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hal.structure.identifierAdvanced Learning Evolutionary Algorithms [ALEA]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorDEL MORAL, Pierre
hal.structure.identifierCentre de Recherche en Économie et Statistique [CREST]
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorJACOB, Pierre E.
hal.structure.identifierDepartment of Statistics [Oxford]
dc.contributor.authorLEE, Anthony
hal.structure.identifierCSIRO Mathematics, Informatics and Statistics
dc.contributor.authorMURRAY, Lawrence
hal.structure.identifierUniversity College of London [London] [UCL]
dc.contributor.authorPETERS, Gareth W.
dc.date.created2012-11-30
dc.description.abstractEnThis article is concerned with the design and analysis of discrete time Feynman-Kac particle integration models with geometric interacting jump processes. We analyze two general types of model, corresponding to whether the reference process is in continuous or discrete time. For the former, we consider discrete generation particle models defined by arbitrarily fine time mesh approximations of the Feynman-Kac models with continuous time path integrals. For the latter, we assume that the discrete process is observed at integer times and we design new approximation models with geometric interacting jumps in terms of a sequence of intermediate time steps between the integers. In both situations, we provide non asymptotic bias and variance theorems w.r.t. the time step and the size of the system, yielding what appear to be the first results of this type for this class of Feynman-Kac particle integration models. We also discuss uniform convergence estimates w.r.t. the time horizon. Our approach is based on an original semigroup analysis with first order decompositions of the fluctuation errors.
dc.language.isoen
dc.title.enFeynman-Kac particle integration with geometric interacting jumps
dc.typeDocument de travail - Pré-publication
dc.subject.halMathématiques [math]/Probabilités [math.PR]
dc.subject.halStatistiques [stat]/Théorie [stat.TH]
dc.identifier.arxiv1211.7191
hal.identifierhal-00932222
hal.version1
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00932222v1
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