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R, also known as GNU S, is a strongly functional, highly extensible programming language, with a general interactive shell environment, extensive graphing abilities, a huge set of functions for mathematical and statistical manipulations and exploration of data sets, with even more available in optional libraries/packages. It provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time series analysis, classification, clustering, ...) and graphical techniques. It can display many graphical representations of data from a custom command line, and easily output well designed, publication quality plots, including mathematical symbols and formulae where needed. Great care has been given to the defaults for the minor design choices in graphics, but users have full control. The shell has an option to save one full environment per working directory. R is heavily influenced by two extant languages: Becker, Chambers & Wilks' S, and Sussman's Scheme. R is most similar in appearance to the S language and environment, but the underlying implementation and semantics are derived from Scheme. R can be viewed as an implementation of S which is less standard and more different from the other implementations, S and S-Plus. Much code written for S can run unaltered in R. It is also useful for artificial intelligence and machine learning. It is Open Source, with a GPL license.
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R Project for Statistical Computing - R, also called GNU S, is a strongly functional language and environment to statistically explore data sets, make many graphical displays of data from custom command line, shell has option to save one full environment per working directory. Descriptions, documents, downloads. [Open Source, GPL] An Introduction to R - Derived from an original set of notes describing the S and S-Plus environments. RPy - R from Python. Simple, robust, Python interface to R; manage all kinds of R objects and execute arbitrary R functions, including graphics. Converts all R errors to Python exceptions. Use any R module from within Python. [Open Source, GPL] Comprehensive R Archive Network - Network of FTP and Web servers around the world that store identical, up-to-date, versions of r code, documentation. Books about R - Sells printed copies of free software manuals, including the official R introduction (tutorial) and both reference manuals. [Network Theory Ltd.] Server Clinic: R Handy for Crunching Data - Beginner introduction with code samples, further reading. [developerWorks] R for Windows FAQ - Answers many questions on installing, packages, customizing, Windows features, building from source. R-bloggers - A center for R users to find and read bloggers who write about the statistical programming language, R. The Omega Project for Statistical Computing - Over 30 R packages, libraries, released as part of Omegahat project. Many are bindings to other languages such as Python, Gtk, XML; COM, and SOAP. Most can also be used with S-Plus. [Open Source, BSD-like] Rseek - A custom front-end to Google search engine to assist in finding content related to the R language. R - Books - An extensive list (with brief comments) of R-related books CRAN Task Views - A directory of links to R packages, sorted by topic, by prominant figures in the R community Rcpp - A C++ API for R, along with associated classes to allow for the integration of C++ into R code. The R Journal - An open access, refereed journal of the R project for statistical computing. Rstudio - A powerful and productive user interface for R. It’s free and open source, and works great on Windows, Mac, and Linux. Jobs for R-users - A job board for people and companies looking to hire R users (for programming, data science, teaching). JGR - Java GUI for R - A universal and platform independent GUI for R. It features many tools like advanced editor, object browser, flexible data input/output, and package management.
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