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Generalized Linear Models

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, this work considers parametric and semiparametric approaches to overdispersed GLMs.

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