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

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 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).

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 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.

Visual predictive checks are a commonly used diagnostic plot in pharmacometrics, showing how certain statistics (percentiles) for observed data compare to those same statistics for data simulated from a model. The package can generate VPCs for continuous, categorical, censored, and (repeated) time-to-event data.

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.

This package provides a collection of (mostly simple) functions for generating and manipulating colors in R.

This package provides R functions implementing a standard unit testing framework, with additional code inspection and report generation tools.

This package provides a set of functions used to automate commonly used methods in regression analysis. This includes plotting interactions, and calculating simple slopes, standardized coefficients, regions of significance (Johnson & Neyman, 1936; cf. Spiller et al., 2012), etc.

tidyr is a reframing of the reshape2 package designed to accompany the tidy data framework, and to work hand-in-hand with magrittr and dplyr to build a solid pipeline for data analysis. It is designed specifically for tidying data, not the general reshaping that reshape2 does, or the general aggregation that reshape did. In particular, built-in methods only work for data frames, and tidyr provides no margins or aggregation.

This package is a port of the S+ "Robust Library". It provides methods for robust statistics, notably for robust regression and robust multivariate analysis.

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

This package provides functions to query the main R repository to find the versions that r-release and r-oldrel refer to, and also all previous R versions and their release dates.

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.

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(), lmeTest::lmer(), gamm4::gamm4(), mgcv::gamm() and SemiPar::spm().

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.

This package provides a number of polymodes for working with mixed R files, including Rmarkdown files.

This package provides a pure R implementation of the t-SNE algorithm.

GNU PSPP is a statistical analysis program. It can perform descriptive statistics, T-tests, linear regression and non-parametric tests. It features both a graphical interface as well as command-line input. PSPP is designed to interoperate with Gnumeric, LibreOffice and OpenOffice. Data can be imported from spreadsheets, text files and database sources and it can be output in text, PostScript, PDF or HTML.

Enumerable::Statistics provides some methods to calculate statistical summary in arrays and enumerables.

This package provides a unit testing system for R designed to be fun, flexible and easy to set up.

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.