Generalized linear models have applications in many areas, including social science and life science. This book will serve as a reference and advanced text for students interested in the applications of statistics.
Rezensionen / Stimmen
From a review:
TECHNOMETRICS
"...one of the best applied statistical books that I have ever read."
Reihe
Auflage
1st ed. 1997. Corr. 3rd printing 2000
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Graduate
Editions-Typ
Illustrationen
Maße
Höhe: 241 mm
Breite: 160 mm
Dicke: 20 mm
Gewicht
ISBN-13
978-0-387-98218-2 (9780387982182)
DOI
Schweitzer Klassifikation
Generalized Linear Modelling: Statistical Modelling.- Exponential Dispersion Models.- Linear Structure.- Three Components of a GLM.- Possible Models.- Inference.- Exercises. Discrete Data: Log Linear Models.- Models of Change.- Overdispersion.- Exercises. Fitting and Comparing Probability Distributions: Fitting Distributions.- Setting Up the Model.- Special Cases.- Exercises. Growth Curves: Exponential Growth Curves.- Logistic Growth Curve.- Gomperz Growth Curve.- More Complex Models.- Exercises. Time Series: Poisson Processes.- Markov Processes.- Repeated Measurements.- Exercises. Survival Data: General Concepts.- 'Nonparametric' Estimation.- Parametric Models.- 'Semiparametric' Models.- Exercises. Event Histories: Event Histories and Survival Distributions.- Counting processes.- Modelling Event Histories.- Generalizations.- Exercises. Spatial data: Spatial Interaction.- Spatial Patterns.- Exercises. Normal Models: Linear Regression.- Analysis of Variance.- Nonlinear Regression.- Exercises. Dynamic Models: Dynamic Generalized Linear Models.- Normal Models.- Count Data.- Positive Response Data.- Continuous Time Nonlinear Models. Appendices: Inference.- Diagnostics.- References.- Index.
