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THE BASIC R README(See "FAQ" and "RESOURCES" for more detailed information- these files are only in the tarballs)(See "INSTALL" for help on installation)1. INTRODUCTIONThis directory contains the source code tree for R, which is alanguage which is not entirely unlike (versions 3 and 4 of) the Slanguage developed at AT&T Bell Laboratories by Rick Becker, JohnChambers and Allan Wilks.R is free software distributed under a GNU-style copyleft.The core of R is an interpreted computer language with a syntaxsuperficially similar to C, but which is actually a "functionalprogramming language" with capabilities similar to Scheme. Thelanguage allows branching and looping as well as modular programmingusing functions. Most of the user-visible functions in R are writtenin R, calling upon a smaller set of internal primitives. It ispossible for the user to interface to procedures written in C orFortran languages for efficiency, and also to write additionalprimitives.The R distribution contains functionality for a large number ofstatistical procedures. Among these are: linear and generalizedlinear models, nonlinear regression models, time series analysis,classical parametric and nonparametric tests, clustering andsmoothing. There is also a large set of functions which provide aflexible graphical environment for creating various kinds of datapresentations.A package specification allows the production of loadable modules forspecific purposes, and several hundred contributed packages are madeavailable through the CRAN sites (seehttp://CRAN.R-project.org/mirrors.html for the current members).2. HISTORYR was initially written by Robert Gentleman and Ross Ihaka of theStatistics Department of the University of Auckland. In addition, alarge group of individuals has contributed to R by sending code and bugreports.Since mid-1997 there has been a core group who can modify the R sourcecode archive, listed in file AUTHORS.R 1.0.0 was released on 29 February 2000 and 2.0.0 on 4 October 2004.3. PRESENT STATUSThe present version implements most of the functionality in the 1988book "The New S Language" (the "Blue Book") and many of theapplications. In addition, we have implemented a large part of thefunctionality from the 1992 book "Statistical Models in S" (the "WhiteBook") and the 1998 book "Programming with Data" (the "Green Book").All the R functions have been documented in the form of help pages inan "output independent" form which can be used to create versions forHTML, LaTeX, text etc. A 1200+ page Reference Index (a collection ofall the help pages) can be obtained in a variety of formats. Themanual `An Introduction to R' provides a more user-friendly startingpoint, and there is an `R Language Definition' manual and morespecialized manuals on data import/export and extending R. See INSTALLfor instructions on how to generate these documents.4. GOALSOur aim at the start of this project was to demonstrate that it waspossible to produce an S-like environment which did not suffer fromthe memory-demands and performance problems which S has. Somewhatlater, we started to turn R into a "real" system, but unfortunately welost a large part of the efficiency advantage in the process, so haverevised the memory management mechanism and implemented delayedloading of R objects. A lot of performance tuning has been done,including the ability to use tuned linear-algebra libraries.Longer-term goals include to explore new ideas: e.g. virtual objectsand component-based programming, and expanding the scope of existingones like formula-based interfaces. Further, we wish to get a handleon a general approach to graphical user interfaces (preferably withcross-platform portability), and to develop better 3-D and dynamicgraphics.Sincerely,The R Core Team.