Intrinsic Priors for Objective Bayesian Model Selection

Elías Moreno and Luís Raúl Pericchi

A chapter in Bayesian Model Comparison, 2014, vol. 34, pp 279-300 from Emerald Group Publishing Limited

Abstract: We put forward the idea that for model selection the intrinsic priors are becoming a center of a cluster of a dominant group of methodologies for objective Bayesian Model Selection. The intrinsic method and its applications have been developed in the last two decades, and has stimulated closely related methods. The intrinsic methodology can be thought of as the long searched approach for objective Bayesian model selection and hypothesis testing. In this paper we review the foundations of the intrinsic priors, their general properties, and some of their applications.

Keywords: g-prior; intrinsic priors; model selection; sampling properties of Bayes factors; C11; C12; C18 (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320140000034012

DOI: 10.1108/S0731-905320140000034012

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