This package provides a fast reimplementation of several density-based algorithms of the DBSCAN family. It includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and hierarchical DBSCAN (HDBSCAN), the ordering algorithm ordering points to identify the clustering structure (OPTICS), shared nearest neighbor clustering, and the outlier detection algorithms local outlier factor (LOF) and global-local outlier score from hierarchies (GLOSH). The implementations use the kd-tree data structure for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided.

This package provides a set of predicates and assertions for checking the properties of code. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

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

This package provides R bindings to OpenSSL libssl and libcrypto, plus custom SSH pubkey parsers. It supports RSA, DSA and NIST curves P-256, P-384 and P-521. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES block cipher is used in CBC mode for symmetric encryption; RSA for asymmetric (public key) encryption. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and bignum math methods for manually performing crypto calculations on large multibyte integers.

This package provides multiple pairwise tests.

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 helps you with creation and use of R repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are supported: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.

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 a collection of perceptually uniform color maps made by Peter Kovesi (2015) "Good Colour Maps: How to Design Them" <arXiv:1509.03700> at the Centre for Exploration Targeting (CET).

This package provides a simple and intuitive pipe-friendly framework, coherent with the tidyverse design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix.

This package provides a light weight implementation of the standard distribution functions for the inverse gamma distribution, wrapping those for the gamma distribution in the stats package.

This package provides functions for fitting and plotting SITAR growth curve models. SITAR is a shape- invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales.

This package provides a toolbox for working with base types, core R features like the condition system, and core Tidyverse features like tidy evaluation.

This package provides functions to compute the distribution function of quadratic forms in normal variables using Imhof's method, Davies's algorithm, Farebrother's algorithm or Liu et al.'s algorithm.

This package improves the user experience of Shiny apps by helping to provide feedback when required inputs are missing, or input values are not valid.

Provides implementations of functions which have been introduced in R since version 3.0.0. The backports are conditionally exported which results in R resolving the function names to the version shipped with R (if available) and uses the implemented backports as fallback. This way package developers can make use of the new functions without worrying about the minimum required R version.

This package provides functions and data to construct technical trading rules with R.

This package provides an alternative to R's built-in functionality for handling regular expressions, based on the Onigmo library. It offers first-class compiled regex objects, partial matching and function-based substitutions, amongst other features.

mlr3misc provides frequently used helper functions and assertions used in mlr3 and its companion packages. It comes with helper functions for functional programming, for printing, to work with data.table, as well as some generally useful R6 classes. This package also supersedes the package BBmisc.

This package converts between R and Simple Feature sf objects, without depending on the Simple Feature library. Conversion functions are available at both the R level, and through Rcpp.

ACDm is a package for Autoregressive Conditional Duration (ACD, Engle and Russell, 1998) models. It creates trade, price or volume durations from transactions (tic) data, performs diurnal adjustments, fits various ACD models and tests them.

This package provides an implementation of bee swarm plots. The bee swarm plot is a one-dimensional scatter plot like stripchart, but with closely-packed, non-overlapping points.

This package provides functions to export graphics drawn with package grid to SVG format. Extra functions provide access to SVG features that are not available in standard R graphics, such as hyperlinks, animation, filters, masks, clipping paths, and gradient and pattern fills.

Tools for performing model selection and model averaging. Automated model selection through subsetting the maximum model, with optional constraints for model inclusion. Model parameter and prediction averaging based on model weights derived from information criteria (AICc and alike) or custom model weighting schemes.