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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
Bayesian Analysis of Linear Models
Generalized Linear Models and Extensions
Introduction to Generalized Linear Models
Generalized Linear Models
Generalized Linear Models With Examples in R
Bayesian Modeling in Bioinformatics
Generalized Linear Models
Generalized Latent Variable Modeling
Foundations of Linear and Generalized Linear Models
Bayesian Biostatistics
Generalized, Linear, and Mixed Models
Extending the Linear Model with R