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The polar slice sampler.

Roberts, Gareth O. and Rosenthal, Jeffrey S. (2002) The polar slice sampler. Stochastic Models, 18 (2). pp. 257-280. ISSN 1532-6349

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Abstract

This paper investigates the polar slice sampler, a particular type of the Markov chain Monte Carlo algorithm known as the slice sampler. This algorithm is shown to have convergence properties which under some circumstances are essentially independent of the dimension of the problem. For log-concave densities, the algorithm probably converges (from an appropriate starting point) to within 0.01 of stationarity in total variation distance in a number of iterations given as a computable function of the spherical asymmetry of the density. In particular, for spherically symmetric log-concave densities, in arbitrary dimension, with an appropriate starting point, we prove that the algorithm converges in, at most, 525 iterations. Simulations are done which confirm the polar slice sampler's excellent performance.

Item Type: Article
Journal or Publication Title: Stochastic Models
Subjects: Q Science > QA Mathematics
Departments: Faculty of Science and Technology > Lancaster Environment Centre
ID Code: 19291
Deposited By: ep_ss_importer
Deposited On: 18 Nov 2008 16:50
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 15:27
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/19291

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