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- W2196549087 abstract "In this paper, we consider the Bayesian posterior distribution as the solutionto a minimization rule, first observed by Zellner (1988). The expression to beminimized is a mixture of two pieces, one piece involving the prior distribution,which is minimized by the prior, and the other piece involves the data,which is minimized by the measure putting all the mass on the maximumlikelihood estimator. From this perspective of the posterior distribution,Bayesian model selection and the search for an objective prior distribution,can be viewed in a way which is different from usual Bayesian approaches." @default.
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- W2196549087 title "Bayesian inference via a minimization rule" @default.
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