ON VARIANCE STABILISATION IN PMC BY DOUBLE RAO-BLACKWELLISATION

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.

Keywords: Importance Sampling mixture, adaptive Monte Carlo, Population Monte Carlo, multimodality, mixture of distributions, random walk.