Generalized Linear Models: A Bayesian Perspective
Dipak K. Dey, Sujit K. Ghosh, Bani K. Mallick
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.
Categories:
Year:
2000
Edition:
1
Publisher:
CRC Press
Language:
english
Pages:
442
ISBN 10:
0824790340
ISBN 13:
9780824790349
Series:
Chapman & Hall CRC Biostatistics Series
File:
PDF, 8.46 MB
IPFS:
,
english, 2000