Reshape2 is an R library to flexibly restructure and aggregate data using just two functions: melt and dcast (or acast).

This package provides a unified interface to interact with Docker and Singularity containers. You can execute a command inside a container, mount a volume or copy a file.

This package provides an mlr3 extension that provides various resampling-based confidence interval (CI) methods for estimating the generalization error. These CI methods are implemented as mlr3 measures, enabling the evaluation of individual algorithms on specific tasks as well as the comparison of different learning algorithms.

This package implements latent Dirichlet allocation (LDA) and related models. This includes (but is not limited to) sLDA, corrLDA, and the mixed-membership stochastic blockmodel. Inference for all of these models is implemented via a fast collapsed Gibbs sampler written in C. Utility functions for reading/writing data typically used in topic models, as well as tools for examining posterior distributions are also included.

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

This package is meant to ease the creation of time-to-event (i.e. survival) endpoint figures. The modular functions create figures ready for publication. Each of the functions that add to or modify the figure are written as proper ggplot2 geoms or stat methods, allowing the functions from this package to be combined with any function or customization from ggplot2 and other ggplot2 extension packages.

The Rsolnp package implements a general non-linear augmented Lagrange multiplier method solver, a sequential quadratic programming (SQP) based solver).

This package lets you manage configuration values across multiple environments (e.g. development, test, production). It reads values using a function that determines the current environment and returns the appropriate value.

This package provides tools to estimate tail area-based false discovery rates as well as local false discovery rates for a variety of null models (p-values, z-scores, correlation coefficients, t-scores). The proportion of null values and the parameters of the null distribution are adaptively estimated from the data. In addition, the package contains functions for non-parametric density estimation (Grenander estimator), for monotone regression (isotonic regression and antitonic regression with weights), for computing the greatest convex minorant (GCM) and the least concave majorant (LCM), for the half-normal and correlation distributions, and for computing empirical higher criticism (HC) scores and the corresponding decision threshold.

This package provides authentication helpers for Snowflake. It provides compatibility with authentication approaches supported by the Snowflake Connector for Python and the Snowflake CLI.

This package provides alluvial plots for ggplot2. Alluvial plots use variable-width ribbons and stacked bar plots to represent multi-dimensional or repeated-measures data with categorical or ordinal variables.

This package estimates the parameters in Dirichlet-Multinomial and computes log-likelihoods.

This package provides tools for the analysis of complex survey samples. The provided features include: summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples; variances by Taylor series linearisation or replicate weights; post-stratification, calibration, and raking; two-phase subsampling designs; graphics; PPS sampling without replacement; principal components, and factor analysis.

This package provides an R client for jq, a JSON processor. jq allows the following with JSON data: index into, parse, do calculations, cut up and filter, change key names and values, perform conditionals and comparisons, and more.

This package implements list environments. List environments are environments that have list-like properties. For instance, the elements of a list environment are ordered and can be accessed and iterated over using index subsetting.

This package provides a Wrapper around the SVDLIBC library for (truncated) singular value decomposition of a sparse matrix. Currently, only sparse real matrices in Matrix package format are supported.

This package implements an S3 class for storing and formatting time-of-day values, based on the difftime class.

This package lets you easily use Bootstrap icons inside Shiny apps and R Markdown documents. More generally, icons can be inserted in any htmltools document through inline SVG.

This package implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices.

This package provides tools to fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.

This package estimates conditional Akaike information in mixed-effect models. These models are fitted using (g)lmer() from lme4, lme() from nlme, and gamm() from mgcv. The provided functions facilitate the computation of the conditional Akaike information for model evaluation.

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 is a package for Bayesian model averaging and variable selection for linear models, generalized linear models and survival models (cox regression).

This package provides code analysis tools for R to check R code for possible problems.