S Programming

The interface facilities are most developed onWindows® 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;

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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 theCSIRO/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.