README - R - Git at Google


 			THE BASIC R README


 	   (See "doc/FAQ" and "doc/RESOURCES" for more detailed information
 				      - these files are only in the tarballs)
 	   (See "INSTALL"             for help on installation)

 1. INTRODUCTION

 This directory contains the source code tree for R, which is a
 language which is not entirely unlike (versions 3 and 4 of) the S
 language developed at AT&T Bell Laboratories by Rick Becker, John
 Chambers and Allan Wilks.

 R is free software distributed under a GNU-style copyleft.

 The core of R is an interpreted computer language with a syntax
 superficially similar to C, but which is actually a "functional
 programming language" with capabilities similar to Scheme.  The
 language allows branching and looping as well as modular programming
 using functions.  Most of the user-visible functions in R are written
 in R, calling upon a smaller set of internal primitives.  It is
 possible for the user to interface to procedures written in C or
 Fortran languages for efficiency, and also to write additional
 primitives.

 The R distribution contains functionality for a large number of
 statistical procedures.  Among these are: linear and generalized
 linear models, nonlinear regression models, time series analysis,
 classical parametric and nonparametric tests, clustering and
 smoothing.  There is also a large set of functions which provide a
 flexible graphical environment for creating various kinds of data
 presentations.

 A package specification allows the production of loadable modules for
 specific purposes, and several thousand contributed packages are made
 available through the CRAN sites (see
 https://CRAN.R-project.org/mirrors.html for the current members).


 2. HISTORY

 R was initially written by Robert Gentleman and Ross Ihaka of the
 Statistics Department of the University of Auckland.  In addition, a
 large group of individuals has contributed to R by sending code and bug
 reports.

 Since mid-1997 there has been a core group who can modify the R source
 code archive, listed in file doc/AUTHORS.

 R 1.0.0 was released on 29 February 2000 and 2.0.0 on 4 October 2004.
 R 3.0.0 came out on 3 April 2013.

 This file has been minimally revised since the release of R 1.0.0.

 3. PRESENT STATUS

 The present version implements most of the functionality in the 1988
 book "The New S Language" (the "Blue Book") and many of the
 applications.  In addition, we have implemented a large part of the
 functionality from the 1992 book "Statistical Models in S" (the "White
 Book") and the 1998 book "Programming with Data" (the "Green Book").

 All the R functions have been documented in the form of help pages in
 an "output independent" form which can be used to create versions for
 HTML, PDF, text etc.  A 1900+ page Reference Index (a collection of
 most of the help pages: there is also a 3300+ page version with all
 the help pages, including recommended packages) can be obtained in
 PDF.  The manual `An Introduction to R' provides a more user-friendly
 starting point, and there is an FAQ, a draft `R Language Definition'
 manual and more specialized manuals on admininstration, data
 import/export and extending R.  See INSTALL for instructions on how to
 generate these documents.


 4. GOALS

 Our aim at the start of this project was to demonstrate that it was
 possible to produce an S-like environment which did not suffer from
 the memory-demands and performance problems which S has.  Somewhat
 later, we started to turn R into a "real" system, but unfortunately we
 lost a large part of the efficiency advantage in the process, so have
 revised the memory management mechanism and implemented delayed
 loading 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 objects
 and component-based programming, and expanding the scope of existing
 ones like formula-based interfaces.  Further, we wish to get a handle
 on a general approach to graphical user interfaces (preferably with
 cross-platform portability), and to develop better 3-D and dynamic
 graphics.


 Sincerely,
 The R Core Team.

	THE BASIC R README


	(See "doc/FAQ" and "doc/RESOURCES" for more detailed information
	- these files are only in the tarballs)
	(See "INSTALL" for help on installation)

	1. INTRODUCTION

	This directory contains the source code tree for R, which is a
	language which is not entirely unlike (versions 3 and 4 of) the S
	language developed at AT&T Bell Laboratories by Rick Becker, John
	Chambers and Allan Wilks.

	R is free software distributed under a GNU-style copyleft.

	The core of R is an interpreted computer language with a syntax
	superficially similar to C, but which is actually a "functional
	programming language" with capabilities similar to Scheme. The
	language allows branching and looping as well as modular programming
	using functions. Most of the user-visible functions in R are written
	in R, calling upon a smaller set of internal primitives. It is
	possible for the user to interface to procedures written in C or
	Fortran languages for efficiency, and also to write additional
	primitives.

	The R distribution contains functionality for a large number of
	statistical procedures. Among these are: linear and generalized
	linear models, nonlinear regression models, time series analysis,
	classical parametric and nonparametric tests, clustering and
	smoothing. There is also a large set of functions which provide a
	flexible graphical environment for creating various kinds of data
	presentations.

	A package specification allows the production of loadable modules for
	specific purposes, and several thousand contributed packages are made
	available through the CRAN sites (see
	https://CRAN.R-project.org/mirrors.html for the current members).


	2. HISTORY

	R was initially written by Robert Gentleman and Ross Ihaka of the
	Statistics Department of the University of Auckland. In addition, a
	large group of individuals has contributed to R by sending code and bug
	reports.

	Since mid-1997 there has been a core group who can modify the R source
	code archive, listed in file doc/AUTHORS.

	R 1.0.0 was released on 29 February 2000 and 2.0.0 on 4 October 2004.
	R 3.0.0 came out on 3 April 2013.

	This file has been minimally revised since the release of R 1.0.0.

	3. PRESENT STATUS

	The present version implements most of the functionality in the 1988
	book "The New S Language" (the "Blue Book") and many of the
	applications. In addition, we have implemented a large part of the
	functionality from the 1992 book "Statistical Models in S" (the "White
	Book") and the 1998 book "Programming with Data" (the "Green Book").

	All the R functions have been documented in the form of help pages in
	an "output independent" form which can be used to create versions for
	HTML, PDF, text etc. A 1900+ page Reference Index (a collection of
	most of the help pages: there is also a 3300+ page version with all
	the help pages, including recommended packages) can be obtained in
	PDF. The manual `An Introduction to R' provides a more user-friendly
	starting point, and there is an FAQ, a draft `R Language Definition'
	manual and more specialized manuals on admininstration, data
	import/export and extending R. See INSTALL for instructions on how to
	generate these documents.


	4. GOALS

	Our aim at the start of this project was to demonstrate that it was
	possible to produce an S-like environment which did not suffer from
	the memory-demands and performance problems which S has. Somewhat
	later, we started to turn R into a "real" system, but unfortunately we
	lost a large part of the efficiency advantage in the process, so have
	revised the memory management mechanism and implemented delayed
	loading 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 objects
	and component-based programming, and expanding the scope of existing
	ones like formula-based interfaces. Further, we wish to get a handle
	on a general approach to graphical user interfaces (preferably with
	cross-platform portability), and to develop better 3-D and dynamic
	graphics.


	Sincerely,
	The R Core Team.