automap performs an automatic interpolation by automatically estimating the variogram and then calling gstat.

This package lets you create a reproducible ggplot2 object by storing the data and calls.

This package enables conversions between R objects and JavaScript Object Notation (JSON) using the rapidjsonr library.

Graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors.

This package provides regression models for grouped and coarse data, under the coarsened at random assumption.

This is a a Common Lisp re-implementation of the Rails routes system for mapping URLs.

The RSS2email program (r2e) fetches RSS/Atom news feeds, converts them into emails, and sends them.

This package exposes a sparse BLAS interface for ROCm. It is implemented in the HIP programming language.

Data package which provides default drug and disease expression profiles for the DvD package.

An R package for computing the number of susceptibility SNPs and power of future studies.

This package implements the uniform scaled beta distribution and the continuous convolution kernel density estimator.

Exploring fitted models by interactively taking 2-D and 3-D sections in data space.

This package provides a small package containing helper utilities for creating functions for computing statistics.

This package provides adaptive association tests for SNP level, gene level and pathway level analyses.

Datasets used in the book Graphical Data Analysis with R (Antony Unwin, CRC Press 2015).

An implementation of a simple and highly optimized ordinary kriging algorithm to plot geographical data.

Genome-wide association (GWAS) analyses of a biomarker that account for the limit of detection.

GEE solver for correlated nominal or ordinal multinomial responses using a local odds ratios parameterization.

Parametric bootstrap (PB) has been used for three-way ANOVA model with unequal group variances.

This package provides a simple way to add page numbers to base/ggplot/lattice graphics.

This package contains the function CUUimpute() which performs model-based clustering and imputation simultaneously.

This package provides functions for the Skellam distribution, including: density (pmf), cdf, quantiles and regression.

This package provides a system for reporting messages, which offers certain useful features over the standard R system, such as the incorporation of output consolidation, message filtering, assertions, expression substitution, automatic generation of stack traces for debugging, and conditional reporting based on the current "output level".

This package implements UbiBic algorithm in R. This biclustering algorithm for analysis of gene expression data was introduced by Zhenjia Wang et al. in 2016. It is currently considered the most promising biclustering method for identification of meaningful structures in complex and noisy data.