Eleonora Fois Fois
Bayesian model selection based on proper scoring rules
MUSIO, MONICA
2015-01-01
Abstract
Bayesian model selection with improper priors is not well-defined becauseof the dependence of the marginal likelihood on the arbitrary scaling constantsof the within-model prior densities. We show how this problem can beevaded by replacing marginal log-likelihood by a homogeneous proper scoring rule,which is insensitive to the scaling constants. Suitably applied, this will typicallyenable consistent selection of the true model.File | Size | Format | |
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BMS-SR2015.pdf open access
Type: versione editoriale
Size 1.58 MB
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1.58 MB | Adobe PDF | View/Open |
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