Pdist computes the euclidean distance between rows of a matrix X and rows of another matrix Y. Previously, this could be done by binding the two matrices together and calling dist, but this creates unnecessary computation by computing the distances between a row of X and another row of X, and likewise for Y. Pdist strictly computes distances across the two matrices, not within the same matrix, making computations significantly faster for certain use cases.

This package provides fast and efficient routines for common rolling / windowed operations. Routines for the efficient computation of windowed mean, median, sum, product, minimum, maximum, standard deviation and variance are provided.

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 provides functions for bitwise operations on integer vectors.

This package provides classes and methods for handling genetic data. It includes classes to represent genotypes and haplotypes at single markers up to multiple markers on multiple chromosomes. Function include allele frequencies, flagging homo/heterozygotes, flagging carriers of certain alleles, estimating and testing for Hardy-Weinberg disequilibrium, estimating and testing for linkage disequilibrium, ...

This package defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. It provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users.

This package provides a suite of custom R Markdown formats and templates for authoring journal articles and conference submissions.

This package provides functions to handle basic input output. These functions always read and write UTF-8 (8-bit Unicode Transformation Format) files and provide more explicit control over line endings.

This package provides functions, data sets, analyses and examples from the third edition of the book A Handbook of Statistical Analyses Using R (Torsten Hothorn and Brian S. Everitt, Chapman & Hall/CRC, 2014). The first chapter of the book, which is entitled An Introduction to R, is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, Sweave source code for slides of selected chapters is included in this package.

This package provides functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, and more.

This package provides a collection of tools to deal with statistical models. The functionality is experimental and the user interface is likely to change in the future.

This is an unofficial package aimed at automating the import of LISREL output in R.

This package contains a simple SMTP client which provides a portable solution for sending email, including attachments, from within R.

mlr3pipelines enriches mlr3 with a diverse set of pipelining operators (PipeOps) that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as mlr3 Learners and can therefore be resampled, benchmarked, and tuned.

This package provides functions and vignettes to update data sets in Ecdat and to create, manipulate, plot, and analyze those and similar data sets.

Extracts sentiment and sentiment-derived plot arcs from text using a variety of sentiment dictionaries conveniently packaged for consumption by R users. Implemented dictionaries include syuzhet (default) developed in the Nebraska Literary Lab, afinn developed by Finn Arup Nielsen, bing developed by Minqing Hu and Bing Liu, and nrc developed by Mohammad, Saif M. and Turney, Peter D. Applicable references are available in README.md and in the documentation for the get_sentiment function. The package also provides a hack for implementing Stanford's coreNLP sentiment parser. The package provides several methods for plot arc normalization.

Similarly to Schafer's package pan, jomo is a package for multilevel joint modelling multiple imputation http://doi.org/10.1002/9781119942283. Novel aspects of jomo are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.

This package provides the datasets to support the Fish Stock Assessment (FSA) package.

This package provides visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).

R-wrs2 offers a range of strong stats methods from Wilcox WRS functions. It implements robust t-tests, both independent and dependent, robust ANOVA, including designs with between-within subjects, quantile ANOVA, robust correlation, robust mediation, and nonparametric ANCOVA models using robust location measures.

Finding an optimal Bayesian experimental design involves maximizing an objective function given by the expectation of some appropriately chosen utility function with respect to the joint distribution of unknown quantities (including responses). This objective function is usually not available in closed form and the design space can be continuous and of high dimensionality. This package uses Approximate Coordinate Exchange (ACE) to maximise an approximation to the expectation of the utility function.

This method identifies topological domains in genomes from Hi-C sequence data. The authors published an implementation of their method as an R script. This package originates from those original TopDom R scripts and provides help pages adopted from the original TopDom PDF documentation. It also provides a small number of bug fixes to the original code.

This is a package for constructing minimum-cost regular spanning subgraph as part of a non-parametric two-sample test for equality of distribution.

This package provides an SCSS compiler, powered by the libsass library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. The package uses the Sass CSS extension language, which is stable, powerful, and CSS compatible.