Show simple item record

dc.contributor.authorRobert, Christian P.
dc.contributor.authorCornuet, Jean-Marie
dc.contributor.authorMarin, Jean-Michel
dc.contributor.authorPillai, Natesh S.
dc.subjectBayes factoren
dc.subjectlikelihood-free methodsen
dc.subjectBayesian model choiceen
dc.titleLack of confidence in approximate Bayesian computation model choiceen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherInstitut de Mathématiques et de Modélisation de Montpellier (I3M);France
dc.contributor.editoruniversityotherCentre de Recherche en Économie et Statistique (CREST);France
dc.contributor.editoruniversityotherCentre de biologie et gestion des populations (CBGP);France
dc.contributor.editoruniversityotherDepartment of Statistics, Harvard University;États-Unis
dc.description.abstractenApproximate Bayesian computation (ABC) have become a essential tool for the analysis of complex stochastic models. Earlier, Grelaud et al. (2009) advocated the use of ABC for Bayesian model choice in the specific case of Gibbs random fields, relying on a inter-model sufficiency property to show that the approximation was legitimate. Having implemented ABC-based model choice in a wide range of phylogenetic models in the DIY-ABC software (Cornuet et al., 2008), we now present theoretical background as to why a generic use of ABC for model choice is ungrounded, since it depends on an unknown amount of information loss induced by the use of insufficient summary statistics. The approximation error of the posterior probabilities of the models under comparison may thus be unrelated with the computational effort spent in running an ABC algorithm. We then conclude that additional empirical verifications of the performances of the ABC procedure are necessary to conduct model choice.en
dc.relation.isversionofjnlnameProceedings of the National Academy of Sciences of the United States of America
dc.subject.ddclabelProbabilités et mathématiques appliquéesen

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record