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- The R Project for Statistical Computing
The R Project for Statistical Computing Getting Started R is a free software environment for statistical computing and graphics It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS To download R, please choose your preferred CRAN mirror
- R-4. 5. 1 for Windows - The Comprehensive R Archive Network
Patches to this release are incorporated in the r-patched snapshot build A build of the development version (which will eventually become the next major release of R) is available in the r-devel snapshot build
- R: What is R? - The R Project for Statistical Computing
R is a language and environment for statistical computing and graphics It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT T, now Lucent Technologies) by John Chambers and colleagues
- An Introduction to R
This is an introduction to R (“GNU S”), a language and environment for statistical computing and graphics R is similar to the award-winning 1 S system, which was developed at Bell Laboratories by John Chambers et al
- R: Documentation
Browsable HTML versions of the manuals, help pages and NEWS for the developing versions of R “ R-patched ” and “ R-devel ”, updated daily CRAN has a growing list of contributed documentation in a variety of languages
- The Comprehensive R Archive Network
CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R Please use the CRAN mirror nearest to you to minimize network load
- R for Windows
Package developers might want to contact Uwe Ligges directly in case of questions suggestions related to Windows binaries You may also want to read the R FAQ and R for Windows FAQ Note: CRAN does some checks on these binaries for viruses, but cannot give guarantees Use the normal precautions with downloaded executables
- The Comprehensive R Archive Network
R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc
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