Abstract : Population Monte Carlo has been introduced as a sequential importance sampling technique to overcome poor fit of the importance function. The performance of the original Population Monte Carlo algorithm is compared with a modified version that eliminates the influence of the transition particle via a double Rao–Blackwellisation. This modification is shown to improve the exploration of the modes through a large simulation experiment on posterior distributions of mean mixtures of distributions.
Type de document :
Article dans une revue
Computational Statistics and Data Analysis, Elsevier, 2010, 54 (3), pp.698-710
https://hal.inria.fr/inria-00260141
Contributeur : Jean-Michel Marin
<>
Soumis le : lundi 3 mars 2008 - 13:30:56
Dernière modification le : mercredi 12 septembre 2018 - 01:28:32
Document(s) archivé(s) le : vendredi 28 septembre 2012 - 10:32:31
Alessandra Iacobucci, Jean-Michel Marin, Christian Robert. On variance stabilisation in Population Monte Carlo by double Rao-Blackwellisation. Computational Statistics and Data Analysis, Elsevier, 2010, 54 (3), pp.698-710. 〈inria-00260141〉
