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R logo. R packages are extensions to the R statistical programming language.R packages contain code, data, and documentation in a standardised collection format that can be installed by users of R, typically via a centralised software repository such as CRAN (the Comprehensive R Archive Network).
The R Consortium is a Linux Foundation project to develop R infrastructure. The R Journal is an open access, academic journal which features short to medium-length articles on the use and development of R. It includes articles on packages, programming tips, CRAN news, and foundation news. The R community hosts many conferences and in-person ...
The R Journal is a peer-reviewed open-access scientific journal published by The R Foundation since 2009. [1] It publishes research articles in statistical computing that are of interest to users of the R programming language. The journal includes a News and Notes section that supersedes the R News newsletter, which was published from 2001 to 2008.
RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser .
For the R programming language, the Comprehensive R Archive Network (CRAN) runs tests routinely. To understand how this is valuable, imagine a situation with two developers, Sally and John. Sally contributes a package A. Sally only runs the current version of the software under one version of Microsoft Windows, and has only tested it in that ...
Part of OS X 10.7 and available as an update for OS X 10.6; Fink: A port of dpkg, it is one of the earliest package managers for macOS; Homebrew: Command-Line Interface-based package manager, known for its ease-of-use and extensibility. MacPorts: Formerly known as DarwinPorts, based on FreeBSD Ports (as is macOS itself);
jamovi is an open source graphical user interface for the R programming language. [3] It is used in statistical research, especially as a tool for ANOVA (analysis of variance) and to understand statistical inference. [4] [5] It also can be used for linear regression, [6] mixed models and Bayesian models. [7]
With the release of version 0.3.0 in April 2016 [4] the use in production and research environments became more widespread. The package was reviewed several months later on the R blog The Beginner Programmer as "R provides a simple and very user friendly package named rnn for working with recurrent neural networks.", [5] which further increased usage.