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hal.structure.identifierMathématiques et Informatique Appliquées [MIA Paris-Saclay]
dc.contributor.authorDonnet, Sophie
HAL ID: 14568
ORCID: 0000-0003-4370-7316
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorRivoirard, Vincent
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorRousseau, Judith
dc.date.accessioned2022-11-22T13:22:31Z
dc.date.available2022-11-22T13:22:31Z
dc.date.issued2020
dc.identifier.issn0090-5364
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/23172
dc.language.isoenen
dc.subjectMultivariate counting processen
dc.subjectHawkes processesen
dc.subjectnonparametric Bayesian estimationen
dc.subjectposterior concentration ratesen
dc.subject.ddc519en
dc.titleNonparametric Bayesian estimation for multivariate Hawkes processesen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenThis paper studies nonparametric estimation of parameters of multivariate Hawkes processes. We consider the Bayesian setting and derive posterior concentration rates. First, rates are derived for L1-metrics for stochastic intensities of the Hawkes process. We then deduce rates for the L1-norm of interactions functions of the process. Our results are exemplified by using priors based on piecewise constant functions, with regular or random partitions and priors based on mixtures of Betas distributions. We also present a simulation study to illustrate our results and to study empirically the inference on functional connectivity graphs of neurons.en
dc.relation.isversionofjnlnameAnnals of Statistics
dc.relation.isversionofjnlvol48en
dc.relation.isversionofjnlissue5en
dc.relation.isversionofjnldate2020
dc.relation.isversionofjnlpages2698-2727en
dc.relation.isversionofdoi10.1214/19-AOS1903en
dc.relation.isversionofjnlpublisherInstitute of Mathematical Statisticsen
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingnonen
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershipnon-rechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2022-11-22T12:58:09Z
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