THE BASIC R README (See "RESOURCES" for additional resources) 1. INTRODUCTION This directory contains the Unix source code tree for R, which is a language which is not entirely unlike the S language developed at AT&T Bell Laboratories by Rick Becker, John Chambers and Allan Wilks. Indeed in the (present) absence of an R manual, you can (mostly) get along by using the S manual. R is free software distributed under a GNU-style copyleft. Currently the software is in a beta test state and we are seeking comments and bug reports. Please send comments and reports to R@stat.auckland.ac.nz In the case of bugs it would be very helpful to have code which reliably reproduces the problem. Some bugs can be very hard to fix without this. 2. PRESENT STATUS We have implemented most of the functionality in the first S book (the "Blue Book") and many of the applications. In addition, we have implemented a certain amount of functionality from the second S book (the "White Book"). In particular we have a functioning versions of "lm" and "glm" and their associated "summary" and "anova" methods (it would be nice to have "drop1", "add1" and "step", but there hasn't been time to complete these yet). What we have in the way of manual is in the directory in an "output independent" form which can be used to create versions for HTML, LaTeX, troff etc. 3. 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. It is only recently that we have started trying to turn R into a "real" system. In the short term we hope to create a small portable free system which will provide most of the functionality of S and perhaps some extensions. Our present plan of attack is as follows: 1. Re-implement parts of the system to make things more modular so that data sets can be saved and restored on an individual basis and so that we have a real library facility. (Mostly done). 2. Move the user interface to an event driven basis. This will enable users to interact with the system in a much more graphical way. It also raises the possibility that we can borrow the graphics technology in LispStat. (Design phase). 3. Add functionality in the form of new functions. (Ongoing). 4. The present documentation is written using our own format into files which can be processed by a combination of sed and m4 into a variety of formats (nroff, latex, html). We should use a real SGML description of our format and develop techniques for more generally translating into other formats. Longer-term we are hoping to move to a compiled evironment which will give substantial performance gains. A separate compiler "skunk works" is engaged in this. 4. DIFFERENCES BETWEEN R AND S 1. In R, "factor" and "ordered factor" are primitive vector types. This means in particular that they can be shaped as arrays. 2. In R a list is a Lisp-style list composed of dotted pairs, rather than a vector of generic elements as in S. This means that list subscripting can be rather inefficient. However, lists are rarely large and so we have not (yet) bothered to implement a matching "generic vector" type, even though this could be quite useful. Robert Gentleman + Ross Ihaka
----------------------------------------------------------------------- R Version 0.49 for NEXTSTEP version 3.3 (M68k and Intel) ----------------------------------------------------------------------- This is a NEXTSTEP port of the R language for statistical programming. Included is beta version 0.49 which includes numerous improvements and enhancements over prior releases. About R: R is an extremely powerful (and fast) alternative to commercial statistics packages such as S-PLUS, SAS and SPSS. Read the README file, "R.ps" Postscript document and man page (R.1) included with this distribution to find out more about R. Note that users of S and S-PLUS will find R very easy to use. If you don't know S, check out "The New S Language" (Becker R, Chambers J, Wilks A; Wadsworth, 1988) to help you get started. For more info, visit the R homepage at http://www.stat.auckland.ac.nz/rproj.html There are also a number of "CRAN" ftp distribution sites for source code and supporting programs (listed on the R home page). Installation: To install R, unpack the distribution in an accessible place (e.g. /usr/local/ or ~/Apps). The "RHOME" directory created will be named "R-0.49". Place the R-0.49/bin/R start-up script somewhere on your path (e.g. /usr/local/bin, ~/bin) and modify to set the "RHOME" variable to point to the chosen installation path. Install the man page (R.1) in /usr/local/man/man1 or /usr/man/man1. Running R: After installation, type "R" from a UNIX shell prompt to start. X Windows is required to view graphics. I have used R successfully with both CubXWindows and co-Xist X11 emulation under NEXTSTEP (versions 3.2 - 3.3). R will run from any shell (e.g. Terminal or Stuart), but graphics will have to be written out using the postscript() function. R also accepts commands from std. input and writes to std. output. All of the available functions are listed in the help directory. The help files are viewed by typing "help(function_name)" at the R prompt. New functions are defined exactly as in S. Quit R by typing q(). If requested, an image of the current session (including the command history) will be saved in the file ".RData" in the current directory. This will automatically be read in the next time R is invoked in this directory. Enhancements in version 0.49 for NEXTSTEP: - all available patches as of June, 1997 are included - includes GNU readline support (past commands are saved and can be viewed and edited with the arrow and backspace keys) - the following additional S-PLUS functions have been compiled into this binary (NEXTSTEP doesn't support dynamic loading): - acepack: ACE and AVAS regression library (L. Breiman, R. Tibshirani) - survival4: survival analysis function library (T. Therneau) - gee: (generalized estimating equation) regression (V. Carey) - splines: spline regression function library (D. Bates) - bootstrap: bootstrap utilities (B. Efron, R. Tibshirani) - integrate: numerical integration functions - date: date handling utilities (for the survival4 package) - ctest: miscellaneous standard statistical tests - local: miscellaneous functions including isotonic regression These additional function libraries are accessed from within R using the "library()" call (e.g. library(bootstrap)). Look in R-0.49/help to view the available functions. DISCLAIMER: I have only tested the binary under NS 3.2 - 3.3 on m68K and Intel architecture. However, there may be bugs, so use at your own risk! If you want to build R for another architecture or for OPENSTEP, you can get the source from one of the CRAN distribution sites. ######################################################################### Stephen Shiboski email: steve@biostat.ucsf.edu Division of Biostatistics voice: 415-476-0533 University of California San Francisco fax: 415-476-6014 500 Parnassus Avenue, MU 420-W; San Francisco, CA 94143-0560 #########################################################################
These are the contents of the former NiCE NeXT User Group NeXTSTEP/OpenStep software archive, currently hosted by Netfuture.ch.