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Activity Number: 516
Type: Invited
Date/Time: Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #318060 View Presentation
Title: Bayesian Model Selection Based on Proper Scoring Rules
Author(s): Philip Dawid* and Monica Musio
Companies: University of Cambridge and University of Cagliari
Keywords: consistent model selection ; homogeneous score ; Hyvärinen score ; prequential
Abstract:

Bayesian model selection with improper priors is not well-defined because of the dependence of the marginal likelihood on the arbitrary scaling constants of the within-model prior densities. We show how this problem can be evaded by replacing marginal log-likelihood by a homogeneous proper scoring rule, which is insensitive to the scaling constants. Suitably applied, this will typically enable consistent selection of the true model.


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