Generalized Linear Models: A Bayesian Perspective, 1st Edition (Hardback) book cover

Generalized Linear Models

A Bayesian Perspective, 1st Edition

Edited by Dipak K. Dey, Sujit K. Ghosh, Bani K. Mallick

CRC Press

440 pages

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Hardback: 9780824790349
pub: 2000-05-25
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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.

Reviews

"…both accessible and valuable. Anyone interested in applying the Bayesian GLMs should have a copy of this book on their shelf."

-Statistical Methods in Medical Research

About the Series

Chapman & Hall/CRC Biostatistics Series

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Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General