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Generalized Linear Models: A Bayesian Perspective
Author(s): Dipak K. Dey (Editor), Sujit K. Ghosh (Editor), Bani K. Mallick (Editor)
- Publisher: CRC Press
- Publication Date: December 20, 2019
- Edition: 1st
- Language: English
- Print length: 442 pages
- ISBN-10: 0367398605
- ISBN-13: 9780367398606
Book 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.
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About the Author
Dipak K. Dey, Sujit K. Ghosh , Bani K. Mallick
