This package contains:

• facilities for working with grouped data: do something to data stratified by some variables.

• implementations of least-squares means, general linear contrasts, and

• miscellaneous other utilities.

This package provides a suite of flexible and versatile model fitting and after-fitting functions for the analysis of dose-response data.

This package provides functions for fitting the generalized additive models for location scale and shape introduced by Rigby and Stasinopoulos (2005), doi:10.1111/j.1467-9876.2005.00510.x. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.

This package provides a small collection of interesting and educational machine learning data sets which are used as examples in the mlr3 book Applied machine learning using mlr3 in R https://mlr3book.mlr-org.com, the use case gallery https://mlr3gallery.mlr-org.com, or in other examples. All data sets are properly preprocessed and ready to be analyzed by most machine learning algorithms. Data sets are automatically added to the dictionary of tasks if mlr3 is loaded.

This package adds additional Twitter Bootstrap components to Shiny.

This package contains all the datasets for the spatstat package.

This package provides a simple and flexible way to generate Circos 2D track plot images. The types of plots include: heatmap, histogram, lines, scatterplot, tiles and plot items for further decorations include connector, link (lines and ribbons), and text (gene) label. All functions require only R graphics packages that comes with the base installation.

This package provides tools to execute arbitrary R or C functions some time after the current time, after the R execution stack has emptied.

This package contains a function to do exact Hardy-Weinburg testing (using Fisher's test) for SNP genotypes as typically obtained in a Genome Wide Association Study (GWAS).

Building on the infrastructure provided by the lattice package, this package provides several new high-level graphics functions and methods, as well as additional utilities such as panel and axis annotation functions.

RestRserve is an R web API framework for building high-performance AND robust microservices and app backends. With Rserve backend on UNIX-like systems it is parallel by design. It will handle incoming requests in parallel - each request in a separate fork.

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 tools for multiple imputation of missing data in multilevel modeling. It includes a user-friendly interface to the packages pan and jomo, and several functions for visualization, data management and the analysis of multiply imputed data sets.

Tools for working with and comparing sets of points and intervals.

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions.

This package provides an interface to Amazon Web Services application integration services, including Simple Queue Service (SQS) message queue, Simple Notification Service (SNS) publish/subscribe messaging, and more.

This package provides tools for depth functions methodology applied to multivariate analysis. Besides allowing calculation of depth values and depth-based location estimators, the package includes functions or drawing contour plots and perspective plots of depth functions. Euclidean and spherical depths are supported.

This package provides tools for accessing the Botanical Information and Ecology Network (BIEN) database. The BIEN database contains cleaned and standardized botanical data including occurrence, trait, plot and taxonomic data. This package provides functions that query the BIEN database by constructing and executing optimized SQL queries.

This package contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX code, and recoding variables.

R-coop offers implementations of covariance, correlation and cosine similarity. The implementations are fast and memory-efficient and their use is resolved automatically based on the input data, handled by R's S3 methods. Full descriptions of the algorithms and benchmarks are available in the package vignettes.

This package provides functions for Meta-analysis Burden Test, Sequence Kernel Association Test (SKAT) and Optimal SKAT (SKAT-O) by Lee et al. (2013) <doi:10.1016/j.ajhg.2013.05.010>. These methods use summary-level score statistics to carry out gene-based meta-analysis for rare variants.

Generate a colorized diff of two R objects for an intuitive visualization of their differences.

This package is a collection of baseline correction algorithms. Beside those it provides a framework and a Tcl/Tk enabled GUI for optimizing baseline algorithm parameters. Typical use is the removal of the background effects from spectra, which are originating from various types of spectroscopy and spectrometry. Also, there is a possibility of optimizing this with regard to regression or classification results. Correction methods include polynomial fitting, weighted local smoothers and many more.

This package provides helper functions to install and maintain the LaTeX distribution named TinyTeX, a lightweight, cross-platform, portable, and easy-to-maintain version of TeX Live. This package also contains helper functions to compile LaTeX documents, and install missing LaTeX packages automatically.