Original paper
Bayesian Measures of Model Complexity and Fit
Volume: 64, Issue: 4, Pages: 583 - 639
Published: Oct 1, 2002
Abstract
Summary We consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly defined. Using an information theoretic argument we derive a measure pD for the effective number of parameters in a model as the difference between the posterior mean of the deviance and the deviance at the posterior means of the parameters of interest. In general pD approximately corresponds to the trace of the product of...
Paper Details
Title
Bayesian Measures of Model Complexity and Fit
Published Date
Oct 1, 2002
Volume
64
Issue
4
Pages
583 - 639