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)
Proceedings in Applied Mathematics & Mechanics – Wiley
Published: Jan 1, 2017
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