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Content Derived from Wikipedia article on R Programming Language

R (programming language)

From Wikipedia, the free encyclopedia

Screenshot of Mac OS X RAqua desktop

Developer: R Foundation

Latest release: 2.4.0 / October 3, 2006

OS: Cross-platform

Use: Programming language

License: GNU General Public License

Website: http://www.r-project.org/

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 developed by the R core team. R is considered by its developers to be an implementation of the S programming language, with semantics derived from Scheme.

R is widely used for statistical software development and data analysis, and has become a de-facto standard among statisticians for the development of statistical software.[1] R's source code is freely available under the GNU General Public License, and pre-compiled binary versions are provided for Microsoft Windows, Mac OS X, and several Linux and other Unix-like operating systems. R uses a command line interface, though several graphical user interfaces are available.

Contents

1 Features

2 Development

3 Productivity tools

4 R newsletter

5 See also

6 References

7 External links

Features

R supports a wide variety of statistical and numerical 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. Due to its S heritage, R has stronger object-oriented programming facilities than most statistical computing languages. Extending R is also eased by its permissive lexical scoping rules.[2]

Another of R's strengths is its graphical facilities, which produce publication-quality graphs which can include mathematical symbols.

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 to GNU Octave and its proprietary counterpart, MATLAB.[3]

Development

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, such as Affymetrix and cDNA microarray object-oriented data handling and analysis tools.

The Gnumeric developers have cooperated with the R project to improve the accuracy of Gnumeric.[4]

Productivity tools

There are several graphical user interfaces for R, including JGR, RKWard, SciViews-R and Rcmdr.

Many editors have specialised modes for R, including:

Emacs (Emacs Speaks Statistics)

jEdit[5]

Kate[6]

Syn[7]

Tinn-R[8]

Vim

TextMate

An R plug-in for the Eclipse IDE framework.[9]

R newsletter

A free newsletter is released online two to three times a year featuring statistical computing and development articles that might be of interest to both users and developers of R. It has been in press since January 2001.[10]

See also

Journal of Statistical Software

References

^ Fox, John and Andersen, Robert (January 2005). "Using the R Statistical Computing Environment to Teach Social Statistics Courses" (PDF). Department of Sociology, McMaster University. Retrieved on 2006-08-03.

^ Jackman, Simon (Spring 2003). "R For the Political Methodologist" (PDF). The Political Methodologist 11 (1): 20–22. Retrieved on 2006-08-03.

^ http://www.sciviews.org/benchmark

^ Gnumeric, Team (2004-12-19). Gnumeric 1.4 is Here!. The GNOME Project. Retrieved on 2006-04-30.

^ http://community.jedit.org/?q=node/view/2339

^ http://www.uni-kiel.de/agrarpol/ahenningsen/app-econ/R.xml.zip

^ http://syn.sourceforge.net/

^ http://sourceforge.net/projects/tinn-r

^ http://www.walware.de/goto/statet

^ http://cran.r-project.org/doc/Rnews/

Crawley, M.J. (2002) Statistical Computing. John Wiley, New York.

Crawley, M.J. (2005) Statistics: An Introduction Using R. John Wiley, New York

External links

Wikibooks has a book on the topic of

R ProgrammingThe R Project for Statistical Computing

R Search Engine (helps with ambiguity of R as a search term)

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

Statistical programming with R is a three part series (part 1, part 2, part 3), by David Mertz and Brad Huntting, introducing both the functional programming style of R, and explaining how to express object-oriented programs.

Robert Gentleman's site

Ross Ihaka's site

Retrieved from http://en.wikipedia.org/wiki/R_%28programming_language%29

End of Wikipedia content, http://en.wikipedia.org/wiki/R_programming_language

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