This package provides an R port of the library Clipper. It performs polygon clipping operations (intersection, union, set minus, set difference) for polygonal regions of arbitrary complexity, including holes. It computes offset polygons (spatial buffer zones, morphological dilations, Minkowski dilations) for polygonal regions and polygonal lines. It computes the Minkowski Sum of general polygons. There is a function for removing self-intersections from polygon data.

This package provides functionality to benchmark your CPU and compare against other CPUs. Also provides functions for obtaining system specifications, such as RAM, CPU type, and R version.

This package contains tools for the organization, display, and analysis of the sorts of data frequently encountered in phonetics research and experimentation, including the easy creation of IPA vowel plots, and the creation and manipulation of WAVE audio files.

Hapassoc performs likelihood inference of trait associations with haplotypes and other covariates in generalized linear models (GLMs). The functions are developed primarily for data collected in cohort or cross-sectional studies. They can accommodate uncertain haplotype phase and handle missing genotypes at some SNPs.

This package provides an API for efficient .hic file data extraction with programmatic matrix access. It doesn't store the pointer data for all the matrices, only the one queried, and currently it only supports matrices.

This package provides an interface to Amazon Web Services, including storage, database, and compute services, such as Simple Storage Service (S3), DynamoDB NoSQL database, and Lambda functions-as-a-service.

This package provides a simple, consistent interface to working with XML files in R. It is built on top of the libxml2 C library.

This package provides an R interface to the Lawson-Hanson implementation of an algorithm for non-negative least squares (NNLS). It also allows the combination of non-negative and non-positive constraints.

This package provides a collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in spdep.

This package provides tools for creating detailed dataframes for common statistical approaches and tests. These include parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for ggstatsplot.

This package provides an interface to lm.wfit for fitting dynamic linear models and time series regression relationships.

This package provides useful functions to deal with the haven_labelled and haven_labelled_spss classes introduced by the haven package.

This package implements Dirichlet regression models.

This package provides methods for caching or memoization of objects and results. With this package, any R object can be cached in a key-value storage where the key can be an arbitrary set of R objects. The cache memory is persistent (on the file system).

This package provides fast implementations of functional enrichment analysis methods using C++ via Rcpp. It currently provides Over-Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA). The multilevel GSEA algorithm is derived from the fgsea package. Methods are described in Subramanian et al. (2005) <doi:10.1073/pnas.0506580102> and Korotkevich et al. (2021) <doi:10.1101/060012>.

R/qtl is an extension library for the R statistics system. It is used to analyze experimental crosses for identifying genes contributing to variation in quantitative traits (so-called quantitative trait loci, QTLs).

Using a hidden Markov model, R/qtl estimates genetic maps, to identify genotyping errors, and to perform single-QTL and two-QTL, two-dimensional genome scans.

This package provides a collection of functions to implement a class for univariate polynomial manipulations.

The curl() and curl_download() functions provide highly configurable drop-in replacements for base url() and download.file() with better performance, support for encryption, gzip compression, authentication, and other libcurl goodies. The core of the package implements a framework for performing fully customized requests where data can be processed either in memory, on disk, or streaming via the callback or connection interfaces.

This R package provides a suite of tools to evaluate clustering algorithms, clusterings, and individual clusters.

This package implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow filehash databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets.

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 package provides functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.

This package provides functions to compare a model object to a comparison object. If the objects are not identical, the functions can be instructed to explore various modifications of the objects (e.g., sorting rows, dropping names) to see if the modified versions are identical.

This package finds the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library. It provides approximate, exact searches, fixed radius searches, bd and kb trees.