CHOPIN, Nicolas; DEL MORAL, Pierre; RUBENTHALER, Sylvain

Métadonnées

Licence d’utilisation du document

CHOPIN, Nicolas
Centre de Recherche en Économie et Statistique [CREST]
École Nationale de la Statistique et de l'Administration Économique [ENSAE Paris]

DEL MORAL, Pierre
Advanced Learning Evolutionary Algorithms [ALEA]

RUBENTHALER, Sylvain
Laboratoire Jean Alexandre Dieudonné [JAD]

Langue

Document de travail - Pré-publication

Résumé en anglais

Several particle algorithms admit a Feynman-Kac representation such that the potential function may be expressed as a recursive function which depends on the complete state trajectory. An important example is the mixture Kalman filter, but other models and algorithms of practical interest fall in this category. We study the asymptotic stability of such particle algorithms as time goes to infinity. As a corollary, practical conditions for the stability of the mixture Kalman filter, and a mixture GARCH filter, are derived. Finally, we show that our results can also lead to weaker conditions for the stability of standard particle algorithms, such that the potential function depends on the last state only.< Réduire

Mots clés en anglais

Feynman-Kac formulae

mixture Kalman filter

path-dependent potential function

Particle filter

Project ANR

Méthodes de Monte Carlo en grande dimension - ANR-08-BLAN-0218

Origine

Importé de hal

Unités de recherche

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251