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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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