On the Forward Filtering Backward Smoothing particle approximations of the smoothing distribution in general state spaces models

dc.creatorDouc, Randal
dc.creatorGarivier, Aurelien
dc.creatorMoulines, Eric
dc.creatorOlsson, Jimmy
dc.date2009-04-02
dc.date.accessioned2026-07-07T12:59:32Z
dc.date.available2026-07-07T12:59:32Z
dc.descriptionA prevalent problem in general state-space models is the approximation of the smoothing distribution of a state, or a sequence of states, conditional on the observations from the past, the present, and the future. The aim of this paper is to provide a rigorous foundation for the calculation, or approximation, of such smoothed distributions, and to analyse in a common unifying framework different schemes to reach this goal. Through a cohesive and generic exposition of the scientific literature we offer several novel extensions allowing to approximate joint smoothing distribution in the most general case with a cost growing linearly with the number of particles.
dc.identifierhttps://arxiv.org/abs/0904.0316
dc.identifierhttp://arxiv.org/abs/0904.0316
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/225605
dc.subjectStatistics Theory
dc.subject60G10, 60K35, 60G18
dc.titleOn the Forward Filtering Backward Smoothing particle approximations of the smoothing distribution in general state spaces models
dc.typetext

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