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A metropolis-class sampler for targets with non-convex support
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Zocca, Alessandro, Vogrinc, Jure and Moriarty, John (2021) A metropolis-class sampler for targets with non-convex support. Statistics and Computing, 31 . 72. doi:10.1007/s11222-021-10044-4 ISSN 0960-3174.
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Official URL: http://dx.doi.org/10.1007/s11222-021-10044-4
Abstract
We aim to improve upon the exploration of the general-purpose random walk Metropolis algorithm when the target has non-convex support A⊂Rd, by reusing proposals in Ac which would otherwise be rejected. The algorithm is Metropolis-class and under standard conditions the chain satisfies a strong law of large numbers and central limit theorem. Theoretical and numerical evidence of improved performance relative to random walk Metropolis are provided. Issues of implementation are discussed and numerical examples, including applications to global optimisation and rare event sampling, are presented.
Item Type: | Journal Article | ||||||||||||||||||
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Subjects: | Q Science > QA Mathematics | ||||||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Markov processes, Monte Carlo method, Mathematical statistics, Random walks (Mathematics) | ||||||||||||||||||
Journal or Publication Title: | Statistics and Computing | ||||||||||||||||||
Publisher: | Springer | ||||||||||||||||||
ISSN: | 0960-3174 | ||||||||||||||||||
Official Date: | 15 September 2021 | ||||||||||||||||||
Dates: |
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Volume: | 31 | ||||||||||||||||||
Article Number: | 72 | ||||||||||||||||||
DOI: | 10.1007/s11222-021-10044-4 | ||||||||||||||||||
Status: | Peer Reviewed | ||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||
Date of first compliant deposit: | 1 September 2021 | ||||||||||||||||||
Date of first compliant Open Access: | 28 September 2021 | ||||||||||||||||||
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