Preprints, Working Papers, ... Year : 2009

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

Abstract

A 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.

Fichier principal
Vignette du fichier
dgarm.pdf (365.11 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Licence
Loading...

Dates and versions

hal-00370685 , version 1 (01-04-2009)

Licence

Identifiers

Cite

Randal Douc, Aurélien Garivier, Éric Moulines, Jimmy Olsson. On the Forward Filtering Backward Smoothing particle approximations of the smoothing distribution in general state spaces models. 2009. ⟨hal-00370685⟩
285 View
246 Download

Altmetric

Share

  • More