This package allows for fast, correct, consistent, portable, as well as convenient character string/text processing in every locale and any native encoding. Owing to the use of the ICU library, the package provides R users with platform-independent functions known to Java, Perl, Python, PHP, and Ruby programmers. Among available features there are: pattern searching (e.g. via regular expressions), random string generation, string collation, transliteration, concatenation, date-time formatting and parsing, etc.

Functions and examples are provided for transmission/disequilibrium tests for extended marker haplotypes, as in Clayton, D. and Jones, H. (1999) "Transmission/disequilibrium tests for extended marker haplotypes".

This package provides fundamental physical constants (quantity, value, uncertainty, unit) for SI and non-SI units, plus unit conversions based on the data from NIST, USA.

This package provides a number of user-level functions to work with grid graphics, notably to arrange multiple grid-based plots on a page, and draw tables.

This package provides an easy to use library to setup, apply and make inference with discrete time and discrete space hidden Markov models.

This package provides system native access to the font catalogue. As font handling varies between systems it is difficult to correctly locate installed fonts across different operating systems. The 'systemfonts' package provides bindings to the native libraries for finding font files that can then be used further by e.g. graphic devices.

This is an R package for dimension reduction based on finite Gaussian mixture modeling of inverse regression.

This package provides maximally selected rank statistics with several p-value approximations.

This package provides fast and accurate convolution-type smoothed quantile regression, implemented using Barzilai-Borwein gradient descent with a Huber regression warm start. Confidence intervals for regression coefficients are constructed using multiplier bootstrap.

This package provides a violin plot, which is a combination of a box plot and a kernel density plot.

To make it easy to create CONSORT diagrams for the transparent reporting of participant allocation in randomized, controlled clinical trials. This is done by creating a standardized disposition data, and using this data as the source for the creation a standard CONSORT diagram. Human effort by supplying text labels on the node can also be achieved.

This package provides fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the Eigen C++ library for numerical linear algebra and RcppEigen glue.

This package can be used to solve Linear Programming / Linear Optimization problems by using the simplex algorithm.

This a package containing diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf, Spatial, and nb. It also contains data stored in a range of file formats including GeoJSON, ESRI Shapefile and GeoPackage. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, are designed to illustrate point pattern analysis techniques.

This package implements functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the spatstat family of packages. Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.

Extract metadata from NetCDF data sources; these can be files, file handles or servers. This package leverages and extends the lower level functions of the RNetCDF package providing a consistent set of functions that all return data frames.

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

Enables mapping of country level and gridded user datasets.

The C++ header files of the Stan project are provided by this package. There is a shared object containing part of the CVODES library, but it is not accessible from R. r-stanheaders is only useful for developers who want to utilize the LinkingTo directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies.

The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or variational methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, templated statistical and linear algebra functions that can handle the automatically differentiable scalar types (and doubles, ints, etc.), and a parser for the Stan language. The r-rstan package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.

This package is an implementation of a regularized regression prediction and empirical Bayes method to recover the true gene expression profile in noisy and sparse single-cell RNA-seq data. In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. This package single-cell analysis via expression recovery (SAVER) implements an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.

This package provides fast machine learning algorithms including matrix factorization and divisive clustering for large sparse and dense matrices.

This package provides a set of handy functions. It includes a versatile one line progress bar, one line function timer with detailed output, time delay function, text histogram, object preview, CRAN package search, simpler package installer, Linux command install check, a flexible Mode function, top function, simulation of correlated data, and more.

This package provides an R interface to the Tabler HTML template. tablerDash is a light Bootstrap 4 dashboard template. There are different layouts available such as a one page dashboard or a multi-page template, where the navigation menu is contained in the navigation bar.

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