Multivariate Statistical Modelling Based on Generalized Linear Models

✍ Scribed by Ludwig Fahrmeir, Gerhard Tutz (auth.)

• Publisher: Springer-Verlag New York
• Year: 2001
• Tongue: English
• Leaves: 536
• Series: Springer Series in Statistics
• Edition: 2
• Category: Library

✦ Synopsis

Since our first edition of this book, many developments in statistical mod­ elling based on generalized linear models have been published, and our primary aim is to bring the book up to date. Naturally, the choice of these recent developments reflects our own teaching and research interests. The new organization parallels that of the first edition. We try to motiv­ ate and illustrate concepts with examples using real data, and most data sets are available on http:/ fwww. stat. uni-muenchen. de/welcome_e. html, with a link to data archive. We could not treat all recent developments in the main text, and in such cases we point to references at the end of each chapter. Many changes will be found in several sections, especially with those connected to Bayesian concepts. For example, the treatment of marginal models in Chapter 3 is now current and state-of-the-art. The coverage of nonparametric and semiparametric generalized regression in Chapter 5 is completely rewritten with a shift of emphasis to linear bases, as well as new sections on local smoothing approaches and Bayesian inference. Chapter 6 now incorporates developments in parametric modelling of both time series and longitudinal data. Additionally, random effect models in Chapter 7 now cover nonparametric maximum likelihood and a new section on fully Bayesian approaches. The modifications and extensions in Chapter 8 reflect the rapid development in state space and hidden Markov models.

✦ Table of Contents

Front Matter....Pages i-xxvi
Introduction....Pages 1-14
Modelling and Analysis of Cross-Sectional Data: A Review of Univariate Generalized Linear Models....Pages 15-67
Models for Multicategorical Responses: Multivariate Extensions of Generalized Linear Models....Pages 69-137
Selecting and Checking Models....Pages 139-172
Semi- and Nonparametric Approaches to Regression Analysis....Pages 173-240
Fixed Parameter Models for Time Series and Longitudinal Data....Pages 241-281
Random Effects Models....Pages 283-329
State Space and Hidden Markov Models....Pages 331-383
Survival Models....Pages 385-431
Back Matter....Pages 433-518

✦ Subjects

Statistical Theory and Methods; Statistics for Business/Economics/Mathematical Finance/Insurance; Statistics for Life Sciences, Medicine, Health Sciences