R help - Nov 1999 - Wanted: online Introduction to R

As a complete newcomer I am attempting to learn to use R, but am finding
it extremely difficult because I have not yet found an "Introduction to
R".

For over a week now I have monitored the R-help list, studied the R-FAQ
and related documents, downloaded and run the Windows R and looked at
the Help, downloaded early and late samples of the R-help archives, and
searched for illuminating articles in online journals, all with little
success.

The R documentation appears to be quite good, but it does assume the
reader already understands the basics of the language. I had hoped to
find, at least, a terse definition of the language syntax with some
description of the semantics.

Can anybody please assist?

Many thanks in anticipation,

Clive Jenkins
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Thanks to all those who responded, both privately and via the list:

 Prof Brian Ripley
 Jens Oehlschlaegel
 Tim McDonough
 John Maindonald
 Maria Wolters
 Pat Altham
 Rashid Nassar
 Jeffrey Morris
 Yves Gauvreau
 Peter Dalgaard BSA
 Paul Kristiansen

I have already listed those documents I had read before asking for help
(Date: Tue, 16 Nov 1999 17:04:18 +0000
 From: Clive Jenkins <clive.jenkins at clara.net>)
so I will not repeat the list here. They were all accessable from the
famous R-FAQ (see URL at the end of every email sent via r-help), which
really is the key document. It repays careful study, and is subject to
change without notice, so never rely on a cached copy.

There is a nice new hyperlinked PDF version of the R-notes (built, I
believe, by Prof Brian Ripley), which is essential reading for anyone
who wants to understand the R language: "Notes on R: A Programming
Environment for Data Analysis and Graphics" by Bill Venables, Dave
Smith, Robert Gentleman, Ross Ihaka and Martin Maechler.
http://www.ci.tuwien.ac.at/R/doc/Rnotes.pdf

The above document is *not* yet referenced directly by the R-FAQ, but a
new link to it *has* appeared in the third item under "R
Documentation"
at CRAN (or a mirror).
http://www.ci.tuwien.ac.at/R/

Although I have not yet read "Modern Applied Statistics with S-PLUS"
Third Edition, W.N. Venables and B.D. Ripley (mentioned in R-FAQ), I
have read quite a few on-line papers and e-mails by the authors. They
clearly know their subject and are engaging communicators.
http://www.stats.ox.ac.uk/pub/MASS3/

Another good book on the S language is (thanks to Jens Oehlschlaegel and
John Maindonald) "S Poetry", Burns, P. J. 1998. This is available
on-line and has been mentioned in r-help in Sept and Oct 1999 (search
for "poetry" in r-help-99-09-28--99-10-28 from mail-archives on CRAN).
http://www.seanet.com/~pburns/Spoetry/

University Statistics Departments are good sources of R course notes (as
mentioned by Maria Wolters who has collected a thick folder). These are
useful "quick-start" guides of a practical nature that immediately
introduce the important functions of the language. John Maindonald of
the Australian National University referred me to his course, which I
found very useful, but because he is still working on it I will leave it
for him to announce when he feels it is ready.

Pat Altham of the Statistical Laboratory, University of Cambridge has
some good course material on Computational Statistics and Statistical
Modelling in gzipped PostScript, together with datasets used in the
exercises.
http://www.statslab.cam.ac.uk/~pat/

To read PostScript (plain and gzipped) and/or PDF files on a Windows PC
the Windows port of the GNU GhostScript Viewer is recommended (by Yves
Gauvreau and others): "Follow installation instructions and once started
use GSVIEW mswinpr2 as the printer driver ..."
http://www.cs.wisc.edu/~ghost/gsview/index.html

I found that legibility of documents in GSView was greatly improved by
turning antialiasing on (thanks to Peter Dalgaard for that hint). On the
menu bar: Media -> Display Settings -> Help.

These last few pointers are not directly related to R, but are
potentially helpful resources I discovered on my travels:

A useful (short) on-line book for the beginner, or as a refresher
course: "Statistics at Square One", Ninth Edition, T D V Swinscow,
Revised by M J Campbell, University of Southampton. Copyright BMJ
Publishing Group 1997.
http://www.bmj.com/collections/statsbk/

An excellent on-line book for the more advanced reader, especially
chapters 14 and 15 that deal with Statistics and Data Modeling:
"Numerical Recipes in C: the Art of Scientific Computing" (ISBN
0-521-43108-5) Copyright (C) 1988-1992 by Cambridge University Press. A
Fortran version is also available, and both exist in PostScript and PDF.
http://www.ulib.org/webRoot/Books/Numerical_Recipes/

A list of Online Journals (Statistics) at Tennessee State University.
http://www.tnstate.edu/library/journal/onjnstat.htm


Finally I must say that I find the R community most friendly and
helpful. Even the top gurus sacrifice considerable time giving detailed
attention to users' questions. Keep up the good work!

Best regards,

Clive Jenkins.

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r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at
stat.math.ethz.ch
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