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Generalized Linear Models and Extensions, Second Edition

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ISBN-10: 1597180149

ISBN-13: 9781597180146

Edition: 2nd 2007 (Revised)

Authors: James W. Hardin, Joseph M. Hilbe

List price: $87.95
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Description:

Generalized Linear Models and Extensions, Second Edition provides a comprehensive overview of the nature and scope of generalized linear models (GLMs) and of the major changes to the basic GLM algorithm that allow modeling of data that violate GLM distributional assumptions. Deftly balancing theory and application, the book stands out in its coverage of the derivation of the GLM families and their foremost links, while also guiding readers in the application of the various models to real data. This edition has new sections on discrete response models, including zero-truncated, zero-inflated, censored, and hurdle count models, as well as heterogeneous negative binomial, generalized Poisson,…    
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Book details

List price: $87.95
Edition: 2nd
Copyright year: 2007
Publisher: StataCorp LLC
Publication date: 2/20/2007
Binding: Paperback
Pages: 387
Size: 7.28" wide x 9.29" long x 0.87" tall
Weight: 1.804

Joseph M. Hilbe is an emeritus professor at the University of Hawaii, an adjunct professor of statistics at Arizona State University, and a Solar System Ambassador with NASA/Jet Propulsion Laboratory, Caltech. An elected Fellow of the American Statistical Association and elected member of the International Statistical Institute, Dr. Hilbe is currently President of the International Astrostatistics Association, is a full member of the American Astronomical Society, and Chairs the Statistics in Sports section of the American Statistical Association (ASA). He has authored fifteen books in statistical modeling, and over 200 book chapters, encyclopedia entries, journal articles, and published…    

Introduction
Foundations of generalized linear models
GLMs
GLM estimation algorithms
Analysis of fit
Continuous-response models
The Gaussian family
The gamma family
The inverse Gaussian family
The power family and link
Binomial response models
The binomial-logit family
The general binomial family
The problem of overdispersion
Count response models
The poisson family
The negative binomial family
Other count data models
Multinomial response models
The ordered-response family
Unordered-response family
Extensions to the GLM
Extending the likelihood
Clustered data
Stata software
Programs for stata