S is a high-level language for manipulating, analysing and displaying
data. It forms the basis of two highly acclaimed and widely used data
analysis software systems, the commercial S-PLUS® and the Open
Source R. This book provides an in-depth guide to writing software in
the S language under either or both of those systems. It is intended
for readers who have some acquaintance with the S language and want to
know how to use it more effectively, for example to build re-usable
tools for streamlining routine data analysis or to implement new
statistical methods.
One of the outstanding strengths of the S language is the ease with
which it can be extended by users. S is a functional language, and
functions written by users are first-class objects treated in the same
way as functions provided by the system. S code is eminently readable
and so a good way to document precisely what algorithms were used, and
as much of the implementations are themselves written in S, they can be
studied as models and to understand their subtleties. The current
implementations also provide easy ways for S functions to call
compiled code written in C, Fortran and similar languages; this is
documented here in depth.
Increasingly S is being used for statistical or graphical analysis
within larger software systems or for whole vertical-market
applications. The interface facilities are most developed on
Windows® and these are covered with worked examples.
The authors have written the widely used Modern Applied Statistics
with S-PLUS, now in its third edition, and several software libraries
that enhance S-PLUS and R; these and the examples used in both books
are available on the Internet.
Dr. W.N. Venables is a senior Statistician with the CSIRO/CMIS
Environmetrics Project in Australia, having been at the Department of
Statistics, University of Adelaide for many years previously.
Professor B.D. Ripley holds the Chair of Applied Statistics at the
University of Oxford, and is the author of four other books on spatial
statistics, simulation, pattern recognition and neural networks. Both
authors are known and respected throughout the international S and R
communities, for their books, workshops, short courses, freely
available software and through their extensive contributions to the
S-news and R mailing lists.
