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Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets

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Sherlock, Chris and Roberts, Gareth O.. (2009) Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets. Bernoulli, Vol.15 (No.3). pp. 774-798. ISSN 1350-7265

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Official URL: http://dx.doi.org/10.3150/08-BEJ176

Abstract

Scaling of proposals for Metropolis algorithms is an important practical problem in MCMC implementation. Criteria for scaling based on empirical acceptance rates of algorithms have been found to work consistently well across a broad range of problems. Essentially, proposal jump sizes are increased when acceptance rates are high and decreased when rates are low. In recent years, considerable theoretical support has been given for rules of this type which work on the basis that acceptance rates around 0.234 should be preferred. This has been based on asymptotic results that approximate high dimensional algorithm trajectories by diffusions. In this paper, we develop a novel approach to understanding 0.234 which avoids the need for diffusion limits. We derive explicit formulae for algorithm efficiency and acceptance rates as functions of the scaling parameter. We apply these to the family of elliptically symmetric target densities, where further illuminating explicit results are possible. Under suitable conditions, we verify the 0.234 rule for a new class of target densities. Moreover, we can characterise cases where 0.234 fails to hold, either because the target density is too diffuse in a sense we make precise, or because the eccentricity of the target density is too severe, again in a sense we make precise. We provide numerical verifications of our results.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Distribution (Probability theory)
Journal or Publication Title: Bernoulli
Publisher: Int Statistical Institute
ISSN: 1350-7265
Date: August 2009
Volume: Vol.15
Number: No.3
Number of Pages: 25
Page Range: pp. 774-798
Identification Number: 10.3150/08-BEJ176
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
References: [1] Apostol, T.M. (1974). Mathematical Analysis. Reading, MA: Addison-Wesley. MR0344384 [2] Bedard, M. (2007). Weak convergence of Metropolis algorithms for non-iid target distributions. Ann. Appl. Probab. 17 1222–1244. MR2344305 [3] Breyer, L.A. and Roberts, G.O. (2000). From Metropolis to diffusions: Gibbs states and optimal scaling. Stochastic Process. Appl. 90 181–206. MR1794535 [4] Fang, K.T., Kotz, S. and Ng, K.W. (1990). Symmetric Multivariate and Related Distributions. Monographs on Statistics and Applied Probability 36. London: Chapman and Hall. MR1071174 [5] Gelman, A., Roberts, G.O. and Gilks, W.R. (1996). Efficient Metropolis jumping rules. In Bayesian Statistics, 5 (Alicante, 1994) 599–607. New York: Oxford Univ. Press. MR1425429 [6] Krzanowski, W.J. (2000). Principles of Multivariate Analysis: A User’s Perspective, 2nd ed. Oxford Statistical Science Series 22. New York: The Clarendon Press Oxford Univ. Press. MR1133626 [7] Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H. and Teller, E. (1953). Equations of state calculations by fast computing machine. J. Chem. Phys. 21 1087–1091. [8] Roberts, G.O. (1998). Optimal metropolis algorithms for product measures on the vertices of a hypercube. Stochastics Stochastic Rep. 62 275–283. MR1613256 [9] Roberts, G.O., Gelman, A. and Gilks,W.R. (1997).Weak convergence and optimal scaling of random walk Metropolis algorithms. Ann. Appl. Probab. 7 110–120. MR1428751 [10] Roberts, G.O. and Rosenthal, J.S. (2001). Optimal scaling for various Metropolis–Hastings algorithms. Statist. Sci. 16 351–367. MR1888450 [11] Sherlock, C. (2006).Methodology for inference on the Markov modulated Poisson process and theory for optimal scaling of the random walk Metropolis. Ph.D. thesis, Lancaster University. Available at http://eprints.lancs.ac.uk/850/.
URI: http://wrap.warwick.ac.uk/id/eprint/17180

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