R programming language
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The R programming language, sometimes described as "GNU S", is a programming language and software environment for statistical computing and graphics. 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 collaborative effort from a core team of developers from around the world.
R is considered by its developers to be an implementation of the S programming language, with semantics derived from Scheme. The commercial implementation of S is S-PLUS.
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.
Features
R supports a wide variety of statistical techniques. R is also 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 over 700 more available at the comprehensive R archive network (CRAN) as of 2006. One of R's strengths is its graphical facilities, which produce publication-quality graphs that can include mathematical symbols.Bioinformatics and R
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 practitioners requiring an environment for statistical computation and software development, it can also be used as a general matrix calculation toolbox with comparable benchmark results [link] to GNU Octave and its proprietary counterpart, MATLAB.It should not be confused with the R package [link], a collection of programs for multidimensional and spatial analysis available on Macintosh and VAX/VMS systems.
The Gnumeric developers are cooperating with the R project for improving the accuracy of Gnumeric.
Productivity tools
There are several GUIs for R, including Many editors have specialised modes for R, including- Emacs (Emacs Speaks Statistics),
- jEdit [link],
- Kate [link],
- Syn [link], and
- [Tinn-R],
- and there is an [R plug-in] for the Eclipse IDE framework.
R newsletter
R provides a freely available downloadable newsletter [link] featuring statistical computing and development articles in the R programming language that might be of interest to both users and developers. It has been in press since January 2001 and is released two to three times a year. The editors are themselves volunteers within the R project. The newsletter is compiled and formatted using the LaTeX typesetting language. LaTeX style files which provide the format style ( .sty extension) and references (.bib extension) are also available for download.See also
- Journal of Statistical Software -- peer-reviewed journal publishing many R related papers
- CRAN -- Comprehensive R Archive Network
External links
- [The R Project for Statistical Computing]
- [The CRAN (Comprehensive R Archive Network) Project]
- [Web-based interface to R]
- [The R Reference Manual - Base Package] by the R Development Core Team. ISBN 0-9546120-0-0 (vol. 1), ISBN 0-9546120-1-9 (vol. 2)
- [R Wiki] User contributed R documentation and how to information.
- [The R Graph Gallery] or the [RGraphExampleLibrary] show examples of graphics generated by R
- [Robert Gentleman's site]
- [Ross Ihaka's site]
- [Rcmdr, an open source GUI for R]
- [List of IDEs and script editors for R]
- [Tinn-R, an advanced open source script editor for R under Windows]
- [Tutorial: Producing Simple Graphs using the R Programming Language]
- [Creating Charts and Graphs with GNU R]
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