This package is a collection of tools to load R packages and automatically generate BibTeX files citing them as well as load and cache plain-text and Excel formatted data stored on GitHub, and from other sources.

This package provides tools to render DOT diagram markup language in R and also provides the possibility to export the graphs in PostScript and SVG (Scalable Vector Graphics) formats. In addition, it supports literate programming packages such as knitr and rmarkdown.

This package implements the R version of the log4j package. It offers hierarchic loggers, multiple handlers per logger, level based filtering, space handling in messages and custom formatting.

Access to selected functions found in liblwgeom, the light-weight geometry library used by PostGIS.

This package provides an all relevant feature selection wrapper algorithm. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).

This package provides tools to enumerates the partitions, unequal partitions, and restricted partitions of an integer; the three corresponding partition functions are also given.

This package lets you replace the standard x-axis in ggplots with a combination matrix to visualize complex set overlaps. UpSet has introduced a new way to visualize the overlap of sets as an alternative to Venn diagrams. This package provides a simple way to produce such plots using ggplot2. In addition it can convert any categorical axis into a combination matrix axis.

This package provides 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 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).

This package provides David Scott's ASH routines ported from S-PLUS to R.

This package is for building isoscapes using mixed models and inferring the geographic origin of samples based on their isotopic ratios. This package is essentially a simplified interface to several other packages which implements a new statistical framework based on mixed models. It uses spaMM for fitting and predicting isoscapes, and assigning an organism's origin depending on its isotopic ratio. IsoriX also relies heavily on the package rasterVis for plotting the maps produced with terra using lattice'.

Ggplot2 is an implementation of the grammar of graphics in R. It combines the advantages of both base and lattice graphics: conditioning and shared axes are handled automatically, and you can still build up a plot step by step from multiple data sources. It also implements a sophisticated multidimensional conditioning system and a consistent interface to map data to aesthetic attributes.

This package runs a minimum-hypergeometric (mHG) test as described in "Discovering Motifs in Ranked Lists of DNA Sequences" by Eran Eden.

This package provides tools to compute polychoric and polyserial correlations by quick "two-step" methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases.

Writing interfaces to command line software is cumbersome. The cmdfun package provides a framework for building function calls to seamlessly interface with shell commands by allowing lazy evaluation of command line arguments. It also provides methods for handling user-specific paths to tool installs or secrets like API keys. Its focus is to equally serve package builders who wish to wrap command line software, and to help analysts stay inside R when they might usually leave to execute non-R software.

This package provides tools for functional linear modeling and analysis of actigraphy data.

This package provides an extensible framework for the efficient calculation of auto- and cross-proximities, along with implementations of the most popular ones.

This package computes fast (relative to other implementations) approximate Shapley values for any supervised learning model. Shapley values help to explain the predictions from any black box model using ideas from game theory; see doi.org/10.1007/s10115-013-0679-x for details.

This package provides functions for Maximum Likelihood (ML) estimation, non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the Maximum Likelihood viewpoint. It also includes a number of convenience tools for testing and developing your own models.

This library lets you place an exclusive or shared lock on a file using the appropriate system call provided by the underlying operating system.

This package provides a vectorized R function for calculating probabilities from a standard bivariate normal CDF.

This package provides utilities for working with Google APIs. This includes functions and classes for handling common credential types and for preparing, executing, and processing HTTP requests.

This package provides miscellaneous small tools and utilities. Many of them facilitate the work with matrices, e.g. inserting rows or columns, creating symmetric matrices, or checking for semidefiniteness. Other tools facilitate the work with regression models, e.g. extracting the standard errors, obtaining the number of (estimated) parameters, or calculating R-squared values.

This package provides a set of functions to run R code in an environment in which global state has been temporarily modified. Many of these functions were originally a part of the r-devtools package.

This package simplifies custom CSS styling of both shiny and rmarkdown via Bootstrap Sass. It supports both Bootstrap 3 and 4 as well as their various Bootswatch themes. An interactive widget is also provided for previewing themes in real time.