This package provides functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data, in particular representation, manipulation and simulation of multistate data - the Lexis suite of functions, which includes interfaces to the mstate, etm and cmprsk packages. It also contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.

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.

In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics that are not provided by base R methods related to model fitting.

r-rvest helps you scrape information from web pages. It is designed to work with magrittr to make it easy to express common web scraping tasks, inspired by libraries like BeautifulSoup.

This is a deprecated package for calculating pairwise multiple comparisons of mean rank sums. This package is superseded by the novel PMCMRplus package. The PMCMR package is no longer maintained, but kept for compatibility of dependent packages for some time.

This package provides tools to export R data as LaTeX and HTML tables.

This package provides a collection of high-performance utilities. It can be used to compute distances, correlations, autocorrelations, clustering, and other tasks. It also contains a graph clustering algorithm described in MetaCell analysis of single-cell RNA-seq data using K-nn graph partitions.

This package provides tidy tools for quantifying how well a model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).

This package provides a wrapper around the C++ library polylabel from Mapbox, providing an efficient routine for finding the approximate pole of inaccessibility of a polygon, which usually serves as an excellent candidate for labeling of a polygon.

This package provides some low-level utilities to use for R package development. It currently provides managers for multiple package specific options and registries, vignette, unit test and bibtex related utilities.

This package provides simple and crisp publication-quality graphics for the ExPosition family of packages. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

This package provides R bindings to the Sundown Markdown rendering library (https://github.com/vmg/sundown). Markdown is a plain-text formatting syntax that can be converted to XHTML or other formats.

This package provides basic I/O tools for streaming and data parsing.

This package provides two methods of plotting categorical scatter plots such that the arrangement of points within a category reflects the density of data at that region, and avoids over-plotting.

This package provides a collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

This package provides datasets associated with the gap package. Currently, it includes an example data for regional association plot (CDKN), an example data for a genomewide association meta-analysis (OPG), data in studies of Parkinson's diease (PD), ALHD2 markers and alcoholism (aldh2), APOE/APOC1 markers and Schizophrenia (apoeapoc), cystic fibrosis (cf), a Olink/INF panel (inf1), Manhattan plots with (hr1420, mhtdata) and without (w4) gene annotations.

This package provides an easy way to fill an environment with active bindings that call a C++ function.

This package provides tools for Independent Component Analysis (ICA) using various algorithms: FastICA, Information-Maximization (Infomax), and Joint Approximate Diagonalization of Eigenmatrices (JADE).

This package lets you import foreign statistical formats into R via the ReadStat C library.

The ggcorrplot package can be used to visualize easily a correlation matrix using ggplot2. It provides a solution for reordering the correlation matrix and displays the significance level on the plot. It also includes a function for computing a matrix of correlation p-values.

This package provides tools for multiple imputation of missing data in multilevel modeling. It includes a user-friendly interface to the packages pan and jomo, and several functions for visualization, data management and the analysis of multiply imputed data sets.

This package provides tools to render DOT diagram markup language in R and also provides the possibility to export the graphs in PostScript and SVG (Scalable Vector Graphics) formats. In addition, it supports literate programming packages such as knitr and rmarkdown.

This package provides an interface from R to Python modules, classes, and functions. When calling into Python, R data types are automatically converted to their equivalent Python types. When values are returned from Python to R they are converted back to R types.

This package enables you to define a command-line interface by just giving it a description in the specific format.