A stable manifold MCMC method for high dimensions

Alexandros Beskos

Statistics & Probability Letters, 2014, vol. 90, issue C, 46-52

Abstract: We combine two important recent advancements of MCMC algorithms: first, methods utilizing the intrinsic manifold structure of the parameter space; then, algorithms effective for targets in infinite-dimensions with the critical property that their mixing time is robust to mesh refinement.

Keywords: Manifold MCMC; Metropolis-adjusted Langevin algorithm; Cameron–Martin space; Infinite dimensions (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1016/j.spl.2014.03.016

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