This package provides a complete unit test system and functions to implement its GUI part.

This package allows the user to specify debug messages as special string constants, and control debugging of packages via environment variables.

This package provides some easy-to-use functions to extract and visualize the output of multivariate data analyses, including PCA (Principal Component Analysis), CA (Correspondence Analysis), MCA (Multiple Correspondence Analysis), FAMD (Factor Analysis of Mixed Data), MFA (Multiple Factor Analysis) and HMFA (Hierarchical Multiple Factor Analysis) functions from different R packages. It contains also functions for simplifying some clustering analysis steps and provides ggplot2-based elegant data visualization.

This package provides a collection of templates to author preregistration documents for scientific studies in PDF format.

This package provides the header files for a stripped-down version of the plog header-only C++ logging library, and a method to log to R's standard error stream.

This package implements tools for manipulation of digital images and the Propagation Separation approach by Polzehl and Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1> for smoothing digital images, see Polzehl and Tabelow (2007) <DOI:10.18637/jss.v019.i01>.

This package contains utility functions used by the Genome Analysis Toolkit (GATK) to load tables and plot data. The GATK is a toolkit for variant discovery in high-throughput sequencing data.

This package support non-robust and robust computations of the sample autocovariance (ACOVF) and sample autocorrelation functions (ACF) of univariate and multivariate processes. The methodology consists in reversing the diagonalization procedure involving the periodogram or the cross-periodogram and the Fourier transform vectors, and, thus, obtaining the ACOVF or the ACF as discussed in Fuller (1995) doi:10.1002/9780470316917. The robust version is obtained by fitting robust M-regressors to obtain the M-periodogram or M-cross-periodogram as discussed in Reisen et al. (2017) doi:10.1016/j.jspi.2017.02.008.

This package provides vectorized distribution objects with tools for manipulating, visualizing, and using probability distributions. It was designed to allow model prediction outputs to return distributions rather than their parameters, allowing users to directly interact with predictive distributions in a data-oriented workflow. In addition to providing generic replacements for p/d/q/r functions, other useful statistics can be computed including means, variances, intervals, and highest density regions.

This package computes spherical trigonometry for geographic applications. That is, compute distances and related measures for angular (longitude/latitude) locations.

This is a package for computation and visualization of the empirical attainment function (EAF) for the analysis of random sets in multi-criterion optimization.

This package provides classes and methods for dense and sparse matrices and operations on them using LAPACK and SuiteSparse.

This package estimates previously compiled regression models using the rstan package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.

This package provides tools to integrate nucleotide sequencing data (variant call format, e.g. VCF or BCF) or meta-analysis results in R.

This package provides methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

This package provides a system for generating extendable and customizable heatmaps for exploring complex datasets, including big data and data with multiple data types.

This package provides an implementation of the Harmony algorithm for single cell integration. This package includes a standalone Harmony function and interfaces to external frameworks.

This package lets you plot model surfaces for a wide variety of models using partial dependence plots and other techniques. Also plot model residuals and other information on the model.

This package provides tools for the estimation of indicators on social exclusion and poverty, as well as an implementation of Pareto tail modeling for empirical income distributions.

This package analyzes gene expression (time series) data with focus on the inference of gene networks. In particular, GeneNet implements the methods of Schaefer and Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007) for learning large-scale gene association networks (including assignment of putative directions).

This package provides an implementation of a data cube extracted out of dplyr for backward compatibility.

The fst package for R provides a fast, easy and flexible way to serialize data frames. With access speeds of multiple GB/s, fst is specifically designed to unlock the potential of high speed solid state disks. Data frames stored in the fst format have full random access, both in column and rows. The fst format allows for random access of stored data and compression with the LZ4 and ZSTD compressors.

Plyr is a set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to fit a model to each spatial location or time point in your study, summarise data by panels or collapse high-dimensional arrays to simpler summary statistics.

This package contains supporting data sets that are used in other packages maintained by Torsten Hothorn.