r-source

		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 and 4.0.0 on 24 April 2020.

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 2300+ page Reference Index (a collection of most of the help pages: there is also a 3900+ 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 administration, 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.