Mathematics – Statistics Theory
Scientific paper
2006-09-19
Bernoulli 14, 1 (2008) 155-179
Mathematics
Statistics Theory
Published in at http://dx.doi.org/10.3150/07-BEJ6150 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statist
Scientific paper
10.3150/07-BEJ6150
This paper concerns the use of sequential Monte Carlo methods (SMC) for smoothing in general state space models. A well-known problem when applying the standard SMC technique in the smoothing mode is that the resampling mechanism introduces degeneracy of the approximation in the path space. However, when performing maximum likelihood estimation via the EM algorithm, all functionals involved are of additive form for a large subclass of models. To cope with the problem in this case, a modification of the standard method (based on a technique proposed by Kitagawa and Sato) is suggested. Our algorithm relies on forgetting properties of the filtering dynamics and the quality of the estimates produced is investigated, both theoretically and via simulations.
Cappé Olivier
Douc Randal
Moulines Eric
Olsson Jimmy
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