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 "
, Model Averaging, Subset Selection, Variable Selection