This package provides data sets used for demonstrating or testing model-related packages.

This package provides an interface (wrapper) to MPI APIs. It also provides an interactive R manager and worker environment.

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 package provides a header-only C++ interface for libhdf5.

This package provides R bindings for Google's s2 library for geometric calculations on the sphere. High-performance constructors and exporters provide high compatibility with existing spatial packages, transformers construct new geometries from existing geometries, predicates provide a means to select geometries based on spatial relationships, and accessors extract information about geometries.

This package provides software to accompany the book "Wavelet Methods for Time Series Analysis", Donald B. Percival and Andrew T. Walden, Cambridge University Press, 2000.

This package provides helper functions to work with spreadsheets and the A1:D10 style of cell range specification.

This package lets you interact with Google Sheets through the Sheets API v4. This package can read and write both the metadata and the cell data in a Sheet.

This package provides an estimation and inference methods for models of conditional quantiles: linear and nonlinear parametric and non-parametric models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.

This package provides e-statistics (energy) tests and statistics for multivariate and univariate inference, including distance correlation, one-sample, two-sample, and multi-sample tests for comparing multivariate distributions, are implemented. Measuring and testing multivariate independence based on distance correlation, partial distance correlation, multivariate goodness-of-fit tests, clustering based on energy distance, testing for multivariate normality, distance components (disco) for non-parametric analysis of structured data, and other energy statistics/methods are implemented.

This package allows for testing of non-nested models. It includes tests of model distinguishability and of model fit that can be applied to both nested and non-nested models. The package also includes functionality to obtain confidence intervals associated with AIC and BIC.

This package provides the Molecular Signatures Database (MSigDB) gene sets typically used with the Gene Set Enrichment Analysis (GSEA) software in a standard R data frame with key-value pairs. Included are the original human gene symbols and Entrez IDs as well as the equivalents for various frequently studied model organisms such as mouse, rat, pig, fly, and yeast.

This package lets you assign distinct colors to arbitrary multi-dimensional data, considering its structure.

This package provides a set of little functions that have been found useful to do little odds and ends such as plotting the results of K-means clustering, substituting special text characters, viewing parts of a data.frame, constructing formulas from text and building design and response matrices.

This r-acceptancesampling provides functionality for creating and evaluating acceptance sampling plans. Acceptance sampling is a methodology commonly used in quality control and improvement. International standards of acceptance sampling provide sampling plans for specific circumstances. The aim of this package is to provide an easy-to-use interface to visualize single, double or multiple sampling plans. In addition, methods have been provided to enable the user to assess sampling plans against pre-specified levels of performance, as measured by the probability of acceptance for a given level of quality in the lot.

The ggplot2 package is an excellent and flexible package for elegant data visualization in R. However the default generated plots require some formatting before we can send them for publication. The ggpubr package provides some easy-to-use functions for creating and customizing ggplot2-based publication-ready plots.

The RSP markup language provides a powerful markup for controlling the content and output of LaTeX, HTML, Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. Today's date is <%=Sys.Date()%>. Contrary to many other literate programming languages, with RSP it is straightforward to loop over mixtures of code and text sections, e.g. in month-by-month summaries. RSP has also several preprocessing directives for incorporating static and dynamic contents of external files (local or online) among other things. RSP is ideal for self-contained scientific reports and R package vignettes.

This package provides a fast reimplementation of several density-based algorithms of the DBSCAN family. It includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and hierarchical DBSCAN (HDBSCAN), the ordering algorithm ordering points to identify the clustering structure (OPTICS), shared nearest neighbor clustering, and the outlier detection algorithms local outlier factor (LOF) and global-local outlier score from hierarchies (GLOSH). The implementations use the kd-tree data structure for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided.

This package implements importance sampling from the truncated multivariate normal using the Geweke-Hajivassiliou-Keane (GHK) simulator. Unlike Gibbs sampling which can get stuck in one truncation sub-region depending on initial values, this package allows truncation based on disjoint regions that are created by truncation of absolute values. The GHK algorithm uses simple Cholesky transformation followed by recursive simulation of univariate truncated normals hence there are also no convergence issues. Importance sample is returned along with sampling weights, based on which, one can calculate integrals over truncated regions for multivariate normals.

Assertthat is an extension to stopifnot() that makes it easy to declare the pre and post conditions that your code should satisfy, while also producing friendly error messages so that your users know what they've done wrong.

This package provides resampling procedures to assess the stability of selected variables with additional finite sample error control for high-dimensional variable selection procedures such as Lasso or boosting. Both, standard stability selection (Meinshausen & Buhlmann, 2010) and complementary pairs stability selection with improved error bounds (Shah & Samworth, 2013) are implemented. The package can be combined with arbitrary user specified variable selection approaches.

This package helps you with creation and use of R repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are supported: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.

This package provides a simple and light-weight API for memory profiling of R expressions. The profiling is built on top of R's built-in memory profiler utils::Rprofmem(), which records every memory allocation done by R (also native code).

This package provides key-value stores with automatic pruning. Caches can limit either their total size or the age of the oldest object (or both), automatically pruning objects to maintain the constraints.