This package contains data structures and algorithms for sparse arrays and matrices, based on index arrays and simple triplet representations, respectively.

This package provides tools to process and print UTF-8 encoded international text (Unicode). Input, validate, normalize, encode, format, and display.

This package contains methods described by Dennis Helsel in his book Nondetects and Data Analysis: Statistics for Censored Environmental Data.

This package provides functions and datasets for the book "Modern Applied Statistics with S" (4th edition, 2002) by Venables and Ripley.

RE is a small, portable, lightweight, and quick, regular expression library for Common Lisp. It is a non-recursive, backtracing VM.

m stands for metal, a better test/unit and minitest test runner that can run tests by line number.

Use the spatial association marginal contributions derived from spatial stratified heterogeneity to capture the degree of correlation between spatial patterns.

An exact and a variational inference for coupled Hidden Markov Models applied to the joint detection of copy number variations.

The DALY Calculator is a free, open-source Graphical User Interface (GUI) for stochastic disability-adjusted life year (DALY) calculation.

Perform frequency distribution tables, associated histograms and polygons from vector, data.frame and matrix objects for numerical and categorical variables.

This package provides algorithms for detection of spatial patterns from oceanographic data using image processing methods based on Gradient Recognition.

We provide the collection of data-sets used in the book An Introduction to Statistical Learning with Applications in R'.

This package provides a LaTeX Letter class for rmarkdown', using the pandoc-letter template adapted for use with markdown'.

This package provides a toolbox for modeling manifest and latent group differences and moderation effects in various statistical network models.

Computes Control limits, coefficients of control limits, various performance metrics and depicts control charts for monitoring Maxwell-distributed quality characteristics.

Is designed to make easier printing summary statistics (for continues and factor level) tables in Latex, and plotting by factor.

Reverse depends for a given package are queued such that multiple workers can run the reverse-dependency tests in parallel.

This package provides a set of functions to implement Time Series Cointegrated System (TSCS) spatial interpolation and relevant data visualization.

Position adjustments for ggplot2 to implement "visualize as you randomize" principles, which can be especially useful when plotting experimental data.

Declarative template-based framework for verifying that objects meet structural requirements, and auto-composing error messages when they do not.

This package provides an implementation of robust nonnegative matrix factorization (rNMF). The rNMF algorithm decomposes a nonnegative high dimension data matrix into the product of two low rank nonnegative matrices, while detecting and trimming outliers. The main function is rnmf(). The package also includes a visualization tool, see(), that arranges and prints vectorized images.

Connect, query, and operate on information available from the Open Source Vulnerability database <https://osv.dev/>. Although CRAN has vulnerabilities listed, these are few compared to projects such as PyPI'. With tighter integration between R and Python', having an R specific package to access details about vulnerabilities from various sources is a worthwhile enterprise.

This package implements techniques for educational resource inspection, selection, and evaluation (RISE) described in Bodily, Nyland, and Wiley (2017) <doi:10.19173/irrodl.v18i2.2952>. Automates the process of identifying learning materials that are not effectively supporting student learning in technology-mediated courses by synthesizing information about access to course content and performance on assessments.

This package provides a client for (1) querying the DHS API for survey indicators and metadata (<https://api.dhsprogram.com/#/index.html>), (2) identifying surveys and datasets for analysis, (3) downloading survey datasets from the DHS website, (4) loading datasets and associate metadata into R, and (5) extracting variables and combining datasets for pooled analysis.