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CRC Press Generalized Linear Models: A Bayesian Perspective (Chapman & Hall/CRC Biostatistics Series)

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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.

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Format
Paperback
Domain
Amazon UK
Release Date
20 December 2019
Listed Since
16 October 2019

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