Seminar: "Variance reduction for MCMC estimators"

AUEB STATISTICS SEMINAR SERIES DECEMBER 2021

Angelos Alexopoulos (Research Associate, MRC Biostatistics Unit, University of Cambridge, UK)

Variance reduction for MCMC estimators

ABSTRACT

We provide a general methodology to construct control variates for any discrete time random walk Metropolis and Metropolis-adjusted Langevin algorithm. By adopting the proposed methods we achieve, in a post-processing manner and with a negligible additional computational cost, impressive variance reduction when compared to the standard MCMC ergodic averages. Our proposed estimators are based on an approximate solution of the Poisson equation for multivariate Gaussian target densities of any dimension.

This is joint work with P. Dellaportas (UCL and AUEB) and M. Titsias (DeepMind)

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