Comparing and calibrating discrepancy measures for Bayesian model selection

• Autores: Julián de la Horra Navarro, María Teresa Rodríguez Bernal
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 36, Nº. 1, 2012, págs. 69-80
• Idioma: inglés
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• Resumen

  • Different approaches have been considered in the literature for the problem of Bayesian model selection. Recently, a new method was introduced and analysed in De la Horra (2008) by minimizing the posterior expected discrepancy between the set of data and the Bayesian model, where the chi-square discrepancy was used. In this article, several discrepancy measures are considered and compared by simulation, and it is obtained that the chi-square discrepancy is reasonable to use. Then, an easy method for calibrating discrepancies is proposed, and the behaviour of this approach is studied on simulated data. Finally, a set of real data is analysed.