Metropolis‐Hastings Importance Sampling Estimator. Issue 1 (15th March 2018) - Rudolf, Daniel; Sprungk, Björn
Abstract: Based on the proposed states of the Metropolis‐Hastings (MH) algorithm we construct a MH Importance Sampling estimator for the approximation of expectations. The new approximation scheme is asymptotically correct and numerical experiments indicate that it can outperform the classical MH Markov chain Monte Carlo estimator. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)