Title: Generalized Linear Models : A Bayesian Perspective
Publisher: Taylor & Francis Ltd Nov 2019
Publication Date: 2019
Language: English
ISBN 10: 0367398605
ISBN 13: 9780367398606
Binding: Taschenbuch
Condition: Neu
Dimensions: 222 millimeters width by 141 millimeters height by 33 millimeters depth
Weight: 515 grams

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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.

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

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