## Modern Applied Statistics with SSpringer Science & Business Media, 09.03.2013 - 498 Seiten 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. |

### Inhalt

14 | |

The S Language | 27 |

20 | 35 |

Graphics | 70 |

Univariate Statistics | 108 |

Linear Statistical Models | 139 |

Generalized Linear Models | 184 |

NonLinear and Smooth Regression | 211 |

TreeBased Methods | 251 |

Random and Mixed Effects | 278 |

Exploratory Multivariate Analysis | 306 |

Classification | 339 |

Survival Analysis | 368 |

Appendices | 447 |

B The SPLUS | 457 |

494 | |

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### Häufige Begriffe und Wortgruppen

algorithm analysis anova approximation argument bandwidth binomial bootstrap character vector clusters coef Coefficients column compute confidence intervals consider covariance coxph data frame dataset default degrees of freedom deviance device dimnames dist distribution eqscplot Error t value example factor fgl$type frequency function function(x give graphics Intercept labels levels library section likelihood linear models linear regression lines log-linear models Loglik M-estimators mean median method mfrow multivariate names non-linear non-linear regression normal object observations output p-value parameters periodogram plot points Poisson postscript predict Pregnanetriol principal component projection pursuit Q-Q plot quantile random effects regression residuals result Ripley S-PLUS sample scale scatterplot smooth specified spline split squares standard error Statistical Tetrahydrocortisone topo tree Trellis Value Std variables variance vector weights Wiley and Sons window WinF xlab ylab zero