This package implements a DBI compliant interface to Presto, a distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.

This package lets you create in just a few lines of R code a nice user interface to modify the data or the graphical parameters of one or multiple interactive charts. It is useful to quickly explore visually some data or for package developers to generate user interfaces easy to maintain.

This package provides functions for making low-level API requests to Amazon Web Services. The functions handle building, signing, and sending requests, and receiving responses. They are designed to help build higher-level interfaces to individual services, such as Simple Storage Service (S3).

This package creates and manages simple key-value stores. These can use a variety of approaches for storing the data. This package implements the base methods and support for file system, in-memory and DBI-based database stores.

This package provides color palettes. They are checked for colorblind accessibility from hue, saturation, and lightness value scaling using the Chroma.js Color Palette Helper. See https://gka.github.io/palettes.

This package provides a developer-facing interface to Arrow Database Connectivity (ADBC) for the purposes of driver development, driver testing, and building high-level database interfaces for users. ADBC is an API standard for database access libraries that uses Arrow for result sets and query parameters.

Partition a data frame across multiple worker processes to provide simple multicore parallelism.

ExtRemes is a suite of functions for carrying out analyses on the extreme values of a process of interest; be they block maxima over long blocks or excesses over a high threshold.

This package provides tools for importing and working with bibliographic references. It greatly enhances the bibentry class by providing a class BibEntry which stores BibTeX and BibLaTeX references, supports UTF-8 encoding, and can be easily searched by any field, by date ranges, and by various formats for name lists (author by last names, translator by full names, etc.). Entries can be updated, combined, sorted, printed in a number of styles, and exported. BibTeX and BibLaTeX .bib files can be read into R and converted to BibEntry objects.

This package provides fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. It provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.

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 provides fundamental physical constants (quantity, value, uncertainty, unit) for SI and non-SI units, plus unit conversions based on the data from NIST, USA.

This package is a placeholder for the Bitstream Vera font. It is intended for the fontquiver package.

This package provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling.

This package provides basic infrastructure and some algorithms for the traveling salesperson problem(TSP) (also known as the traveling salesman problem).

This is a package for computation and visualization of the empirical attainment function (EAF) for the analysis of random sets in multi-criterion optimization.

This package provides a system for generating extendable and customizable heatmaps for exploring complex datasets, including big data and data with multiple data types.

This package provides a unified interface to various machine learning algorithms. Confusion matrices are provided too.

This package implements the RUV (Remove Unwanted Variation) algorithms. These algorithms attempt to adjust for systematic errors of unknown origin in high-dimensional data. The algorithms were originally developed for use with genomic data, especially microarray data, but may be useful with other types of high-dimensional data as well. The algorithms require the user to specify a set of negative control variables, as described in the references. The algorithms included in this package are RUV-2, RUV-4, RUV-inv, RUV-rinv, RUV-I, and RUV-III, along with various supporting algorithms.

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 classes and methods for dense and sparse matrices and operations on them using LAPACK and SuiteSparse.

This package provides functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.

This package provides tools for maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting. It extends the lme4 package.

This package creates lots of colorful plots in a multitude of variations. Try a demo of the LSD by running demotour().