The function missForest in this package is used to impute missing values, particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data, including complex interactions and non-linear relations. It yields an OOB imputation error estimate without the need of a test set or elaborate cross- validation. It can be run in parallel to save computation time.

This is yet another command-line argument parser which wraps the powerful Perl module Getopt::Long and with some adaptation for easier use in R. It also provides a simple way for variable interpolation in R.

This package implements tools designed to collect and organize Twitter data via Twitter's REST and stream Application Program Interfaces (API).

This package provides a versatile interior point solver that solves linear programs (LPs), quadratic programs (QPs), second-order cone programs (SOCPs), semidefinite programs (SDPs), and problems with exponential and power cone constraints (https://clarabel.org/stable/). For quadratic objectives, unlike interior point solvers based on the standard homogeneous self-dual embedding (HSDE) model, Clarabel handles quadratic objective without requiring any epigraphical reformulation of its objective function. It can therefore be significantly faster than other HSDE-based solvers for problems with quadratic objective functions. Infeasible problems are detected using using a homogeneous embedding technique.

This package provides tools to compute polychoric and polyserial correlations by quick "two-step" methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases.

This package provides an implementation of the Uniform Manifold Approximation and Projection dimensionality reduction by McInnes et al. (2018). It also provides means to transform new data and to carry out supervised dimensionality reduction. An implementation of the related LargeVis method of Tang et al. (2016) is also provided.

This package provides an interface to the Nexus class library which allows parsing of NEXUS, Newick and other phylogenetic tree file formats. It provides elements of the file that can be used to build phylogenetic objects such as ape's phylo or phylobase's phylo4(d). This functionality is demonstrated with read_newick_phylo() and read_nexus_phylo().

This package provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. It uses a trans-dimensional Markov Chain Monte Carlo (MCMC) approach based on a continuous-time birth-death process.

It contains functions that solve least squares linear regression problems under linear equality/inequality constraints. Functions for solving quadratic programming problems are also available, which transform such problems into least squares ones first.

This package orders panels in scatterplot matrices and parallel coordinate displays by some merit index. It contains various indices of merit, ordering functions, and enhanced versions of pairs and parcoord which color panels according to their merit level.

This package provides some very simple method functions for confidence interval calculation and to distill pertinent information from a potentially complex object; primarily used in common with the packages extRemes and SpatialVx.

This r-rbenchmark package is inspired by the Perl module Benchmark, and is intended to facilitate benchmarking of arbitrary R code. The library consists of just one function, benchmark, which is a simple wrapper around system.time. Given a specification of the benchmarking process (counts of replications, evaluation environment) and an arbitrary number of expressions, benchmark evaluates each of the expressions in the specified environment, replicating the evaluation as many times as specified, and returning the results conveniently wrapped into a data frame.

In order to smoothly animate the transformation of polygons and paths, many aspects needs to be taken into account, such as differing number of control points, changing center of rotation, etc. The transformr package provides an extensive framework for manipulating the shapes of polygons and paths and can be seen as the spatial brother to the tweenr package.

The wordspace package turns R into an interactive laboratory for empirical research on distributional semantic models (DSM). It consists of a small set of carefully designed functions, most of which

• encapsulate non-trivial R operations in a user-friendly manner or

• provide efficient and memory-lean C implementations of key operations.

The main function of this package is beep(), with the purpose to make it easy to play notification sounds on whatever platform you are on. It is intended to be useful, for example, if you are running a long analysis in the background and want to know when it is ready.

This package provides a more comfortable interface to work with R data or source files in a key-value fashion.

To make it easy to create CONSORT diagrams for the transparent reporting of participant allocation in randomized, controlled clinical trials. This is done by creating a standardized disposition data, and using this data as the source for the creation a standard CONSORT diagram. Human effort by supplying text labels on the node can also be achieved.

This package provides a collection of libraries for numerical computing (numerical integration, optimization, etc.) and their integration with Rcpp.

Estimate quantile regression (QR) and composite quantile regression (cqr) and with adaptive lasso penalty using interior point (IP), majorize and minimize (MM), coordinate descent (CD), and alternating direction method of multipliers algorithms (ADMM).

This package adds additional Twitter Bootstrap components to Shiny.

This package provides simple and crisp publication-quality graphics for the ExPosition family of packages. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

This package contains a list of functional time series, sliced functional time series, and functional data sets. Functional time series is a special type of functional data observed over time. Sliced functional time series is a special type of functional time series with a time variable observed over time.

This package provides graphical scales that map data to aesthetics, and provides methods for automatically determining breaks and labels for axes and legends.

This package provides tools to create Class Cover Catch Digraphs, neighborhood graphs, and relatives.