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Modern Applied Statistics with S

  • W. N. Venables
  • B. D. Ripley

Part of the Statistics and Computing book series (SCO)

Table of contents

  1. Front Matter
    Pages i-xi
  2. W. N. Venables, B. D. Ripley
    Pages 1-12
  3. W. N. Venables, B. D. Ripley
    Pages 13-39
  4. W. N. Venables, B. D. Ripley
    Pages 41-68
  5. W. N. Venables, B. D. Ripley
    Pages 69-105
  6. W. N. Venables, B. D. Ripley
    Pages 107-138
  7. W. N. Venables, B. D. Ripley
    Pages 139-181
  8. W. N. Venables, B. D. Ripley
    Pages 183-210
  9. W. N. Venables, B. D. Ripley
    Pages 211-250
  10. W. N. Venables, B. D. Ripley
    Pages 251-269
  11. W. N. Venables, B. D. Ripley
    Pages 271-300
  12. W. N. Venables, B. D. Ripley
    Pages 301-330
  13. W. N. Venables, B. D. Ripley
    Pages 331-351
  14. W. N. Venables, B. D. Ripley
    Pages 353-385
  15. W. N. Venables, B. D. Ripley
    Pages 387-418
  16. W. N. Venables, B. D. Ripley
    Pages 419-434
  17. W. N. Venables, B. D. Ripley
    Pages 435-446
  18. Back Matter
    Pages 447-497

About this book

Introduction

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,

Keywords

Bootstrapping Cluster analysis Estimator Factor analysis Fitting Generalized linear model STATISTICA Survival analysis Time series best fit classification data analysis linear regression

Authors and affiliations

  • W. N. Venables
    • 1
  • B. D. Ripley
    • 2
  1. 1.CSIRO Mathematics and Information ScienceClevelandAustralia
  2. 2.Department of StatisticsUniversity of OxfordOxfordEngland

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-21706-2
  • Copyright Information Springer-Verlag New York 2002
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-3008-8
  • Online ISBN 978-0-387-21706-2
  • Series Print ISSN 1431-8784
  • Buy this book on publisher's site