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Statistical Model Selection Criteria and Bayesianism

Published online by Cambridge University Press:  01 April 2022

I. A. Kieseppä
I. A. Kieseppä*
Affiliation:
University of Helsinki
*
†Send requests for reprints to the author, Department of Philosophy, P.O. Box 24 (Unioninkatu 40), 00014 University of Helsinki, Finland; email: kieseppa@cc.helsinki.fi.
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Abstract

Two Bayesian approaches to choosing between statistical models are contrasted. One of these is an approach which Bayesian statisticians regularly use for motivating the use of AIC, BIC, and other similar model selection criteria, and the other one is a new approach which has recently been proposed by Bandyopadhayay, Boik, and Basu. The latter approach is criticized, and the basic ideas of the former approach are presented in a way that makes them accessible to a philosophical audience. It is also pointed out that the former approach establishes a new, philosophically interesting connection between the notions of simplicity and informativeness.

Type
Bayesian Methodology
Information
Philosophy of Science , Volume 68 , Issue S3: No. 3 Supplement: Proceedings of the 2000 Biennial Meeting of the Philosophy of Science Association. Part I: Contributed Papers Sep., 2001 , 2001 , pp. S141 - S152
Copyright
Copyright © Philosophy of Science Association 2001

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Footnotes

‡

I would like to express my gratitude to Jouni Kuha for his critical comments on an earlier version of this paper.

References

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