Geodesic
Particle filter-based approximate maximum likelihood inference asymptotics in state-space models
Jimmy Olsson1 ; Tobias Rydén1
1 Centre for Mathematical Sciences, Lund University, Box 118, 221 00 Lund, Sweden
ESAIM. Proceedings, Tome 19 (2007), pp. 115-120.

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To implement maximum likelihood estimation in state-space models, the log-likelihood function must be approximated. We study such approximations based on particle filters, and in particular conditions for consistency of the corresponding approximate maximum likelihood estimator. Numerical results illustrate the theory.
DOI : 10.1051/proc:071915

Jimmy Olsson 1 ; Tobias Rydén 1

1 Centre for Mathematical Sciences, Lund University, Box 118, 221 00 Lund, Sweden 
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Jimmy Olsson; Tobias Rydén. Particle filter-based approximate maximum likelihood inference asymptotics in state-space models. ESAIM. Proceedings, Tome 19 (2007), pp. 115-120. doi : 10.1051/proc:071915. http://geodesic.mathdoc.fr/articles/10.1051/proc:071915/

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