This package provides a collection of R functions to perform nonparametric analysis of covariance for regression curves or surfaces. Testing the equality or parallelism of nonparametric curves or surfaces is equivalent to analysis of variance (ANOVA) or analysis of covariance (ANCOVA) for one-sample functional data. Three different testing methods are available in the package, including one based on L-2 distance, one based on an ANOVA statistic, and one based on variance estimators.

The choices of color palettes in R can be quite overwhelming with palettes spread over many packages with many different API's. This package aims to collect all color palettes across the R ecosystem under the same package with a streamlined API.

This package provides analytic derivatives and information matrices for fitted linear mixed effects (lme) models and generalized least squares (gls) models estimated using lme() (from package nlme) and gls() (from package nlme), respectively. The package includes functions for estimating the sampling variance-covariance of variance component parameters using the inverse Fisher information. The variance components include the parameters of the random effects structure (for lme models), the variance structure, and the correlation structure. The expected and average forms of the Fisher information matrix are used in the calculations, and models estimated by full maximum likelihood or restricted maximum likelihood are supported. The package also includes a function for estimating standardized mean difference effect sizes based on fitted lme or gls models.

This package implements different robust clustering algorithms (tclust) based on trimming and including some graphical diagnostic tools (ctlcurves and DiscrFact).

This package contains an implementation of a function digest() for the creation of hash digests of arbitrary R objects (using the md5, sha-1, sha-256, crc32, xxhash and murmurhash algorithms) permitting easy comparison of R language objects, as well as a function hmac() to create hash-based message authentication code.

Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as OpenSSL should be used.

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. 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++.

The package implements basic and high-level functions for reading, writing, manipulating, analyzing and modeling of gridded spatial data. Processing of very large files is supported.

This package provides functions for the quality control, homogenization and missing data infilling of climatological series, and to obtain climatological summaries and grids from the results. Also functions to draw wind-roses and Walter&Lieth climate diagrams are included.

A treemap is a space-filling visualization of hierarchical structures. This package offers great flexibility to draw treemaps.

The R package ggplot2 is a plotting system based on the grammar of graphics. GGally extends ggplot2 by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.

This package implements core utilities for single-cell RNA-seq data analysis. Contained within are utility functions for working with DE matrices and count matrices, a collection of functions for manipulating and plotting data via ggplot2, and functions to work with cell graphs and cell embeddings. Graph-based methods include embedding kNN cell graphs into a UMAP, collapsing vertices of each cluster in the graph, and propagating graph labels.

This package provides an implementation of interpreted string literals, inspired by Python's Literal String Interpolation (PEP-0498) and Docstrings (PEP-0257) and Julia's Triple-Quoted String Literals.

This package 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.

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.

This package provides multiple sources of stopwords, for use in text analysis and natural language processing.

This package provides data sets used for demonstrating or testing model-related packages.

This package provides density, probability and quantile functions, and random number generation for (skew) stable distributions, using the parametrizations of Nolan.

This package provides a file format for storing tensors that is secure (doesn't allow for code execution), fast and simple to implement. safetensors also enables cross language and cross frameworks compatibility making it an ideal format for storing machine learning model weights.

This package allows for the imputation of the last largest censored observantions. This method brings less bias and more efficient estimates for AFT models.

This package provides a ggplot2 extension for implementing parliament charts and several other useful visualizations.

This package provides a fast dimensionality reduction method scalable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.

This package provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling.

This package provides a new class Formula, which extends the base class formula. It supports extended formulas with multiple parts of regressors on the right-hand side and/or multiple responses on the left-hand side.

This package provides

1. pseudo random generators, such as general linear congruential generators, multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister algorithm and WELL generators)

2. quasi random generators, such as the Torus algorithm, the Sobol sequence, the Halton sequence (including the Van der Corput sequence), and

3. some generator tests: the gap test, the serial test, the poker test.

See e.g. Gentle (2003) doi:10.1007/b97336.