This package provides methods to create, store, access, and manipulate large matrices. Matrices are allocated to shared memory and may use memory-mapped files.

This package lets you record test suite HTTP requests and replay them during future runs. It works by hooking into the webmockr R package for matching HTTP requests by various rules, and then caching real HTTP responses on disk in cassettes. Subsequent HTTP requests matching any previous requests in the same cassette use a cached HTTP response.

This package provides a set of tools to perform Quantitative Trait Locus (QTL) analysis in experimental crosses. It is a reimplementation of the R/qtl package to better handle high-dimensional data and complex cross designs. Broman et al. (2018) <doi:10.1534/genetics.118.301595>.

This is a framework for fitting multiple caret models. It uses the same re-sampling strategy as well as creating ensembles of such models. Use caretList to fit multiple models and then use caretEnsemble to combine them greedily or caretStack to combine them using a caret model.

This package provides tools for defensive programming. It is inspired by purrr mappers and based on rlang. Attempt extends and facilitates defensive programming by providing a consistent grammar, and a set of functions for common tests and conditions. Attempt only depends on rlang, and focuses on speed, so it can be integrated with other functions and used in the data analysis.

This is a package for slanted matrices and ordered clustering for better visualization of similarity data.

This package enables the translation of ggplot2 graphs to an interactive web-based version and/or the creation of custom web-based visualizations directly from R. Once uploaded to a plotly account, plotly graphs (and the data behind them) can be viewed and modified in a web browser.

This package generates graphics with embedded details from statistical tests. Statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous or categorical data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses.

This package provides configurable progress bars. They may include percentage, elapsed time, and/or the estimated completion time. They work in terminals, in Emacs ESS, RStudio, Windows Rgui, and the macOS R.app. The package also provides a C++ API, that works with or without Rcpp.

This package constructs basis functions of B-splines, M-splines, I-splines, convex splines (C-splines), periodic splines, natural cubic splines, generalized Bernstein polynomials, their derivatives, and integrals (except C-splines) by closed-form recursive formulas. It also contains a C++ head-only library integrated with Rcpp.

This package provides functions to compute insolation on tilted surfaces, computes atmospheric transmittance and related parameters such as: Earth radius vector, declination, sunset and sunrise, daylength, equation of time, vector in the direction of the sun, vector normal to surface, and some atmospheric physics.

This package creates a lightweight way to add markdown helpfiles to Shiny apps, using modal dialog boxes, with no need to observe each help button separately.

This package provides a collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values.

This package computes the Kendall rank correlation and Mann-Kendall trend test.

This package provides different high-level graphics functions for displaying large datasets, displaying circular data in a very flexible way, finding local maxima, brewing color ramps, drawing nice arrows, zooming 2D-plots, creating figures with differently colored margin and plot region. In addition, the package contains auxiliary functions for data manipulation like omitting observations with irregular values or selecting data by logical vectors, which include NAs. Other functions are especially useful in spectroscopy and analyses of environmental data: robust baseline fitting, finding peaks in spectra, converting humidity measures.

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 provides functions for drawing and calibrating samples.

This package provides some functions for sample classification in microarrays.

This package provides functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.

In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The NNG-powered mirai R package by Gao (2023) <doi:10.5281/zenodo.7912722> is a scheduler that efficiently processes these intense workloads. The crew package extends mirai with a unifying interface for third-party worker launchers.

This package contains the core survival analysis routines, including definition of Surv objects, Kaplan-Meier and Aalen-Johansen (multi-state) curves, Cox models, and parametric accelerated failure time models.

This package provides utilities to understand and describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion such as Highest Density Interval (HDI), and indices used for null-hypothesis testing (such as ROPE percentage and pd).

This package provides a C++ header library for using the libsoda-cxx library with R. The C++ header reimplements the lsoda function from the ODEPACK library for solving initial value problems for first order ordinary differential equations. The C++ header can be used by other R packages by linking against this package. The C++ functions can be called inline using Rcpp. Finally, the package provides an ode function to call from R.

This package provides linear models based on Theil-Sen single median and Siegel repeated medians. They are very robust (29 or 50 percent breakdown point, respectively), and if no outliers are present, the estimators are very similar to OLS.