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.

This Python package can be used to read and write SAS, SPSS and Stata files into/from Pandas DataFrames. It is a wrapper around the C library readstat.

This package lets you calculate power for generalized linear mixed models, using simulation. It was designed to work with models fit using the lme4 package. The package is described in Green and MacLeod (2016).

Nautilus is an pure-Python package for Bayesian posterior and evidence estimation. It utilizes importance sampling and efficient space exploration using neural networks. Compared to traditional MCMC and Nested Sampling codes, it often needs fewer likelihood calls and produces much larger posterior samples. Additionally, nautilus is highly accurate and produces Bayesian evidence estimates with percent precision. It is widely used in many areas of astrophysical research.

ArviZ is a Python package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, data storage, model checking, comparison and diagnostics.

SPAMS (SPArse Modeling Software) is an optimization toolbox for solving various sparse estimation problems. It includes tools for the following problems:

1. Dictionary learning and matrix factorization (NMF, sparse principle component analysis (PCA), ...)

2. Solving sparse decomposition problems with LARS, coordinate descent, OMP, SOMP, proximal methods

3. Solving structured sparse decomposition problems (l1/l2, l1/linf, sparse group lasso, tree-structured regularization, structured sparsity with overlapping groups,...).

This package provides a generic infrastructure for creating and using R package registries.

Roxygen2 is a Doxygen-like in-source documentation system for Rd, collation, and NAMESPACE files.

This package implements importance sampling from the truncated multivariate normal using the Geweke-Hajivassiliou-Keane (GHK) 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.

This package provides an implementation of the Language Server Protocol for R. The Language Server protocol is used by an editor client to integrate features like auto completion.

The sourcetools package provides both an R and C++ interface for the tokenization of R code, and helpers for interacting with the tokenized representation of R code.

This package provides an integration of Eigen in R using 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.

This package provides a collection of algorithms and functions to aid statistical modeling. It 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. It also includes advanced generalized linear model functions that implement secure convergence, dispersion modeling and Tweedie power-law families.

This package displays 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.

This package provides the R math library as an independent package.

This package provides methods for caching or memoization of objects and results. 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).

This package provides functionalities to build and manipulate probability distributions of the skew-normal family and some related ones, notably the skew-t family, and provides related statistical methods for data fitting and diagnostics, in the univariate and the multivariate case.

rchitect provides access to R functionality from Python. Its main use is as the driver for radian, the R console.

Radian is an alternative console for the R program with multiline editing and rich syntax highlight. One would consider Radian as a IPython clone for R, though its design is more aligned to Julia.

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 3.8.8.2) is included.

This package provides a resampling-based inference based on data resampling and permutation.

Features:

• Bootstrap resampling: ordinary or balanced with optional stratification

• Extended bootstrap resampling: also varies sample size

• Parametric resampling: Gaussian, Poisson, gamma, etc.)

• Jackknife estimates of bias and variance of any estimator

• Compute bootstrap confidence intervals (percentile or BCa) for any estimator

• Permutation-based variants of traditional statistical tests (USP test of independence and others)

• Tools for working with empirical distributions (CDF, quantile, etc.)

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 provides a small wrapper on regexpr to extract the matches and captured groups from the match of a regular expression to a character vector.

This package provides the Breiman and Cutler's random forests algorithm, based on a forest of trees using random inputs, for classification and regression.