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Methods and Criteria for Model Selection

Joseph B. Kadane and Nicole A. Lazar

Revised August 2003

Abstract:

Model selection is an important part of any statistical analysis, and indeed is central to the pursuit of science in general. Many authors have examined this question, from both frequentist and Bayesian perspectives, and many tools for selecting the ``best model'' have been suggested in the literature. This paper considers the various proposals from a Bayesian decision-theoretic perspective.

Keywords: AIC, Bayes Factors, BIC, Mallow's "$C_p$, Model Averaging, Subset Selection, Variable Selection

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