<p>Since our first edition of this book, many developments in statistical modΒ 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
Multivariate Statistical Modelling Based on Generalized Linear Models
β Scribed by Ludwig Fahrmeir, Gerhard Tutz (auth.)
- Publisher
- Springer New York
- Year
- 1994
- Tongue
- English
- Leaves
- 440
- Series
- Springer Series in Statistics
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Front Matter....Pages i-xxiv
Introduction....Pages 1-13
Modelling and analysis of crossβsectional data: a review of univariate generalized linear models....Pages 15-62
Models for multicategorical responses: multivariate extensions of generalized linear models....Pages 63-118
Selecting and checking models....Pages 119-149
Semiβ and nonparametric approaches to regression analysis....Pages 151-185
Fixed parameter models for time series and longitudinal data....Pages 187-218
Random effects models....Pages 219-255
State space models....Pages 257-303
Survival models....Pages 305-344
Back Matter....Pages 345-426
β¦ Subjects
Probability Theory and Stochastic Processes
π SIMILAR VOLUMES
This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, econom
Starting from simple hypothesis testing and then moving towards model-building, this valuable book takes readers through the basics of multivariate analysis including: which tests to use on which data; how to run analyses in SPSS for Windows and GLIM4; how to interpret results; and how to report and