This package provides linear models based on Theil-Sen single median and Siegel repeated medians. They are very robust (29 or 50 percent breakdown point, respectively), and if no outliers are present, the estimators are very similar to OLS.

This package provides flexible Bayesian estimation of IMIFA and related models, for nonparametrically clustering high-dimensional data. The IMIFA model conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model selection criteria to choose the number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific diagnostic tools are also provided, as well as many options for plotting results, conducting posterior inference on parameters of interest, posterior predictive checking, and quantifying uncertainty.

This package lets you download Google fonts and generate CSS to use in rmarkdown documents and Shiny applications. Some popular fonts are included and ready to use.

This R package caches the results of a function so that when you call it again with the same arguments it returns the pre-computed value.

Solving a system of linear equations is one of the most fundamental computational problems for many fields of mathematical studies, such as regression problems from statistics or numerical partial differential equations. This package provides basic stationary iterative solvers such as Jacobi, Gauss-Seidel, Successive Over-Relaxation and SSOR methods. Nonstationary, also known as Krylov subspace methods are also provided. Sparse matrix computation is also supported in that solving large and sparse linear systems can be manageable using the Matrix package along with RcppArmadillo.

This package provides an interface to Amazon Web Services security, identity, and compliance services, including the Identity and Access Management (IAM) service for managing access to services and resources, and more.

Algorithms to find arrangements of non-overlapping circles.

This package performs sparse linear discriminant analysis for Gaussians and mixture of Gaussian models.

This package provides useful functions to edit ggplot object (e.g., setting fonts for theme and layers, adding rounded rectangle as background for each of the legends).

Tools for performing model selection and model averaging. Automated model selection through subsetting the maximum model, with optional constraints for model inclusion. Model parameter and prediction averaging based on model weights derived from information criteria (AICc and alike) or custom model weighting schemes.

This package provides bindings to the OSQP solver. The OSQP solver is a numerical optimization package or solving convex quadratic programs written in C and based on the alternating direction method of multipliers. See <arXiv:1711.08013> for details.

This package helps to construct standard dialog boxes for your GUI, including message boxes, input boxes, list, file or directory selection, and others. In case R cannot display GUI dialog boxes, a simpler command line version of these interactive elements is also provided as a fallback solution.

This package provides routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

This package allows you to control the number of threads the BLAS library uses. It is also possible to control the number of threads in OpenMP.

Logging functions in RcppSpdlog provide access to the logging functionality from the spdlog C++ library. This package offers shorter convenience wrappers for the R functions which match the C++ functions, namely via, say, spdl::debug() at the debug level. The actual formatting is done by the fmt::format() function from the fmtlib library (that is also std::format() in C++20 or later).

This package provides an R interface to the vis.js JavaScript charting library. It allows an interactive visualization of networks.

This package provides a fast implementation of hierarchical clustering.

This package enables you to estimate the p-values for predictors x against target variable y in Lasso regression, using the regularization strength when each predictor enters the active set of regularization path for the first time as the statistic.

This package provides tools for exploratory data analysis and data visualization of biological sequence (DNA and protein) data. It also includes utilities for sequence data management under the ACNUC system.

This package provides basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002).

This package contains some functions to help users (especially data explorers) to make more sense of their variables and take the most out of variables and hardware resources. Functions in this package are supposed to be efficient and easy to use.

This package provides efficient routines for manipulation of date-time objects while accounting for time-zones and daylight saving times. The package includes utilities for updating of date-time components (year, month, day etc.), modification of time-zones, rounding of date-times, period addition and subtraction etc. Parts of the CCTZ source code, released under the Apache 2.0 License, are included in this package.

For outlier detection in small and normally distributed samples the ratio test of Dixon (Q-test) can be used. Density, distribution function, quantile function and random generation for Dixon's ratio statistics are provided as wrapper functions. The core applies McBane's Fortran functions that use Gaussian quadrature for a numerical solution.

This package provides utilities for computation and analysis of correlation/covariation in multiple sequence alignments and in side chain motions during molecular dynamics simulations. Features include the computation of correlation/covariation scores using a variety of scoring functions between either sequence positions in alignments or side chain dihedral angles in molecular dynamics simulations and utilities to analyze the correlation/covariation matrix through a variety of tools including network representation and principal components analysis. In addition, several utility functions are based on the R graphical environment to provide friendly tools for help in data interpretation.