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!-- 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. !-- R can be considered as a different implementation of S. There are some !-- important differences, but much code written for S runs unaltered under R. !-- !--
!-- R provides a wide variety of statistical (linear and nonlinear !-- modelling, classical statistical tests, time-series analysis, !-- classification, clustering, ...) and graphical techniques, and is !-- highly extensible. The S language is often the vehicle of choice for !-- research in statistical methodology, and R provides an Open Source !-- route to participation in that activity. !-- !--
!-- One of R's strengths is the ease with which well-designed !-- publication-quality plots can be produced, including mathematical !-- symbols and formulae where needed. Great care has been taken over the !-- defaults for the minor design choices in graphics, but the user !-- retains full control. !-- !--
!-- R is an integrated suite of software facilities for data !-- manipulation, calculation and graphical display. It includes !-- !--
!-- The term "environment" is intended to characterize it as a fully !-- planned and coherent system, rather than an incremental accretion of !-- very specific and inflexible tools, as is frequently the case with other !-- data analysis software. !-- !--
!-- R, like S, is designed around a true computer language, and it allows !-- users to add additional functionality by defining new functions. Much !-- of the system is itself written in the R dialect of S, which makes it !-- easy for users to follow the algorithmic choices made. For !-- computationally-intensive tasks, C, C++ and Fortran code can be linked !-- and called at run time. Advanced users can write C code to manipulate !-- R objects directly. !-- !--
!-- Many users think of R as a statistics system. We prefer to think of !-- it of an environment within which statistical techniques are !-- implemented. R can be extended (easily) via packages. There !-- are about eight packages supplied with the R distribution and many !-- more are available through the CRAN family of Internet sites covering !-- a very wide range of modern statistics. !-- !--
!-- R has its own LaTeX-like documentation format, which is used to supply !-- comprehensive documentation, both on-line in a number of formats and !-- in hardcopy. !-- !--
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!-- R can be found on http://cran.r-project.org, !-- the master site of comprehensive R archive network, or at one of its !-- mirrors. !-- !--
!-- It is available as source code and as binary distributions for a !-- number of GNU/Linux and Unix platforms, and for versions of Microsoft !-- Windows that support long file names. !-- !--
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!-- R comes with an FAQ list, and an !-- introduction to the language and how to use R for doing statistical !-- analysis and graphics in PDF and !-- other formats. !-- !--
!-- Further manuals and documentation (including in French and Spanish) !-- are discussed in the FAQ and in the documentation section on !-- CRAN. !-- !--
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!-- !-- Please send FSF & GNU inquiries & questions to !-- !-- [email protected]. !-- There are also other ways to !-- contact the FSF. !--
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!-- Copyright (C) 1999 Free Software Foundation, Inc. !--
!-- Verbatim copying and distribution of this entire article is !-- permitted in any medium, provided this notice is preserved. !--
!-- <\!-- hhmts start -\-> !-- Last modified: 2000 May 18 by Brian Ripley !-- <\!-- hhmts end -\-> !--