Modern Applied Statistics with S

Front Cover
Springer, Aug 12, 2002 - Computers - 495 pages
12 Reviews
S-PLUS is a powerful environment for the statistical and graphical analysis of data. It provides the tools to implement many statistical ideas which have been made possible by the widespread availability of workstations having good graphics and computational capabilities. This book is a guide to using S-PLUS to perform statistical analyses and provides both an introduction to the use of S-PLUS and a course in modern statistical methods. S-PLUS is available for both Windows and UNIX workstations, and both versions are covered in depth. The aim of the book is to show how to use S-PLUS as a powerful and graphical data analysis system. Readers are assumed to have a basic grounding in statistics, and so the book in intended for would-be users of S-PLUS 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, tree-based methods, multivariate analysis and pattern recognition, survival analysis, time series and spatial statistics. Throughout, modern techniques such as robust methods, non-parametric smoothing, and bootstrapping are used where appropriate. This third edition is intended for users of S-PLUS 4.5, 5.0, 2000 or later, although S-PLUS 3.3/4 are also considered. The major change from the second edition is coverage of the current versions of S-PLUS. The material has been extensively rewritten using new examples and the latest computationally intensive methods. The companion volume on S Programming will provide an in-depth guide for those writing software in the S language. The authors have written several software libraries that enhance S-PLUS; these and all the datasets used are available on the Internet in versions for Windows and UNIX. There are extensive on-line complements covering advanced material, user-contributed extensions, further exercises, and new features of S-PLUS as they are introduced. Dr. Venables is now Statistician with CSRIO in Queensland, having been at the Department of Statistics, University of Adelaide, for many years previously. He has given many short courses on S-PLUS 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.
  

What people are saying - Write a review

User ratings

5 stars
4
4 stars
5
3 stars
1
2 stars
1
1 star
1

User Review - Flag as inappropriate

A good overview of what you can do with R and S+.
It won't be sufficient if you don't already know your statistics: but there are plenty of references for further reading.

User Review - Flag as inappropriate

Useful.

Related books

Contents

Introduction
1
11 A Quick Overview of S
3
12 Using S
5
13 An Introductory Session
6
14 What Next?
12
Data Manipulation
13
22 Connections
20
23 Data Manipulation
27
88 Additive Models
232
89 ProjectionPursuit Regression
238
810 Neural Networks
243
811 Conclusions
249
TreeBased Methods
251
91 Partitioning Methods
253
92 Implementation in rpart
258
93 Implementation in tree
266

24 Tables and CrossClassification
37
The S Language
41
32 More on S Objects
44
33 Arithmetical Expressions
47
34 Character Vector Operations
51
35 Formatting and Printing
54
36 Calling Conventions for Functions
55
37 Model Formulae
56
38 Control Structures
58
39 Array and Matrix Operations
60
310 Introduction to Classes and Methods
66
Graphics
69
41 Graphics Devices
71
42 Basic Plotting Functions
72
43 Enhancing Plots
77
44 Fine Control of Graphics
82
45 Trellis Graphics
89
Univariate Statistics
107
52 Generating Random Data
110
53 Data Summaries
111
54 Classical Univariate Statistics
115
55 Robust Summaries
119
56 Density Estimation
126
57 Bootstrap and Permutation Methods
133
Linear Statistical Models
139
62 Model Formulae and Model Matrices
144
63 Regression Diagnostics
151
64 Safe Prediction
155
65 Robust and Resistant Regression
156
66 Bootstrapping Linear Models
163
67 Factorial Designs and Designed Experiments
165
68 An Unbalanced FourWay Layout
169
69 Predicting Computer Performance
177
610 Multiple Comparisons
178
Generalized Linear Models
183
71 Functions for Generalized Linear Modelling
187
72 Binomial Data
190
73 Poisson and Multinomial Models
199
74 A Negative Binomial Family
206
75 OverDispersion in Binomial and Poisson GLMs
208
NonLinear and Smooth Regression
211
82 Fitting NonLinear Regression Models
212
83 NonLinear Fitted Model Objects and Method Functions
217
84 Confidence Intervals for Parameters
220
85 Profiles
226
86 Constrained NonLinear Regression
227
87 OneDimensional CurveFitting
228
Random and Mixed Effects
271
101 Linear Models
272
102 Classic Nested Designs
279
103 NonLinear Mixed Effects Models
286
104 Generalized Linear Mixed Models
292
105 GEE Models
299
Exploratory Multivariate Analysis
301
111 Visualization Methods
302
112 Cluster Analysis
315
113 Factor Analysis
321
114 Discrete Multivariate Analysis
325
Classification
331
122 Classification Theory
338
123 NonParametric Rules
341
124 Neural Networks
342
125 Support Vector Machines
344
126 Forensic Glass Example
346
127 Calibration Plots
349
Survival Analysis
353
131 Estimators of Survivor Curves
355
132 Parametric Models
359
133 Cox Proportional Hazards Model
365
134 Further Examples
371
Time Series Analysis
387
141 SecondOrder Summaries
389
142 ARIMA Models
397
143 Seasonality
403
144 Nottingham Temperature Data
406
145 Regression with Autocorrelated Errors
411
146 Models for Financial Series
414
Spatial Statistics
419
152 Kriging
425
153 Point Process Analysis
430
Optimization
435
162 SpecialPurpose Optimization Functions
436
ImplementationSpecific Details
447
A2 Using SPLUS under Windows
450
A3 Using R under Unix Linux
453
A4 Using R under Windows
454
A5 For Emacs Users
455
The SPLUS GUI
457
Datasets Software and Libraries
461
C2 Using Libraries
462
References
465
Index
481
Copyright

Common terms and phrases

Popular passages

Page 471 - Gill, PE, Murray. W.. and Wright. MH (1981). Practical Optimization.

References to this book

All Book Search results »

References from web pages

Modern Applied Statistics with S - Statistics and Computing ...
Modern Applied Statistics with S - Computational Statistics. S-PLUS is a powerful environment for the statistical and graphical analysis of data.
www.springer.com/ statistics/ computational/ book/ 978-0-387-95457-8

Modern Applied Statistics with S, 4th ed
By William N. Venables, BD Ripley; Springer-Verlag, 2002, ISBN 0387954570. Guide to using S-Plus and R for statistical analyses: introduces using S, ...
www.stats.ox.ac.uk/ pub/ MASS4/

Modern Applied Statistics with S-Plus, 2d Ed
Modern Applied Statistics with S-Plus, 2d ed. by Karen Kafadar , James R. Koehler. William N. VENABLES and Brian D. RIPLEY. New York: Springer-Verlag, 1997, ...
www.questia.com/ PM.qst?a=o& se=gglsc& d=5001242598

citeulike: Modern Applied Statistics with S
TY - BOOK ID - citeulike:699473 TI - Modern Applied Statistics with S PB - Springer SN - 0387954570 N2 - {S-PLUS is a powerful environment for the ...
www.citeulike.org/ user/ tkdoerksen/ article/ 699473

JSTOR: Modern Applied Statistics with S-PLUS
Modern Applied Statistics With S-PLUS (3rd ed.), by wn Venables and bd Ripley, New York: Springer- Verlag, 1999, ISBN 0-387-98825-4, xi + 501 pp., $64.95. ...
links.jstor.org/ sici?sici=0040-1706(200105)43%3A2%3C249%3AMASWS%3E2.0.CO%3B2-%23

Modern Applied Statistics with S-PLUS (Third Edition) wn Venables ...
Modern Applied Statistics with S-PLUS, first published in 1994, has made its. mark as a valuable reference for users of statistical methods in the S-Plus ...
sankhya.isical.ac.in/ search/ 62b3/ 62b3rev5.pdf

Modern Applied Statistics with S-PLUS: Windows Software
Modern Applied Statistics with S-PLUS by wn Venables & bd Ripley, Springer, 1999. ISBN 0 387 98825 4. [Details]. The software is for the Third Edition; ...
lib.stat.cmu.edu/ S/ MASS3/ Windows.shtml

Review of "Modern applied statistics" with S, 4th ed. by wn ...
Review of "Modern applied statistics" with S, 4th ed. by wn Venables and bd Ripley. Springer-Verlag 2002. Source, Computational Statistics & Data Analysis ...
portal.acm.org/ citation.cfm?id=793965& jmp=cit& coll=GUIDE& dl=ACM& CFID=15151515& CFTOKEN=6184618

Modern Applied Statistics with S-Plus
Modern Applied Statistics with S-Plus. Benny Yakir. Abstract. These notes are based on the book Modern Applied Statistics with ...
www.ces.clemson.edu/ ~calvinw/ MthSc885/ yakirsplus.pdf

Modern Applied Statistics With S | Technometrics | Find Articles ...
Modern Applied Statistics With S from Technometrics in Reference provided by Find Articles.
findarticles.com/ p/ articles/ mi_go2243/ is_200302/ ai_n6498550

About the author (2002)

Brian Ripley is the Professor of Applied Statistics at the University of Oxford and a member of the Department of Statistics as well as a Professorial Fellow of St. Peter's College.

Bibliographic information