This package provides a shared resource interface for the bigmemory and synchronicity packages.

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

This package provides functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous item responses. It enables the estimation of the DINA and DINO model, the multiple group (polytomous) GDINA model, the multiple choice DINA model, the general diagnostic model (GDM), the structured latent class model (SLCA), and regularized latent class analysis. See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) doi:10.18637/jss.v074.i02 for further details on estimation and the package structure. For tutorials on how to use the CDM package see George and Robitzsch (2015, doi:10.20982/tqmp.11.3.p189) as well as Ravand and Robitzsch (2015).

This package includes HTML functions and methods to write in an HTML file. Thus, making HTML reports is easy. It includes a function that allows redirection on the fly, which appears to be very useful for teaching purposes, as the student can keep a copy of the produced output to keep all that they did during the course. The package comes with a vignette describing how to write HTML reports for statistical analysis. Finally, a driver for Sweave parses HTML flat files containing R code and to automatically write the corresponding outputs (tables and graphs).

This package provides procedures to work with block diagonal symmetric matrices, a special case of sparse matrices.

This package provides functions for feed-forward neural networks with a single hidden layer, and for multinomial log-linear models.

This package provides an R module for display of maps. Projection code and larger maps are in separate packages (mapproj and mapdata).

Nucleotide conversion sequencing experiments have been developed to add a temporal dimension to RNA-seq and single-cell RNA-seq. Such experiments require specialized tools for primary processing such as GRAND-SLAM, and specialized tools for downstream analyses. grandR provides a comprehensive toolbox for quality control, kinetic modeling, differential gene expression analysis and visualization of such data.

This package is a data visualization package for R providing an implementation of an interactive grammar of graphics, taking the best parts of ggplot2, combining them with the reactive framework of Shiny and drawing web graphics using Vega.

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

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

Alternating least squares is often used to resolve components contributing to data with a bilinear structure; the basic technique may be extended to alternating constrained least squares. This package provides an implementation of multivariate curve resolution alternating least squares (MCR-ALS).

Commonly applied constraints include unimodality, non-negativity, and normalization of components. Several data matrices may be decomposed simultaneously by assuming that one of the two matrices in the bilinear decomposition is shared between datasets.

This package provides a unified interface to interact with Docker and Singularity containers. You can execute a command inside a container, mount a volume or copy a file.

This package implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.

This package contains the Rook specification and convenience software for building and running Rook applications. A Rook application is an R reference class object that implements a call method or an R closure that takes exactly one argument, an environment, and returns a list with three named elements: the status, the headers, and the body.

This package performs search for the global minimum of a very complex non-linear objective function with a very large number of optima.

This package was previously an R wrapper of the ARPACK library, and now a shell of the R package RSpectra, an R interface to the Spectra library for solving large scale eigenvalue/vector problems. The current version of rARPACK simply imports and exports the functions provided by RSpectra. New users of rARPACK are advised to switch to the RSpectra package.

This R package provides a single procedure guix.install(), which allows users to install R packages via Guix right from within their running R session. If the requested R package does not exist in Guix at this time, the package and all its missing dependencies will be imported recursively and the generated package definitions will be written to ~/.Rguix/packages.scm. This record of imported packages can be used later to reproduce the environment, and to add the packages in question to a proper Guix channel (or Guix itself). guix.install() not only supports installing packages from CRAN, but also from Bioconductor or even arbitrary git or mercurial repositories, replacing the need for installation via devtools.

This package provides functions for easily manipulating colors, creating color scales and calculating color distances.

This package provides the cumulative distribution function (CDF), quantile, and statistical power calculator for a collection of thresholding Fisher's p-value combination methods, including Fisher's p-value combination method, truncated product method and, in particular, soft-thresholding Fisher's p-value combination method which is proven to be optimal in some context of signal detection. The p-value calculator for the omnibus version of these tests are also included.

This package provides an htmlwidgets interface to billboard.js, a re-usable easy interface JavaScript chart library, based on D3 v4+. Chart types include line charts, scatterplots, bar/lollipop charts, histogram/density plots, pie/donut charts and gauge charts. All charts are interactive, and a proxy method is implemented to smoothly update a chart without rendering it again in shiny apps.

This package provides a system for embedded scientific computing and reproducible research with R. The OpenCPU server exposes a simple but powerful HTTP API for RPC and data interchange with R. This provides a reliable and scalable foundation for statistical services or building R web applications. The OpenCPU server runs either as a single-user development server within the interactive R session, or as a multi-user stack based on Apache2.

This package provides utility functions that enhance the parallel package and support the built-in parallel backends of the future package. For example, availableCores gives the number of CPU cores available to your R process as given by R options and environment variables, including those set by job schedulers on high-performance compute clusters. If none is set, it will fall back to parallel::detectCores. Another example is makeClusterPSOCK, which is backward compatible with parallel::makePSOCKcluster while doing a better job in setting up remote cluster workers without the need for configuring the firewall to do port-forwarding to your local computer.

This package provides routines for Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear Models.