R programming language

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The R programming language (or just "R"), sometimes described as "GNU S", is a mathematical language and environment used for statistical analysis and display. It was originally created by Ross Ihaka and Robert Gentleman (hence the name R) at the University of Auckland, New Zealand, and is now steadily developed further by a large community around the world.

It is based upon S, which was developed by John Chambers of Bell Laboratories and described in the paper "Evolution of the S Language" [1]. R is considered by its developers to be an implementation of S, with semantics derived from Scheme. The commercial implementation of S is S-PLUS [2].

R's source code is freely available under the GNU GPL and pre-compiled binary versions are provided for Windows, Macintosh, and many Unix operating systems. There are several GUIs for R, including RKWard, SciViews-R [3], and Rcmdr [4]. Many editors have specialised modes for R, including Emacs (Emacs Speaks Statistics), jEdit [5], Kate (text editor) [6], and Tinn [7], and there is an R plug-in for the Eclipse IDE framework.

R is highly extensible through the use of packages, which are user submitted libraries for specific functions or specific areas of study. A core set of packages are included with the installation of R, with many more available at the comprehensive R archive network, CRAN. The bioinformatics community has seeded a successful effort to use R for the analysis of data from molecular biology laboratories. The bioconductor project started in the fall of 2001 provides R packages for the analysis of genomic data. e.g. Affymetrix and cDNA microarray object-oriented data handling and analysis tools.

Comparison with other programs

Although R is mostly used by statisticians, and other people in need of statistics, it can also be used as a general matrix calculation toolbox in a program such as GNU Octave or its proprietary counterpart, MATLAB.

It should not be confused with the R package [8], a collection of programs for multidimensional and spatial analysis available on Macintosh and VAX/VMS systems.

See also

External links

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