Generalized Linear Models : A Bayesian Perspective
Book Details
Format
Paperback / Softback
Book Series
Chapman & Hall/CRC Biostatistics Series
ISBN-10
0367398605
ISBN-13
9780367398606
Publisher
Taylor & Francis Ltd
Imprint
CRC Press
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Nov 1st, 2019
Print length
442 Pages
Weight
515 grams
Dimensions
22.20 x 14.10 x 3.30 cms
Product Classification:
Probability & statistics
AI Summary
Ksh 12,250.00
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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.
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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