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
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Dernière modification le : jeudi 22 novembre 2018 - 01:21:02
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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〉
