This fourth edition was published in late July 2002, and reprinted in May 2003. Links to material for earlier editions.
Online material:  

Description  Contents  Differences from Earlier Editions 
Online Complements  Exercises and Selected Answers  Software and Datasets 
Errata  Contact authors  Publisher's Web Sites 
S is a powerful environment for the statistical and graphical analysis of data. It provides the tools to implement many statistical ideas that have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S environments to perform statistical analyses and provides both an introduction to the use of S and a course in modern statistical methods. Implementations of S are available commercially in SPLUS®; and as the Open Source R for a wide range of computer systems.
The aim of this book is to show how to use S as a powerful and graphical data analysis system. Readers are assumed to have a basic grounding in statistics, and so the book is intended for wouldbe users of SPLUS or R and both students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets. Many of the methods discussed are state of the art approaches to topics such as linear, nonlinear and smooth regression models, treebased methods, multivariate analysis, pattern recognition, survival analysis, time series and spatial statistics. Throughout modern techniques such as robust methods, nonparametric smoothing and bootstrapping are used where appropriate.
This fourth edition is intended for users of SPLUS 6.0 or R 1.5.0 (or later). A substantial change from the third edition is updating for the current versions of SPLUS and adding coverage of R. The introductory material has been rewritten to emphasis the import, export and manipulation of data. Increased computational power allows even more computerintensive methods to be used, and methods such as GLMMs, MARS, Kohonen's SOM and support vector machines are considered.
The authors have written several software libraries that enhance SPLUS and R; these and all the datasets used are supplied with Windows versions of SPLUS and all versions of R, and are also available on the Internet in versions for Windows and Unix. There are extensive online complements covering advanced material, exercises and new features of SPLUS and R as they are introduced.
Dr Venables is a Senior Statistician with the CSIRO in Australia. He has given many courses on statistical computing, data analysis and graphics using S in Australia, Europe and the USA. Professor 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. They are the joint authors of `S Programming', the authoritative guide to using the S language.
SPLUS® is a commercial system of the Insightful Corporation.
The book is equally useful with R, a freelyavailable Open Source statistical system `not unlike S'.

Appendices:

The `complements' provide an online updating of the book, as well as further details of technical material.
Currently there are `Statistical Complements' in gziped postscript and PDF covering
Future complements are planned to cover changes in SPLUS and in R.
Some exercises on both S programming and data analysis are available for downloading. There are answers to almost all the programming exercises and to some of the data analysis problems.
VR4ex.ps.gz  gziped PostScript  (125Kb) 
VR4ex.pdf  (240Kb) 
The PDF version has extensive hyperlinks, for example between
exercises and their answers. Viewers can be downloaded from www.adobe.com;
a suitable viewer is normally installed with SPLUS
6.x on Windows.
There are errata lists available for
Printing  

First Edition  first  second  third  fourth 
Second Edition  first  second  third  
Third Edition  first  second  third  
Fourth Edition  first  second 
Only those for the current edition are maintained.
The Second Edition was written when SPLUS 3.4 was current; version 4.0 appeared shortly after the book.
The Third Edition was extensively revised, assuming that the reader had SPLUS 4.0 or later, and it takes account of SPLUS 5.x and 2000. As much of the material as possible was usable with SPLUS 3.3/4 and also with R. This gave accounts of the analyses made possible by the nlme3 and survival5 software. We added enhanced software for robust regression and for proportional odds logistic regression, and provided indepth analyses using these.
The Fourth Edition is targeted at SPLUS 6.x and R. This enables many new features of current S to be used, and will be particularly helpful to R users for whom almost all the changes needed are present in the main text. We have reorganized the introductory material and added new material on data import/export. The statistical material uses automated bandwidth selectors for histograms and density estimation, and adds new material on visualization, ICA, Kohonen's SOM, support vector machines and fitting GLMMs. Material previously in the online complements on overdispersion, factor analysis and correspondence analysis is now in the main text. The timeseries material has been reworked, using the arima() function we wrote and including material on GARCH models. There is a separate chapter on optimization, making use of the optim() function written by BDR for R and now available for SPLUS in MASS.
The material on programming has been reduced since the first and second editions: a much more comprehensive account is given in the companion volume S Programming.
Dr W. N. Venables CMIS Environmetrics Project PO Box 120, Cleveland, Qld, 4163 AUSTRALIA Email: Bill.Venables@csiro.au 
Professor B. D. Ripley Department of Statistics 1 South Parks Road Oxford OX1 3TG UK Email: ripley@stats.ox.ac.uk 
Links are provided to Springer's home pages in Germany and the USA.