Some connections between Bayesian and non-Bayesian methods for regression model selection
In this article, we study the connections between Bayesian methods and non-Bayesian methods for variable selection in multiple linear regression. We show that each of the non-Bayesian criteria, FPE[alpha], AIC, Cp and adjusted , has its Bayesian correspondence under an appropriate prior setting. The theoretical results are illustrated by numerical simulations.
Volume (Year): 57 (2002)
Issue (Month): 1 (March)
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- Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer, vol. 21(1), pages 243-247, December.
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