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R (programming language)

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R
Designed byRoss Ihaka and Robert Gentleman
DeveloperR Development Core Team
Stable release
2.6.0 / October 3, 2007
Preview release
Through SVN
OSCross-platform
LicenseGNU General Public License
Websitehttp://www.r-project.org/
Influenced by
S

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 at the University of Auckland, New Zealand, and is now developed by the R Development Core Team. R is considered by its developers to be an implementation of the S programming language, with semantics derived from Scheme. The name R comes partly from the first name of the two original authors, and partly as a word play on the name 'S'.[1]

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.[2] 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.

Features

File:R gui on os x.png
The R gui running the general linear model demo on Mac OS X.

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. 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.[3]

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 (version < 7).[4]

Packages

The capabilities of R are extended through user-submitted packages, which allow specialized statistical techniques, graphical devices, as well as programming interfaces and import/export capabilities to many external data formats. These packages are developed in R, LaTeX, Java, and often C and Fortran. A core set of packages are included with the installation of R, with over 1000 more available at the Comprehensive R Archive Network. Notable packages are listed along with comments on the official R Task View pages.

Development

The bioinformatics community has seeded a successful effort to use R for the analysis of data from molecular biology laboratories. The bioconductor project, which 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.[5]

Milestones

Productivity tools

There are several graphical user interfaces for R, including:

Many editors have specialised modes for R, including:

R functionality has been made accessible from the Python programming language by the RPy[12] interface package.

CRAN

R and user-submitted packages are commonly distributed through CRAN, which is an acronym for the Comprehensive R Archive Network. There are over 60 CRAN mirrors world-wide, with the head-node (http://cran.r-project.org/) located in Vienna, Austria.

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.[13]

See also

References

  1. ^ The R FAQ: Why is R named R ?. Last accessed 31 July 2007.
  2. ^ 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 2006-08-03. {{cite journal}}: Cite journal requires |journal= (help)CS1 maint: multiple names: authors list (link)
  3. ^ Jackman, Simon (Spring 2003). "R For the Political Methodologist" (PDF). The Political Methodologist. 11 (1). Political Methodology Section, American Political Science Association: 20–22. Retrieved 2006-08-03.
  4. ^ http://www.sciviews.org/benchmark
  5. ^ Gnumeric, Team (2004-12-19). "Gnumeric 1.4 is Here!". The GNOME Project. Retrieved 2006-04-30. {{cite web}}: Check date values in: |date= (help)
  6. ^ http://rattle.togaware.com
  7. ^ http://community.jedit.org/?q=node/view/2339
  8. ^ http://www.kate-editor.org/syntax/2.5/r.xml
  9. ^ http://syn.sourceforge.net/
  10. ^ http://sourceforge.net/projects/tinn-r
  11. ^ http://www.walware.de/goto/statet
  12. ^ http://rpy.sourceforge.net
  13. ^ http://cran.r-project.org/doc/Rnews/
  • Everitt, B. S. and Hothorn, T. (2006). A Handbook of Statistical Analyses Using R. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help)CS1 maint: multiple names: authors list (link) [1]
  • Faraway, J. J. (2004). Linear Models with R. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help) [2]
  • Faraway, J. J. (2005). Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help) [3]
  • Jureckova, J. and Picek, J. (2005). Robust Statistical Methods with R. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help)CS1 maint: multiple names: authors list (link) [4]
  • Maindonald, J. and Braun, W. J. (2007). Data Analysis and Graphics Using R, second edition. Cambridge University Press. {{cite book}}: Cite has empty unknown parameter: |1= (help)CS1 maint: multiple names: authors list (link) [5]
  • Murrell, P. (2005). R Graphics. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help) [6]
  • Murtagh, F. (2005). Correspondence Analysis and Data Coding with Java and R. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help) [7]
  • Verzani, J. (2004). Using R for Introductory Statistics. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help) [8]
  • Wood, S. N. (2006). Generalized Additive Models: An Introduction with R. Chapman & Hall/CRC. {{cite book}}: Cite has empty unknown parameter: |1= (help) [9]
  • Crawley, M.J. (2002) Statistical Computing. John Wiley, New York.
  • Crawley, M.J. (2005) Statistics: An Introduction Using R. John Wiley, New York.
  • Crawley, M.J. (2007) The R Book. John Wiley, New York.
  • Ihaka, R., and Gentleman, R. (1996) R: A Language for Data Analysis and Graphics, Journal of Computational and Graphical Statistics, Vol. 5, No. 3, pp. 299-314, doi:10.2307/1390807.
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