Talker:  Arnaud Doucet (Oxford U.)

Title: Efficient Implementation of MCMC When Using An Unbiased Likelihood Estimator

Abstract: Particle MCMC methods is a class of MCMC methods relying on high dimensional proposals  built using particle methods. In the first part of the talk I will review the two main particle MCMC schemes that have been proposed in the literature and discuss some recent developments on how one to tune optimally these algorithms. In the second part of the talk I will show how one can harness the remarkable theoretical properties of particle MCMC methods to obtain a perfect simulation procedure.

- slides
- video