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Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions

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Hairer, Martin, Stuart, A. M. and Vollmer, Sebastian (2014) Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions. The Annals of Applied Probability, 24 (6). pp. 2455-2490. doi:10.1214/13-AAP982

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Official URL: http://dx.doi.org/10.1214/13-AAP982

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Abstract

We study the problem of sampling high and infinite dimensional target measures arising in applications such as conditioned diffusions and inverse problems. We focus on those that arise from approximating measures on Hilbert spaces defined via a density with respect to a Gaussian reference measure. We consider the Metropolis–Hastings algorithm that adds an accept–reject mechanism to a Markov chain proposal in order to make the chain reversible with respect to the target measure. We focus on cases where the proposal is either a Gaussian random walk (RWM) with covariance equal to that of the reference measure or an Ornstein–Uhlenbeck proposal (pCN) for which the reference measure is invariant.

Previous results in terms of scaling and diffusion limits suggested that the pCN has a convergence rate that is independent of the dimension while the RWM method has undesirable dimension-dependent behaviour. We confirm this claim by exhibiting a dimension-independent Wasserstein spectral gap for pCN algorithm for a large class of target measures. In our setting this Wasserstein spectral gap implies an L2L2-spectral gap. We use both spectral gaps to show that the ergodic average satisfies a strong law of large numbers, the central limit theorem and nonasymptotic bounds on the mean square error, all dimension independent. In contrast we show that the spectral gap of the RWM algorithm applied to the reference measures degenerates as the dimension tends to infinity.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Mathematics
Library of Congress Subject Headings (LCSH): Inverse problems (Differential equations) , Hilbert space, Algorithms , Markov processes, Random walks (Mathematics)
Journal or Publication Title: The Annals of Applied Probability
Publisher: Institute of Mathematical Statistics
ISSN: 1050-5164
Official Date: 26 August 2014
Dates:
DateEvent
26 August 2014Published
26 August 2014Accepted
Date of first compliant deposit: 3 March 2017
Volume: 24
Number: 6
Page Range: pp. 2455-2490
DOI: 10.1214/13-AAP982
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

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