Modern applied statistics with S

William Venables, Brian D. Ripley

496 pages, parution le 25/09/2002 (4^eme édition)

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Résumé

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 S-PLUS(R) workstations 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 would-be users of S-PLUS 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, tree-based methods, multivariate analysis, 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 fourth edition is intended for users of S-PLUS 6.0 or R 1.5.0 or later. A substantial change from the third edition is updating for the current versions of S-PLUS 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 computer-intensive methods to be used, and methods such as GLMMs, MARS, SOM and support vector machines are considered.

Contents

Introduction
Data Manipulation
The S Language
Graphics
Univariate Statistics
Linear Statistical Models
Generalized Linear Models
Non-linear and Smooth Regression
Tree-based Methods
Random and Mixed Effects
Exploratory Multivariate Analysis
Classification
Survival Analysis
Time Series Analysis
Spatial Statistics
Optimization.
Appendices

L'auteur - William Venables

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.

L'auteur - Brian D. Ripley

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, and freely available software, and through their extensive contributions to the S-news and R mailing lists.

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	William Venables, Brian D. Ripley
Parution	25/09/2002
Édition	4^eme édition
Nb. de pages	496
Format	16 x 24
Couverture	Relié
Poids	860g
Intérieur	Noir et Blanc
EAN13	9780387954578
ISBN13	978-0-387-95457-8