
Generalized Linear Models
A Bayesian Perspective
CRC Press
1st Edition
Published on 1. November 2019
Book
Paperback/Softback
442 pages
978-0-367-39860-6 (ISBN)
Description
This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Dimensions
Height: 246 mm
Width: 174 mm
Weight
820 gr
ISBN-13
978-0-367-39860-6 (9780367398606)
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Additional editions

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05/2000
1st Edition
CRC Press
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E-Book
05/2000
CRC Press
€89.99
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E-Book
05/2000
CRC Press
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Persons
Dipak K. Dey, Sujit K. Ghosh , Bani K. Mallick
Content
Part 1 Extending the GLMs. Part 2 Categorical and longitudinal data. Part 3 Semiparametric approaches. Part 4 Model diagnositics and value selection in GLMs. Part 5 Challenging problems in GLMs