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Large deviations in estimation of an Ornstein-Uhlenbeck model

dc.contributor.authorPham, Huyen
dc.contributor.authorFlorens, Danielle
dc.date.accessioned2011-06-08T09:53:59Z
dc.date.available2011-06-08T09:53:59Z
dc.date.issued1999
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/6449
dc.language.isoenen
dc.subjectLarge deviationsen
dc.subjectrate functionen
dc.subjectOrnstein-Uhlenbeck diffusion processen
dc.subjectdrift estimationen
dc.subject.ddc519en
dc.titleLarge deviations in estimation of an Ornstein-Uhlenbeck modelen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenA large deviation principle (LDP) with an explicit rate function is proved for the estimation of drift parameter of the Ornstein-Uhlenbeck process. We establish an LDP for two estimating functions, one of them being the score function. The first one is derived by applying the Gärtner-Ellis theorem. But this theorem is not suitable for the LDP on the score function and we circumvent this key point by using a parameter-dependent change of measure. We then state large deviation principles for the maximum likelihood estimator and another consistent drift estimator.en
dc.relation.isversionofjnlnameJournal of Applied Probability
dc.relation.isversionofjnlvol36en
dc.relation.isversionofjnlissue1en
dc.relation.isversionofjnldate1999
dc.relation.isversionofjnlpages60-77en
dc.relation.isversionofdoihttp://dx.doi.org/10.1239/jap/1032374229en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherApplied Probability Trusten
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


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