ABSTRACT
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
TABLE OF CONTENTS
part I|2 pages
General Overview
part II|2 pages
Extending the GLMs
part III|2 pages
Categorical and Longitudinal Data
part IV|2 pages
Semiparametric Approaches
part V|2 pages
Model Diagnostics and Variable Selection in GLMs
part VI|2 pages
Challenging Approaches in GLMs