This package implements an empirical Bayes approach for large-scale hypothesis testing and false discovery rate estimation.

This package contains general data structures and functions for longitudinal data with multiple variables, repeated measurements, and irregularly spaced time points. It also implements a shrinkage estimator of dynamical correlation and dynamical covariance.

This package provides extensions to ggplot2, respecting the grammar of its graphics paradigm.

This package provides a header only, C++11 interface to R's C interface. Compared to other approaches cpp11 strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with ALTREP vectors.

This package provides high performance container data types such as queues, stacks, deques, dicts and ordered dicts.

An R interface to the Pushbullet messaging service which provides fast and efficient notifications (and file transfer) between computers, phones and tablets.

The objective of this package is to perform inference using an expressive statistical grammar that coheres with the Tidy design framework.

This package provides various R programming tools for data manipulation, including:

• medical unit conversions

• combining objects

• character vector operations

• factor manipulation

• obtaining information about R objects

• generating fixed-width format files

• extricating components of date and time objects

• operations on columns of data frames

• matrix operations

• operations on vectors and data frames

• value of last evaluated expression

• wrapper for sample that ensures consistent behavior for both scalar and vector arguments

This package provides e-statistics (energy) tests and statistics for multivariate and univariate inference, including distance correlation, one-sample, two-sample, and multi-sample tests for comparing multivariate distributions, are implemented. Measuring and testing multivariate independence based on distance correlation, partial distance correlation, multivariate goodness-of-fit tests, clustering based on energy distance, testing for multivariate normality, distance components (disco) for non-parametric analysis of structured data, and other energy statistics/methods are implemented.

This package provides the prediction() function, a type-safe alternative to predict() that always returns a data frame. The package currently supports common model types (e.g., "lm", "glm") from the stats package, as well as numerous other model classes from other add-on packages.

This package implements a self-sufficient reader and writer for flat Parquet files. It can read most Parquet data types. It can write many R data types, including factors and temporal types.

This package computes fast (relative to other implementations) approximate Shapley values for any supervised learning model. Shapley values help to explain the predictions from any black box model using ideas from game theory; see doi.org/10.1007/s10115-013-0679-x for details.

This package provides a ggplot2 extension that enables the rendering of complex formatted plot labels (titles, subtitles, facet labels, axis labels, etc.). Text boxes with automatic word wrap are also supported.

This package offers quick statistical hypothesis testing for matrix rows/columns. The main goals are speed through vectorization, detailed and user-friendly output, and compatibility with tests implemented in R.

This package implements methods to perform fast approximate K-nearest neighbor search on the input matrix. The algorithm is based on the N2 implementation of an approximate nearest neighbor search using hierarchical NSW graphs.

This package contains utility functions for the spatstat package which may also be useful for other purposes.

This package provides procedures to create preliminary exploratory data visualisations of an entire dataset to identify problems or unexpected features using ggplot2.

This package provides a set of utilities for client/server computing with R, controlling a remote R session (the server) from a local one (the client).

This package interacts with a suite of web services for chemical information. Sources include: Alan Wood's Compendium of Pesticide Common Names, Chemical Identifier Resolver, ChEBI, Chemical Translation Service, ChemSpider, ETOX, Flavornet, NIST Chemistry WebBook, OPSIN, PubChem, SRS, Wikidata.

This package provides tools for clustering and principal component analysis (with robust methods, and parallelized functions).

This package implements shadowtextGrob() for grid and geom_shadowtext() layer for ggplot2. These functions draw text grob with background shadow.

Deciding what resolution to use can be a difficult question when approaching a clustering analysis. One way to approach this problem is to look at how samples move as the number of clusters increases. This package allows you to produce clustering trees, a visualization for interrogating clusterings as resolution increases.

This package is a compatibility wrapper to replace the orphaned package by Romain Francois. New applications should use the openssl or base64enc package instead.

This package provides a variety of descriptive multivariate analyses with the singular value decomposition, such as principal components analysis, correspondence analysis, and multidimensional scaling. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.