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dc.contributor.authorHoffmann, Marc*
dc.contributor.authorMarguet, Aline*
dc.date.accessioned2018-03-09T11:19:03Z
dc.date.available2018-03-09T11:19:03Z
dc.date.issued2019
dc.identifier.issn0304-4149
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17524
dc.language.isoenen
dc.subjectstatistical estimation
dc.subjectBranching processes
dc.subjectbifurcating Markov chains
dc.subjectgeometric ergodicity
dc.subjectscalar diffusions
dc.subject.ddc519en
dc.titleStatistical estimation in a randomly structured branching population
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe consider a binary branching process structured by a stochastic trait that evolves according to a diffusion process that triggers the branching events, in the spirit of Kimmel's model of cell division with parasite infection. Based on the observation of the trait at birth of the first n generations of the process, we construct nonparametric estimator of the transition of the associated bifurcating chain and study the parametric estimation of the branching rate. In the limit n → ∞, we obtain asymptotic efficiency in the parametric case and minimax optimality in the nonparametric case.
dc.relation.isversionofjnlnameStochastic Processes and their Applications
dc.relation.isversionofjnlvol129
dc.relation.isversionofjnlissue12
dc.relation.isversionofjnldate2019
dc.relation.isversionofjnlpages5236-5277
dc.relation.isversionofdoi10.1016/j.spa.2019.02.015
dc.relation.isversionofjnlpublisherElsevier
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewedoui
dc.date.updated2020-05-05T12:17:23Z
hal.person.labIds60*
hal.person.labIds89626*


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