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dc.contributor.authorFlorens, Danielle
dc.contributor.authorPham, Huyen
dc.date.accessioned2011-06-23T09:01:34Z
dc.date.available2011-06-23T09:01:34Z
dc.date.issued1998
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/6579
dc.language.isoenen
dc.subjectLarge deviationsen
dc.subjectPoisson random measuresen
dc.subjectMaximum likelihood estimatoren
dc.subject.ddc519en
dc.titleLarge deviation probabilities in estimation of Poisson random measuresen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe consider the parametric estimation problem of intensity measure of a Poisson random measure. We prove large deviation principles for Poisson random measures and an implicit contraction principle. These results are applied to provide a large deviation principle for a maximum likelihood estimator in a parametric statistical model and to explicitly identify the rate function.en
dc.relation.isversionofjnlnameStochastic Processes and their Applications
dc.relation.isversionofjnlvol76en
dc.relation.isversionofjnlissue1en
dc.relation.isversionofjnldate1998
dc.relation.isversionofjnlpages117-139en
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/S0304-4149(98)00005-2en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


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