This package provides a set of predicates and assertions for checking the types of variables. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package provides the Molecular Signatures Database (MSigDB) gene sets typically used with the Gene Set Enrichment Analysis (GSEA) software in a standard R data frame with key-value pairs. Included are the original human gene symbols and Entrez IDs as well as the equivalents for various frequently studied model organisms such as mouse, rat, pig, fly, and yeast.

This package provides tools to perform analyses and combine results from multiple-imputation datasets.

This package provides functions useful in the design and ANOVA of experiments. The content falls into the following groupings:

1. data,

2. factor manipulation functions,

3. design functions,

4. ANOVA functions,

5. matrix functions,

6. projector and canonical efficiency functions, and

7. miscellaneous functions.

There is a vignette called DesignNotes describing how to use the design functions for randomizing and assessing designs. The ANOVA functions facilitate the extraction of information when the Error function has been used in the call to aov.

This package provides a system for organizing column names in data. It is aimed at supporting a prefix-based and suffix-based column naming scheme. It extends dplyr functionality to add ordering by function and more explicit renaming.

This package provides support for iterators, which allow a programmer to traverse through all the elements of a vector, list, or other collection of data.

This package provides a set of predicates and assertions for checking the properties of strings. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package provides basic functions, implemented in C, for large data manipulation. Fast vectorised ifelse()/nested if()/switch() functions, psum()/pprod() functions equivalent to pmin()/pmax() plus others which are missing from base R. Most of these functions are callable at C level.

This is a package for 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 a library for manipulation, processing and displaying with OpenGL of triangle and tetrahedral meshes.

This is a package for the computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate, and multimodal regression.

spacefillr enables generation of random and quasi-random space-filling sequences. It supports the following sequences: Halton, Sobol, Owen-scrambled Sobol, Owen-scrambled Sobol with errors distributed as blue noise, progressive jittered, progressive multi-jittered (PMJ), PMJ with blue noise, PMJ02, and PMJ02 with blue noise. The package also includes a C++ API.

This package provides bindings to GnuPG for working with OpenGPG (RFC4880) cryptographic methods. It includes utilities for public key encryption, creating and verifying digital signatures, and managing your local keyring. Some functionality depends on the version of GnuPG that is installed on the system.

This package provides a dependency manager for R projects that allows you to manage the R packages your project depends on in an isolated, portable, and reproducible way.

Similarly to the FNN package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. The implementation is based on cover trees introduced by Alina Beygelzimer, Sham Kakade, and John Langford (2006) doi:10.1145/1143844.1143857.

The encoding of color can be handled in many different ways, using different color spaces. As different color spaces have different uses, efficient conversion between these representations are important. This package provides a set of functions that gives access to very fast color space conversion and comparisons implemented in C++, and offers 100-fold speed improvements over the convertColor function in the grDevices package.

This package provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations).

This package lets you generate random colors, possibly with a given hue or a given luminosity.

Gtable is a collection of tools to make it easier to work with "tables" of grobs.

This R package provides a single procedure guix.install(), which allows users to install R packages via Guix right from within their running R session. If the requested R package does not exist in Guix at this time, the package and all its missing dependencies will be imported recursively and the generated package definitions will be written to ~/.Rguix/packages.scm. This record of imported packages can be used later to reproduce the environment, and to add the packages in question to a proper Guix channel (or Guix itself). guix.install() not only supports installing packages from CRAN, but also from Bioconductor or even arbitrary git or mercurial repositories, replacing the need for installation via devtools.

This package contains methods described by Dennis Helsel in his book Nondetects and Data Analysis: Statistics for Censored Environmental Data.

The package provides estimators of the mode of univariate unimodal (and sometimes multimodal) data and values of the modes of usual probability distributions.

This package provides drop-in replacements for the base system2() function with fine control and consistent behavior across platforms. It supports clean interruption, timeout, background tasks, and streaming STDIN / STDOUT / STDERR over binary or text connections. The package also provides functions for evaluating expressions inside a temporary fork. Such evaluations have no side effects on the main R process, and support reliable interrupts and timeouts. This provides the basis for a sandboxing mechanism.

This package provides colour choice in information visualisation. It important in order to avoid being mislead by inherent bias in the used colour palette. This package provides access to the perceptually uniform and colour-blindness friendly palettes developed by Fabio Crameri and released under the "Scientific Colour-Maps" moniker. The package contains 24 different palettes and includes both diverging and sequential types.

This package provides implementation of methods for estimation of quantitative maps from Multi-Parameter Mapping (MPM) acquisitions including adaptive smoothing methods in the framework of the ESTATICS model. The smoothing method is described in Mohammadi et al. (2017). <doi:10.20347/WIAS.PREPRINT.2432>. Usage of the package is also described in Polzehl and Tabelow (2019), Magnetic Resonance Brain Imaging, Chapter 6, Springer, Use R! Series. <doi:10.1007/978-3-030-29184-6_6>.