSNOW, emil, lulcc, mlr, subsemble, SuperLearner
fscaret, paleofire, roughrf, taRifx, taRifx.geo
FNN, gaselect, PLSbiplot1, plsRglm, rknn, soil.spec
FinTS, gsubfn, highfrequency, Hmisc, xts, zoo
archdata, bcpa, move, picante, RGraphics
boostr, catdata, ChemometricsWithR, ElemStatLearn, frbs, FRESA.CAD, fscaret, hmeasure, mlr, RoughSets, soil.spec, subsemble, SuperLearner, TunePareto
BiodiversityR, ChemometricsWithR, clues, dendextend, e1071, flexclust, freqweights, GDAtools, GMD, grImport, languageR, mlr, nor1mix, pdfCluster, r2d2, R2HTML, REdaS, RGraphics, robustbase, robustfa, sfsmisc, sjPlot, sprint, TraMineR
emil, Epi, mstate, pec, RcmdrPlugin.EZR, survival
AdMit, amen, BayHaz, bcp, bglm, bnormnlr, CARramps, CARrampsOcl, gap, GeneFeST, geoCount, geoRglm, ggmcmc, ltbayes, MethComp, pscl, R2BayesX, rbugs, shinystan, surveillance, Zelig, zoo
BBmisc, enaR, flexmix, formatR, knitr, peperr, RSiena
agridat, benchmark, choplump, gMCP, HSAUR, HSAUR2, HSAUR3, interval, IPSUR, multcomp, partykit, perm, sjmisc, UsingR, vcd
aqp, arulesViz, cba, copula, dendextend, flexsurv, gamlss.util, geiger, grImport, IsotopeR, movMF, netmeta, nodiv, nonrandom, OpenStreetMap, party, psychotree, RandomFields, rasterVis, rattle, Rcmdr, RGraphics, RSurvey, surveillance, tourr
ecp, IPSUR, MCMCglmm, needy, polysat, readGenalex, SNPmaxsel
aftgee, docopulae, mbbefd, npcp, simsalapar, simsem
BLCOP, FAiR, NMF, picante, PortfolioAnalytics, subselect
boral, candisc, dendextend, knitrBootstrap, rattle, textreg
GlobalFit, sybil, sybilccFBA, sybilcycleFreeFlux, sybilEFBA
checkmate, dplyr, installr, Lahman, partools, ProjectTemplate, rtop, taRifx, Xmisc
aroma.affymetrix, ETLUtils, mitools, oce, pitchRx, ProjectTemplate, quantmod, stream, TSdata, WhopGenome
ade4, CARBayes, dismo, ecolMod, hyperSpec, latticeExtra, PBSmapping, R2Cuba
nanop, npsp, PortfolioAnalytics, RcppDE, SACOBRA, SPOT
aRxiv, assertive, assertive.base, biomartr, broman, DataCombine, doRNG, dpmr, graticule, h2o, icd9, installr, likert, lineup, manifestoR, metafolio, myTAI, NlsyLinks, NMF, npsm, packrat, pkgmaker, PSAboot, rclinicaltrials, readODS, REDCapR, rfishbase, rpdo, satellite, smss, testthat, Wats, wikipediatrend
FME, gamclass, IPSUR, markovchain, PGRdup, RGraphics
colorspace, dplR, rasterVis, RGraphics, RSurvey
anonymizer, icd9, openssl, R.cache, R.devices, rmarkdown, robustlmm, R.rsp, R.utils
distr, distrRmetrics, distrSim, distrTEst, FinTS, geoCount, IPSUR, RcmdrPlugin.IPSUR, SweaveListingUtils
BayesFactor, bayou, Bclim, Causata, chemosensors, dcGOR, dnet, fitTetra, JBTools, lfl, lpbrim, MetaPCA, MetaQC, paco, pec, TED
bigrf, clustvarsel, DiceKriging, doRNG, EGRETci, evolqg, fdasrvf, GA, harvestr, hdnom, HMPTrees, intamap, Interatrix, msm, pbo, plyr, pROC, protr, psgp, regRSM, resemble, rpg, simsalapar, solarius, ss3sim, treatSens
bayesGDS, checkmate, DepthProc, enigma, fueleconomy, gapminder, ggmap, ggRandomForests, haven, JacobiEigen, metricsgraphics, nycflights13, pitchRx, pollstR, qualvar, randomizr, rattle, reval, rex, rivr, rpdo, rtable, TH.data, titanic, wikipediatrend
A3, benchmark, BiodiversityR, boostr, caret, caretEnsemble, caschrono, catdata, ChemometricsWithR, classifly, clue, coin, Daim, FinTS, frbs, fscaret, IPSUR, klaR, languageR, mistat, MLmetrics, mlr, pmml, pvar, rattle, Rcmdr, RcmdrPlugin.IPSUR, RcmdrPlugin.NMBU, ripa, RWeka, soil.spec, SPOT, strucchange, subsemble, SuperLearner, TDMR, tmle.npvi, TunePareto, VBmix
BiodiversityR, caret, ElemStatLearn, fscaret, mda, mlr, plotmo, SPOT, subsemble, SuperLearner
catdata, discSurv, Ecfun, gamclass, intReg, micEcon, miscTools
acss, AER, agridat, BiodiversityR, heplots, psychomix, Rcmdr, RcmdrPlugin.IPSUR, RcmdrPlugin.pointG, sjPlot, vcdExtra
AppliedPredictiveModeling, BiodiversityR, caret, emdbook, flexclust, flexmix, fscaret, geostatsp, IsotopeR, logmult, MetaPCA, nlmeU, plgp, rattle, robustfa, rrcov
caret, ChemometricsWithR, coloredICA, fGarch, fmri, fscaret, NMF, yaImpute
caschrono, cati, lawstat, mlDNA, modeest, rattle, stabledist
fftwtools, monitoR, psd, ripa, seewave, waveslim
caschrono, fPortfolio, portes, PortfolioAnalytics, simsalapar
backShift, bigGP, CompRandFld, crimelinkage, EFDR, ensembleBMA, ensembleMOS, expectreg, extRemes, FDboost, gstat, IPMpack, lava, mboost, MRIaggr, npsp, palaeoSig, popgraph, RSA, smoothie, spam, SpatioTemporal, SPOT, spTest, taRifx.geo, Thermimage
catdata, HSAUR, HSAUR2, HSAUR3, rebmix, tlemix
BayesFactor, bayou, Bclim, biganalytics, dcGOR, DEoptim, DiceKriging, dnet, dplR, EGRETci, evolqg, FinancialInstrument, fitTetra, fxregime, GMCM, harvestr, Interatrix, itertools, kselection, lava, msm, neuroim, pbo, phenex, plyr, protr, ripa, rpg, simsalapar, SpatPCA, ss3sim, strucchange, treatSens
dplR, gamclass, lifecontingencies, mFilter, portes, rainbow
AER, aqp, biomod2, CARBayes, dynBiplotGUI, gap, ImportExport, mi, migui, mitools, multcomp, Nippon, oce, PBSmapping, prabclus, PracTools, ProjectTemplate, rattle, Rcmdr, RcmdrPlugin.EZR, RcmdrPlugin.IPSUR, REdaS, rfordummies, RGIFT, semTools, separationplot, simsem, sjmisc, SMIR, spacetime, spdep, survey
evtree, HSAUR3, metafor, partykit, psychotools, quantreg, Zelig
agridat, BiodiversityR, biomod2, broom, caret, DiceEval, earth, ElemStatLearn, fscaret, LinRegInteractive, locfit, medflex, slp, sm, ssym, subsemble, SuperLearner, tmle.npvi, tsModel, yaImpute
aods3, depmixS4, gamboostLSS, hnp, mice, MNM, PerformanceAnalytics, surveillance, texreg
depmixS4, fitdistrplus, gamboostLSS, hnp, PerformanceAnalytics
BiodiversityR, caretEnsemble, crimelinkage, dismo, fscaret, mboost, mlr, subsemble, SuperLearner
Ecdat, gapminder, HistogramTools, ipdw, MetaQC, plotMCMC, popReconstruct, primer, ProjectTemplate, rattle, readGenalex, rfigshare, scape, SII, SMIR, solarius, sorvi, taRifx, taRifx.geo, TH.data
ape, catdata, dlnm, HSAUR, HSAUR2, HSAUR3, longpower, lsmeans, Zelig
catdata, contrast, dlnm, doBy, etm, fastpseudo, geeM, lava, lsmeans, meboot, MRCV, MuMIn
diversitree, ouch, phytools, PVR, Reol, RNeXML
geoBayes, georob, geostatsp, ipdw, npsp, prevR, RandomFields, rpanel, simba, SpatialPack, spBayes, spTest, taRifx.geo
abctools, abd, archetypes, ARPobservation, automap, bbmle, BCEA, bcp, binom, biogas, biogram, BlandAltmanLeh, broom, cda, checkmate, choroplethrMaps, chron, clere, clusterfly, coloc, contoureR, cvxclustr, dams, data.table, demi, dendextend, dielectric, directlabels, disclapmix, doBy, dplyr, ecoengine, EFDR, enigma, etm, eurostat, evaluate, ExtDist, fermicatsR, FField, flowr, freqweights, frontiles, gapminder, gcookbook, GDAdata, gender, ggROC, glinternet, gridDebug, gridExtra, hazus, HistData, historydata, HiveR, httk, icd9, installr, JacobiEigen, kfigr, Kmisc, knitrBootstrap, Lahman, latex2exp, lda, LDheatmap, lme4, ltbayes, MAc, MAd, matrixStats, metricsgraphics, mistat, moonBook, morse, MSG, multitable, munsell, mvtboost, mwaved, NlsyLinks, NNTbiomarker, oapackage, OpenStreetMap, packcircles, pander, PBImisc, PDQutils, peptider, physiology, planar, playwith, plspm, pollstR, pomp, popReconstruct, profr, ProjectTemplate, PRROC, PSCBS, psd, pxweb, qualvar, quanteda, QuantumClone, R2admb, R6, raincpc, rasterVis, rattle, rbefdata, rclinicaltrials, RcmdrPlugin.MA, RCMIP5, RDML, ReporteRs, reval, rex, rfordummies, rivr, robustbase, rpdo, rpf, rplexos, rtematres, rtf, sadists, SamplerCompare, sand, SDaA, SEERaBomb, seewave, sensitivity, shiny, simcausal, simTool, snpEnrichment, Sofi, sotkanet, spca, SPOT, ss3sim, StatRank, SuperLearner, tableone, tabplot, taRifx, TeachingDemos, tidyjson, tikzDevice, timeit, TimeProjection, tourr, tourrGui, trapezoid, treecm, tufterhandout, UsingR, varbvs, vcdExtra, viridis, wesanderson, wikipediatrend, xgboost, XLConnect, zoo
broom, catdata, CompareCausalNetworks, emil, fbRanks, flexmix, FRESA.CAD, fscaret, medflex, mlr, ModelGood, mplot, nscancor, pmml, randomForestSRC, subsemble, SuperLearner
bayesTFR, Kmisc, Lahman, NanoStringNorm, spacetime, tfplot, vegdata
FAiR, FinTS, Lambda4, psych, REdaS, semTools
automap, BayesX, lgcp, polyCub, spatsurv, surveillance, UScensus2010
compendiumdb, dendextend, dendsort, FRESA.CAD, gmodels, heplots, HistData, MAMA, matR, MKmisc, mlDNA, pbkrtest, PerformanceAnalytics, protiq, rattle, RGraphics, simba, spartan
cda, chemosensors, disclapmix, EFDR, evolqg, FField, ggExtra, ltbayes, mlxR, morse, packcircles, planar, pmc, QuantumClone, RcmdrPlugin.MA, remote, RGraphics, rotations, rpf, SCGLR, Sofi, StatRank, surveillance, walkr
Bessel, maRketSim, MBESS, PearsonDS, spatstat, TunePareto
agridat, dismo, GWmodel, ipdw, mgraph, npsp, pedometrics, sos4R, sp, spacetime, spcosa, spsann
gmodels, HistData, MetaQC, nonparaeff, paleofire, rattle, readGenalex, R.filesets, SPOT
baseline, ENmisc, LifeTables, ProgGUIinR, retistruct, RGraphics, vegdata
apt, dbConnect, LifeTables, ProgGUIinR, rattle, retistruct, RGraphics, RGtk2Extras, TopKLists
data.table, ggmap, ggplot2, RGraphics, RnavGraph, survey, viridis
Rcpp, RcppClassic, RcppCNPy, RcppGSL, RcppZiggurat, RHRV, RProtoBuf
abd, ascii, asVPC, BB, bbmle, bfp, BIFIEsurvey, biomod2, ClueR, contrast, Deducer, denstrip, emil, epade, fastR, fscaret, ggplot2, GMCM, GSIF, hdnom, htmlTable, IPSUR, languageR, lulcc, MARSS, MissingDataGUI, mlr, ndl, nlme, pec, PerformanceAnalytics, planar, plotKML, PopED, PSCBS, randomForestSRC, rattle, Rcell, Rcmdr, RcmdrPlugin.pointG, rex, RGraphics, rknn, Rmisc, Rz, separationplot, simcausal, simsalapar, Sleuth3, smcUtils, StatMatch, subsemble, SuperLearner
bcp, bio3d, ConnMatTools, dna, dynatopmodel, enaR, igraphdata, isa2, knitrBootstrap, lava, lfe, metafor, miniCRAN, NetSim, osmar, pnea, raster, rbmn, repo, rgp, RGraphics, rtop, sensitivity, simcausal, spatgraphs, spdep, stm, surface, TDAmapper, TunePareto
dMod, hyperSpec, kergp, MfUSampler, Rclusterpp, Rcpp, RcppClassic, RcppDE, RcppEigen, RcppGSL, Rmalschains
caret, caretEnsemble, ChemometricsWithR, Daim, fscaret, party, RGraphics, sperrorest, subsemble, SuperLearner
DEoptim, dplR, EGRETci, plyr, PortfolioAnalytics, solarius
dyn, FinancialInstrument, quantmod, tframePlus, TSdata, tseries, xts, zoo
ChemoSpec, curl, dismo, DT, futile.logger, io, metricsgraphics, quanteda, soilDB, sysfonts
apcluster, BiodiversityR, caret, caretEnsemble, colorspace, CompareCausalNetworks, conformal, dismo, evtree, fscaret, gamclass, mlr, pmml, rattle, sand, SPOT, vcd
AER, bpkde, colorspace, copula, EMMIXuskew, gridGraphics, HistData, HSAUR, HSAUR2, HSAUR3, latentnet, lattice, lava, MSG, MVA, NCmisc, openair, PBSmodelling, rstan, simsem, stm, survey, vcd
coxme, gap, multic, pbatR, seqMeta, skatMeta, solarius
caret, caretEnsemble, fscaret, hda, mlr, TunePareto
ChemometricsWithR, clusterfly, clValid, fscaret, mlr, RankAggreg
ChemometricsWithR, COBRA, directlabels, dna, ElemStatLearn, fscaret, glmnet, knockoff, lassoscore, mvtboost, scout
acss, ade4, AER, afex, AppliedPredictiveModeling, BaBooN, baseline, beanplot, betareg, binom, bio3d, BiodiversityR, bnlearn, cati, ChemoSpec, ChoiceModelR, CombMSC, contrast, copCAR, CORElearn, CorrBin, DAAGxtras, dclone, denstrip, desirability, DiceDesign, directlabels, diveMove, dyn, eggCounts, EnvStats, ergm, evaluate, evtree, fda, FuncMap, gamlss.add, gap, geoR, glogis, gridBase, gridDebug, gridExtra, gridSVG, grImport, gsubfn, hamlet, heplots, HistData, HiveR, HSAUR, HSAUR2, HSAUR3, hydroTSM, IPSUR, JoSAE, KRLS, Lahman, languageR, LDheatmap, libamtrack, LPCM, LPTime, lsmeans, lucid, marmap, MASS, mbbefd, MEMSS, meteoForecast, MethComp, mi, mlbench, mlmRev, mlogit, Morpho, morse, mosaicData, movMF, MPDiR, mpMap, multitable, mutoss, MVA, nlmeU, npmlreg, nutshell, Oncotree, OrgMassSpecR, pacman, pander, PBImisc, pdc, PKPDmodels, planar, plm, polyCub, polywog, protViz, psyphy, QTLRel, r2d2, Rcmdr, RcmdrPlugin.IPSUR, RcmdrPlugin.NMBU, RcmdrPlugin.pointG, RcppDE, RcppZiggurat, remote, reshape2, RFLPtools, rfordummies, RMark, robustbase, robustfa, robustX, rpanel, RSiena, rtf, sand, SASmixed, SCEPtER, SCEPtERbinary, SemiPar, simecol, simsalapar, Sleuth2, Sleuth3, SMIR, soilDB, SoilR, spdep, sperich, SPOT, SPSL, STAR, StatRank, stellaR, subsemble, SuperLearner, surveillance, survey, tableplot, taRifx, TeachingDemos, tergm, texmex, tmvtnorm, topicmodels, TrackReconstruction, ustyc, vcdExtra, WeightedCluster, wux, XLConnect
agridat, aqp, directlabels, ergm, hnp, mirt, mountainplot, pbo, remote, RGraphics, Rmisc, statnetWeb, survSNP, tdr
car, ChemometricsWithR, DAAG, ElemStatLearn, fscaret, gamclass, glmulti, Rcmdr, RcmdrPlugin.NMBU, SenSrivastava, Sleuth3
kergp, laGP, mistat, ParamHelpers, SACOBRA, spartan, SPOT, vdg
agridat, AICcmodavg, ANOM, aod, BayesFactor, benchmark, BIFIEsurvey, broom, car, catdata, DAAG, dlnm, doBy, expp, flexmix, glmulti, gmodels, hamlet, HLMdiag, hnp, HSAUR, HSAUR2, HSAUR3, irtrees, KFAS, kulife, kyotil, languageR, lava, likelihoodAsy, lsmeans, lucid, MESS, metafor, MethComp, mice, mitml, multcomp, MuMIn, mztwinreg, NanoStringNorm, ordinal, pan, pez, phia, phmm, R2admb, RcmdrPlugin.NMBU, RLRsim, SASmixed, sjmisc, sjPlot, spaMM, SPOT, texreg, TripleR, visreg
broom, car, censReg, crch, Ecdat, FinTS, fxregime, gmnl, IPSUR, meboot, multcomp, multiwayvcov, oglmx, pglm, plm, pscl, psychomix, R2MLwiN, Rchoice, Rcmdr, RcmdrPlugin.IPSUR, sampleSelection, sandwich, sjPlot, strucchange, vcdExtra
DAAGbio, kaps, mFilter, peperr, reldist, spatstat
diversitree, ggvis, mosaic, ProjectTemplate, statar, UsingR
assertr, curl, data.tree, ensurer, formula.tools, htmltab, icd9, mosaic, ngramrr, operator.tools, pomp, rio, rpdo, tidyjson, wikipediatrend
FDboost, gstat, IRISSeismic, maps, marmap, RGraphics, sos4R, spacetime, waterData
agridat, CompRandFld, dams, eeptools, eurostat, Geneland, ggplot2, ggthemes, knitrBootstrap, latticeExtra, MapGAM, maps, marmap, mosaic, move, oce, RAM, taRifx.geo, USAboundaries