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hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorClarté, Grégoire
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorRyder, Robin J.
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorRobert, Christian P.
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorStoehr, Julien
HAL ID: 177045
ORCID: 0000-0002-7813-0185
dc.date.accessioned2019-09-04T11:30:21Z
dc.date.available2019-09-04T11:30:21Z
dc.date.issued2019
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/19680
dc.language.isoenen
dc.subjectApproximate Bayesian computationen
dc.subjectGibbs sampleren
dc.subjecthierarchical Bayes modelen
dc.subjectcurse of dimension- alityen
dc.subjectconditional distributionsen
dc.subjectconvergence of Markov chainsen
dc.subjectincompatible conditionalsen
dc.subject.ddc515en
dc.titleComponent-wise approximate Bayesian computation via Gibbs-like stepsen
dc.typeDocument de travail / Working paper
dc.description.abstractenApproximate Bayesian computation methods are useful for generative models with intractable likelihoods. These methods are however sensitive to the dimension of the parameter space, requiring exponentially increasing resources as this dimension grows. To tackle this difficulty, we explore a Gibbs version of the ABC approach that runs component-wise approximate Bayesian computation steps aimed at the corresponding conditional posterior distributions, and based on summary statistics of reduced dimensions. While lacking the standard justifications for the Gibbs sampler, the resulting Markov chain is shown to converge in distribution under some partial independence conditions. The associated stationary distribution can further be shown to be close to the true posterior distribution and some hierarchical versions of the proposed mechanism enjoy a closed form limiting distribution. Experiments also demonstrate the gain in efficiency brought by the Gibbs version over the standard solution.en
dc.publisher.nameCahier de recherche CEREMADE, Université Paris-Dauphineen
dc.publisher.cityParisen
dc.identifier.citationpages30en
dc.relation.ispartofseriestitleCahier de recherche CEREMADEen
dc.identifier.urlsitehttps://hal.archives-ouvertes.fr/hal-02274914v1en
dc.subject.ddclabelAnalyseen
dc.identifier.citationdate2019-05
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2019-09-04T11:25:55Z
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