This represents the original developments of Sequential Monte Carlo Samplers in the class of solutions that generalise SMC filtering methods to the case of a fixed state-space. This makes such methods exact and applicable for Bayesian inference in context otherwise typically treated by Markov...

Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. Nevertheless the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC) methods. Not only SMC...

In this paper, the world distribution of personal incomes (WDPI) is estimated using a global sample comprising country sample clones. A clone is a random sample that reproduces – with predetermined high probability and precision – an unknown survey sample using information that is 'encoded'...