Computational methods for Bayesian model choice

Christian Robert (1, 2) , D. Wraith (2, 3)

1 CREST - Centre de Recherche en Économie et Statistique
2 CEREMADE - CEntre de REcherches en MAthématiques de la DEcision
3 IAP - Institut d'Astrophysique de Paris

In this note, we shortly survey some recent approaches on the approximation of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model choice. In particular, we reassess importance sampling, harmonic mean sampling, and nested sampling from a unified perspective.

Mots clés: Bayesian inference; Bayes factor; importance sampling; nested sampling; Monte Carlo

Domaines: Méthodologie [stat.ME]

Christian Robert, D. Wraith. Computational methods for Bayesian model choice. 2009. ⟨hal-00408203⟩