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Libro 102 de 155: Chapman & Hall/CRC Biostatistics
 
9780367398606: Generalized Linear Models: A Bayesian Perspective (Chapman & Hall/CRC Biostatistics Series)

Sinopsis

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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Acerca del autor

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

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