This package provides JSON parsing capability through the Rapidjson library.

The r-ggformula introduces a family of graphics functions, gf_point(), gf_density(), and so on, bring the formula interface to ggplot(). This captures and extends the excellent simplicity of the lattice-graphics formula interface, while providing the intuitive capabilities of r-ggplot2.

This package provides a multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution.

Calculate generalized R-squared, partial R-squared, and partial correlation coefficients for generalized linear (mixed) models (including quasi models with well defined variance functions).

This package provides data sets for econometrics, including political science.

This package provides functions that implement the known population median test.

Currently there are many functions in S-PLUS that are missing in R. To facilitate the conversion of S-PLUS packages to R packages, this package provides some missing S-PLUS functionality in R.

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

The Ziggurat pseudo-random number generator (or PRNG) offers a lightweight and very fast PRNG for the normal, exponential, and uniform distributions. It is provided here in a small zero-dependency package. It can be used from R as well as from C/C++ code in other packages as is demonstrated by four included sample packages using four distinct methods to use the PRNG presented here in client package.

Uniform manifold approximation and projection is a technique for dimension reduction. This package provides an interface to the UMAP algorithm in R, including a translation of the original algorithm into R.

These utilities facilitate the programmatic manipulations of formulas, expressions, calls, assignments and other R language objects. These objects all share the same structure: a left-hand side, operator and right-hand side. This package provides methods for accessing and modifying this structures as well as extracting and replacing names and symbols from these objects.

This package provides functions for Maximum Likelihood (ML) estimation, non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the Maximum Likelihood viewpoint. It also includes a number of convenience tools for testing and developing your own models.

Convert a logical vector or a vector of p-values or a correlation, difference, or distance matrix into a display identifying the pairs for which the differences were not significantly different.

This package implements an efficient O(n) algorithm based on bucket-sorting for fast computation of standard clustering comparison measures. Available measures include adjusted Rand index (ARI), normalized information distance (NID), normalized mutual information (NMI), adjusted mutual information (AMI), normalized variation information (NVI) and entropy.

This package integrates sophisticated mixed modelling methods with a whole genome approach to detecting significant QTL in linkage maps.

This package provides a violin plot, which is a combination of a box plot and a kernel density plot.

This package provides a friendly interface for the construction of regular expressions. Regular expressions are a very powerful feature, however they are often difficult to interpret. Rex allows you to build complex regular expressions from human readable expressions

This package provides output formats and utilities for authoring books and technical documents with R Markdown.

Sensitivity (or recall or true positive rate), false positive rate, specificity, precision (or positive predictive value), negative predictive value, misclassification rate, accuracy, F-score---these are popular metrics for assessing performance of binary classifiers for certain thresholds. These metrics are calculated at certain threshold values. Receiver operating characteristic (ROC) curve is a common tool for assessing overall diagnostic ability of the binary classifier. Unlike depending on a certain threshold, area under ROC curve (also known as AUC), is a summary statistic about how well a binary classifier performs overall for the classification task. The ROCit package provides flexibility to easily evaluate threshold-bound metrics.

This package computes exact conditional p-values and quantiles using an implementation of the Shift-Algorithm by Streitberg & Roehmel.

In order to smoothly animate the transformation of polygons and paths, many aspects needs to be taken into account, such as differing number of control points, changing center of rotation, etc. The transformr package provides an extensive framework for manipulating the shapes of polygons and paths and can be seen as the spatial brother to the tweenr package.

Cluster ensembles are collections of individual solutions to a given clustering problem which are useful or necessary to consider in a wide range of applications. This R package provides an extensible computational environment for creating and analyzing cluster ensembles, with basic data structures for representing partitions and hierarchies, and facilities for computing on them, including methods for measuring proximity and obtaining consensus and secondary clusterings.

This package provides classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).

This is a package for simplified document database access and manipulation, providing a common API across supported NoSQL databases Elasticsearch, CouchDB, MongoDB as well as SQLite/JSON1, PostgreSQL, and DuckDB.