666

Bayesian Model Selection and Model Averaging

Larry Wasserman

Abstract:

This paper reviews the Bayesian approach to model selection and model averaging. In this review, I emphasize objective Bayesian methods based on noninformative priors. I will also discuss implementation details, approximations and relationships to other methods.

Keywords: AIC, Bayes Factors, BIC, Consistency, Default Bayes Methods, Markov Chain Monte Carlo.



Here is the full postscript text for this technical report. It is 370098 bytes long.