This package provides data structures and algorithms for k-ary relations with arbitrary domains, featuring relational algebra, predicate functions, and fitters for consensus relations.

This package provides auxiliary functions and data sets for "Ecological Models and Data", a book presenting maximum likelihood estimation and related topics for ecologists (ISBN 978-0-691-12522-0).

This package provides tools for the statistical modelling of spatial extremes using max-stable processes, copula or Bayesian hierarchical models. More precisely, this package allows (conditional) simulations from various parametric max-stable models, analysis of the extremal spatial dependence, the fitting of such processes using composite likelihoods or least square (simple max-stable processes only), model checking and selection and prediction.

latex2exp parses and converts LaTeX math formulas to R's plotmath expressions, used to enter mathematical formulas and symbols to be rendered as text, axis labels, etc. throughout R's plotting system.

Similarly to the FNN package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. The implementation is based on cover trees introduced by Alina Beygelzimer, Sham Kakade, and John Langford (2006) doi:10.1145/1143844.1143857.

This package provides a common interface to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. R, Spark, Stan, etc).

This package is designed to be used with Rscript to write shebang scripts that accept short and long options. Many users will prefer to use the packages optparse or argparse which add extra features like automatically generated help options and usage texts, support for default values, positional argument support, etc.

This package provides an R tool for estimating and partitioning R2 in generalized linear mixed models (GLMMs) based on predictor variance.

This package provides tools to identify global ("unknown" or "free") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal. The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.

This package provides an R interface to the JAGS MCMC library. JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation.

This package provides implementation of methods for estimation of quantitative maps from Multi-Parameter Mapping (MPM) acquisitions including adaptive smoothing methods in the framework of the ESTATICS model. The smoothing method is described in Mohammadi et al. (2017). <doi:10.20347/WIAS.PREPRINT.2432>. Usage of the package is also described in Polzehl and Tabelow (2019), Magnetic Resonance Brain Imaging, Chapter 6, Springer, Use R! Series. <doi:10.1007/978-3-030-29184-6_6>.

In S3 generics, it's useful to take ... so that methods can have additional arguments. But this flexibility comes at a cost: misspelled arguments will be silently ignored. The ellipsis package is an experiment that allows a generic to warn if any arguments passed in ... are not used.

This package provides tools to compute Gower's distance (or similarity) coefficient between records, and to compute the top-n matches between records. Core algorithms are executed in parallel on systems supporting OpenMP.

This package provides a custom CSS/HTML or GIF/image file for the loading screen in R Shiny. It also can use the marquee to have a custom text loading screen.

This package provides extended data frames, with a special data frame column which contains two indexes, with potentially a nesting structure.

The purpose of this package is to factor out logic and math common to Item Factor Analysis fitting, diagnostics, and analysis. It is envisioned as core support code suitable for more specialized IRT packages to build upon. Complete access to optimized C functions is made available with R_RegisterCCallable().

This package provides C code used by the wmtsa, fractal, and sapa R packages.

This package provides high level functions for parallel programming with Rcpp. For example, the parallelFor() function can be used to convert the work of a standard serial for loop into a parallel one and the parallelReduce() function can be used for accumulating aggregates or other values.

This package provides an improved heatmap package. It is completely compatible with the original R function heatmap, and provides more powerful and convenient features.

This package provides an interface to the rich display capabilities of Jupyter front-ends (e.g. Jupyter Notebook). It is designed to be used from a running IRkernel session.

This package provides tidy tools for quantifying how well a model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).

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.

mlr3 enables efficient, object-oriented programming on the building blocks of machine learning. It provides R6 objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While mlr3 focuses on the core computational operations, add-on packages provide additional functionality.

A workflow is a combination of a model and preprocessors (e.g, a formula, recipe, etc.). In order to try different combinations of these, an object can be created that contains many workflows. There are functions to create workflows en masse as well as training them and visualizing the results.