This package provides a unified R graphics backend. Render R graphics fast and easy to many common file formats. It provides a thread safe C interface for asynchronous rendering of R graphics.

This package provides a comprehensive library for date-time manipulations using a new family of orthogonal date-time classes (durations, time points, zoned-times, and calendars) that partition responsibilities so that the complexities of time zones are only considered when they are really needed. Capabilities include: date-time parsing, formatting, arithmetic, extraction and updating of components, and rounding.

Tidygeocoder makes getting data from geocoding services easy. A unified high-level interface is provided for a selection of supported geocoding services and results are returned in tibble format.

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

This package contains routines for logspline density estimation. The function oldlogspline() uses the same algorithm as the logspline package version 1.0.x; i.e., the Kooperberg and Stone (1992) algorithm (with an improved interface). The recommended routine logspline() uses an algorithm from Stone et al (1997).

This is a QTL mapping toolkit for inbred crosses and recombinant inbred lines. It includes maximum likelihood and Bayesian tools.

This package performs augmented backward elimination and checks the stability of the obtained model. Augmented backward elimination combines significance or information based criteria with the change in estimate to either select the optimal model for prediction purposes or to serve as a tool to obtain a practically sound, highly interpretable model.

As a successor of the packages BatchJobs and BatchExperiments, this package provides a parallel implementation of the Map function for high performance computing systems managed by various schedulers. A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.

Estimate generalized additive mixed models via a version of function gamm from the mgcv package, using the lme4 packagefor estimation.

This package provides a forest plot that allows for multiple confidence intervals per row, custom fonts for each text element, custom confidence intervals, text mixed with expressions, and more. The aim is to extend the use of forest plots beyond meta-analyses. This is a more general version of the original rmeta package's forestplot() function and relies heavily on the grid package.

This package provides an all relevant feature selection wrapper algorithm. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).

This package generates version 2 and 4 request signatures for Amazon Web Services (AWS) and provides a mechanism for retrieving credentials from environment variables, AWS credentials files, and EC2 instance metadata. For use on EC2 instances, the package 'aws.ec2metadata' is suggested.

ActiLife generates activity counts from data collected by Actigraph accelerometers. Actigraph is one of the most common research-grade accelerometers. There is considerable research validating and developing algorithms for human activity using ActiLife counts. Unfortunately, ActiLife counts are proprietary and difficult to implement if researchers use different accelerometer brands. The code creates ActiLife counts from raw acceleration data for different accelerometer brands.

This package provides a common framework for optimization of black-box functions for other packages, e.g. mlr3. It offers various optimization methods e.g. grid search, random search and generalized simulated annealing.

This package provides a lightweight unit testing framework. Main features:

1. install tests with the package;

2. test results are treated as data that can be stored and manipulated;

3. test files are R scripts interspersed with test commands, that can be programmed over;

4. fully automated build-install-test sequence for packages;

5. skip tests when not run locally (e.g. on CRAN);

6. flexible and configurable output printing;

7. compare computed output with output stored with the package;

8. run tests in parallel;

9. extensible by other packages;

10. report side effects.

This package arranges data by a set of methods. It uses rearrangers to reorder data points and mutators to change their values. From basic utilities, to centering the greatest value, to swirling in 3-dimensional space, rearrr enables creativity when plotting and experimenting with data.

This package provides miscellaneous small tools and utilities. Many of them facilitate the work with matrices, e.g. inserting rows or columns, creating symmetric matrices, or checking for semidefiniteness. Other tools facilitate the work with regression models, e.g. extracting the standard errors, obtaining the number of (estimated) parameters, or calculating R-squared values.

This package provides tools to create themes and color palettes for the package ggplot2.

This package provides an improved implementation (based on k-nearest neighbors) of the density peak clustering algorithm, originally described by Alex Rodriguez and Alessandro Laio (Science, 2014 vol. 344). It can handle large datasets (> 100,000 samples) very efficiently.

This is a package for visualizing functional data and identifying functional outliers with bagplots, boxplots and rainbow plots.

This package lets you edit and simplify geojson, Spatial, and sf objects. This is a wrapper around the mapshaper JavaScript library to perform topologically-aware polygon simplification, as well as other operations such as clipping, erasing, dissolving, and converting multi-part to single-part geometries.

This package offers features plots for mlr3 objects such as tasks, learners, predictions, benchmark results, tuning instances and filters via the autoplot() generic of ggplot2. The mlr3viz package draws plots with the viridis color palette and applies the minimal theme. Visualizations include barplots, boxplots, histograms, ROC curves, and precision-recall curves.

This package provides a collection of tools to make working with physical measurements easier. One can convert between metric and imperial units, or calculate a dimension's unknown value from other dimensions' measurements.

This package fits multivariate generalized linear mixed models and related models. This is done using Markov chain Monte Carlo techniques.