The Rcpp package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about Rcpp is provided by several vignettes included in this package, via the Rcpp Gallery site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, JSS), and the book by Eddelbuettel (2013, Springer); see citation("Rcpp") for details on these last two.

This package provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to:

1. Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions.

2. Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws.

3. Provide various summaries of draws in convenient formats.

4. Provide lightweight implementations of state of the art posterior inference diagnostics.

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 a %dopar% adapter such that any type of futures can be used as backends for the foreach framework.

This is a developer-focused, low dependency package in tidymodels that provides functions to register how models are to be used. Functions to register models are complimented with accessor functions to retrieve registered model information to aid in model fitting and error handling.

Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.

This package provides utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models, this package implements features like standardization or bootstrapping of parameters and models, feature reduction (feature extraction and variable selection) as well as conversion between indices of effect size.

This package provides SNP array data from different types of copy-number regions. These regions were identified manually by the authors of the package and may be used to generate realistic data sets with known truth.

This package provides functions for the quality control, homogenization and missing data infilling of climatological series, and to obtain climatological summaries and grids from the results. Also functions to draw wind-roses and Walter&Lieth climate diagrams are included.

The package provides estimators of the mode of univariate unimodal (and sometimes multimodal) data and values of the modes of usual probability distributions.

This package implements the regularized Gaussian maximum likelihood estimation of the inverse of a covariance matrix. It uses Newton's method and coordinate descent to solve the regularized inverse covariance matrix estimation problem.

Look up the username and full name of the current user, the current user's email address and GitHub username, using various sources of system and configuration information.

This package provides tools for generating and handling of Universally Unique Identifiers (UUIDs).

This package provides a suite of functions to help ease the use of the d3.js visualization library in R. These helpers include htmltools::htmlDependency functions, hierarchy builders, and conversion tools for partykit, igraph, table, and data.frame R objects into the JSON format that the d3.js library expects.

This package provides the header files for a stripped-down version of the plog header-only C++ logging library, and a method to log to R's standard error stream.

This package provides an implementation of the Anderson-Darling GoF test with p-value calculation based on Marsaglia's 2004 paper "Evaluating the Anderson-Darling Distribution".

This package provides Cramer-Von Mises and Anderson-Darling tests of goodness-of-fit for continuous univariate distributions, using efficient algorithms.

This package provides a modern module system for R. Organize code into hierarchical, composable, reusable modules, and use it effortlessly across projects via a flexible, declarative dependency loading syntax.

This package contains all the datasets for the spatstat package.

This package implements many algorithms for statistical learning on sparse matrices: matrix factorizations, matrix completion, elastic net regressions, factorization machines. The rsparse package also enhances the Matrix package by providing methods for multithreaded <sparse, dense> matrix products and native slicing of the sparse matrices in Compressed Sparse Row (CSR) format.

This package provides tools to help working with text files. It can return the number of lines; print the first and last lines; convert encoding. Operations are made without reading the entire file before starting, resulting in good performances with large files.

This package provides functions to extract commonly used fragmentation metrics to quantify time accumulation strategies based on minute level actigraphy-measured activity counts data.

This package provides a collection of functions to help in the analysis of right-censored survival data. These extend the methods available in the survival package.

This is a package containing Public Key Infrastructure functions such as verifying certificates, RSA encryption and signing, which can be used to build PKI infrastructure and perform cryptographic tasks.