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(r) 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(r) 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.