This package provides different high-level graphics functions for displaying large datasets, displaying circular data in a very flexible way, finding local maxima, brewing color ramps, drawing nice arrows, zooming 2D-plots, creating figures with differently colored margin and plot region. In addition, the package contains auxiliary functions for data manipulation like omitting observations with irregular values or selecting data by logical vectors, which include NAs. Other functions are especially useful in spectroscopy and analyses of environmental data: robust baseline fitting, finding peaks in spectra, converting humidity measures.

This package allows users to test characteristics of common R objects.

This package provides a set of tools for manipulating and reading geographic data, in particular ESRI Shapefiles. It includes binary access to GSHHG shoreline files. The package also provides interface wrappers for exchanging spatial objects with other R packages.

This package provides tools to get text from images of text using Abbyy Cloud Optical Character Recognition (OCR) API. With abbyyyR, one can easily OCR images, barcodes, forms, documents with machine readable zones, e.g. passports and get the results in a variety of formats including plain text and XML. To learn more about the Abbyy OCR API, see http://ocrsdk.com/.

This package provides counterparts to R string manipulation functions that account for the effects of ANSI text formatting control sequences.

This is a package for estimation of a sparse inverse covariance matrix using a lasso (L1) penalty. Facilities are provided for estimates along a path of values for the regularization parameter.

This package provides functions for manipulation of R documentation objects, including functions reprompt() and ereprompt() for updating Rd documentation for functions, methods and classes; it also includes Rd macros for citations and import of references from bibtex files for use in Rd files and roxygen2 comments, as well as many functions for manipulation of references and Rd files.

Read in activity measurements from standard file formats used by circadian rhythm researchers, currently only ClockLab format, and process and plot the data. The central type of plot is the actogram, as first described in "Activity and distribution of certain wild mice in relation to biotic communities" by MS Johnson (1926) doi:10.2307/1373575.

This package provides an environment for teaching "Financial Engineering and Computational Finance" and for managing chronological and calendar objects.

This package provides color palettes that have been generated mostly from Wes Anderson movies.

This package contains various routines for drawing ellipses and ellipse-like confidence regions, implementing the plots described in Murdoch and Chow (1996), A graphical display of large correlation matrices, The American Statistician 50, 178-180. There are also routines implementing the profile plots described in Bates and Watts (1988), Nonlinear Regression Analysis and its Applications.

This package provides functions and data sets for actuarial science: modeling of loss distributions; risk theory and ruin theory; simulation of compound models, discrete mixtures and compound hierarchical models; credibility theory. It boasts support for many additional probability distributions to model insurance loss amounts and loss frequency: 19 continuous heavy tailed distributions; the Poisson-inverse Gaussian discrete distribution; zero-truncated and zero-modified extensions of the standard discrete distributions. It also supports phase-type distributions commonly used to compute ruin probabilities.

Run R CMD check from R programmatically, and capture the results of the individual checks.

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 implements two methods for performing a constrained principal component analysis (PCA), where non-negativity and/or sparsity constraints are enforced on the principal axes (PAs). The function nsprcomp computes one principal component (PC) after the other. Each PA is optimized such that the corresponding PC has maximum additional variance not explained by the previous components. In contrast, the function nscumcomp jointly computes all PCs such that the cumulative variance is maximal. Both functions have the same interface as the prcomp function from the stats package (plus some extra parameters).

This package provides portable tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes and their children; restart processes. It can read the standard output and error of the processes, using non-blocking connections. processx can poll a process for standard output or error, with a timeout. It can also poll several processes at once.

The googleVis package provides an interface between R and the Google Charts API. Google Charts offer interactive charts which can be embedded into web pages. The functions of the googleVis package allow the user to visualise data stored in R data frames with Google Charts without uploading the data to Google. The output of a googleVis function is HTML code that contains the data and references to JavaScript functions hosted by Google. googleVis makes use of the internal R HTTP server to display the output locally.

This package provides tools for shrunken centroids regularized discriminant analysis for the purpose of classifying high dimensional data.

This package supports twin models that are able to estimate the dynamic behaviour of the variance components in the classical twin models with respect to age using B-splines and P-splines.

This package provides helper functions to install and maintain the LaTeX distribution named TinyTeX, a lightweight, cross-platform, portable, and easy-to-maintain version of TeX Live. This package also contains helper functions to compile LaTeX documents, and install missing LaTeX packages automatically.

This is a package for text mining for word processing and sentiment analysis using dplyr, ggplot2, and other Tidy tools.

This package contains the core survival analysis routines, including definition of Surv objects, Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, and parametric accelerated failure time models.

This package provides tools to obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. It can be used to compute contrasts or linear functions of EMMs, trends, and comparisons of slopes.

This package provides a collection of functions to compute the standardized effect sizes for experiments (Cohen d, Hedges g, Cliff delta, Vargha-Delaney A). The computation algorithms have been optimized to allow efficient computation even with very large data sets.