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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 system. Readers are assumed to have a basic grounding in statistics, and so the book is 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 and non-linear regression models, robust and smooth regression methods, survival analysis, multivariate analysis, tree-based methods, time series, spatial statistics, and classification. This second edition is intended for users of S-PLUS 3.3, 4.0, or later. It covers the recent developments in graphics and new statistical functionality, including bootstraping, mixed effects, linear and non-linear models, factor analysis, and regression with autocorrelated errors. The material on S-PLUS programming has been re-written to explain the full story behind the object-oriented programming features. The authors have written several software libraries which enhance S-PLUS; these and all the datasets used are available on the Internet in versions for Windows and UNIX. There are also on-line complements covering advanced material, further exercises and new features of S-PLUS as they are introduced. Dr. Venables is Head of Department and Senior Lecturer at the Department of
Content Level »Research
Keywords »Graphical Data Analysis System - S-PLUS - adopted-textbook NY
1 Introduction.- 2 The S Language.- 3 Graphical Output.- 4 Programming in S.- 5 Distributions and Data Summaries.- 6 Linear Statistical Models.- 7 Generalized Linear Models.- 8 Robust Statistics.- 9 Non-linear Models.- 10 Random and Mixed Effects.- 11 Modern Regression.- 12 Survival Analysis.- 13 Multivariate Analysis.- 14 Tree-based Methods.- 15 Time Series.- 16 Spatial Statistics.- 17 Classification.- Appendices.- A Datasets and Software.- A.1 Libraries.- A.2 Caveat.- B Common S-PLUS Functions.- C Using S-PLUS Libraries.- C.1 Sources of libraries.- C.2 Creating a library section.- References.