S Programming

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Springer Science & Business Media, Apr 20, 2000 - Computers - 264 pages
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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 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.

 

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Contents

Introduction
1
11 Versions of S
2
12 S programming
3
13 Online material
4
The S Language Syntax and Semantics
5
22 Arithmetical expressions
17
23 Indexing
23
24 Vectors matrices and arrays
27
71 Managing loops
153
72 A large regression
159
73 Simulation envelopes for normalscores plots
161
74 Making good use of language objects
163
75 Bootstrapping and crossvalidation
172
76 Maximum likelihood estimates and iterative calculations
175
77 Tips
177
S Software Development
179

25 Character vector operations
29
26 Control structures
31
27 Vectorized calculations
34
The S Language Advanced Aspects
39
32 Writing functions
42
33 Calling the operating system
52
34 Databases frames and environments
54
35 Computing on the language
65
36 Graphics functions
72
Classes
75
42 An extended statistical example
83
an example of group method functions
87
Newstyle Classes
99
51 Creating a class
100
52 Inheritance
105
53 Generic and method functions
106
54 Oldstyle classes
109
55 An extended statistical example revisited
110
56 Group methods and another polynomial class
115
Using Compiled Code
123
62 Writing compiled code to work with S
128
63 Calling S from C
138
64 Using the Call interface
141
65 Debugging compiled code
148
66 Portability
149
General Strategies and Extended Examples
151
81 Editing S functions and objects
180
82 Tracing and debugging
181
83 Creating online help
188
84 SPLUS libraries
194
85 R packages
200
86 Developing code to be used on more than one engine
201
87 A checklist
202
Interfaces under Windows
205
92 Adding items to the menus
218
93 Managing a customized GUI
221
DDE
223
Automation
225
96 Interfacing with R
234
Compiling and Loading Code
235
A2 Procedures with R
239
A3 Common concerns
240
A4 Writing Dynamic Link Libraries for Windows
241
The Interactive Environment
247
B2 Options
249
B3 Session startup and finishing functions
250
BATCH Operation
253
C2 R
254
References
255
Index
257
Copyright

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About the author (2000)

Professor B. D. Ripley holds the Chair Applied Statistics at the University of Oxford.