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An adaptive approach to Langevin MCMC
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Marshall, T. (Tristan) and Roberts, Gareth O. (2012) An adaptive approach to Langevin MCMC. Statistics and Computing, Volume 22 (Number 5). pp. 1041-1057. doi:10.1007/s11222-011-9276-6 ISSN 0960-3174.
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Official URL: http://dx.doi.org/10.1007/s11222-011-9276-6
Abstract
We consider a class of adaptive MCMC algorithms using a Langevin-type proposal density. We state and prove regularity conditions for the convergence of these algorithms. In addition to these theoretical results we introduce a number of methodological innovations that can be applied much more generally. We assess the performance of these algorithms with simulation studies, including an example of the statistical analysis of a point process driven by a latent log-Gaussian Cox process.
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): | Langevin equations, Markov processes, Monte Carlo method | ||||
Journal or Publication Title: | Statistics and Computing | ||||
Publisher: | Springer | ||||
ISSN: | 0960-3174 | ||||
Official Date: | September 2012 | ||||
Dates: |
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Volume: | Volume 22 | ||||
Number: | Number 5 | ||||
Page Range: | pp. 1041-1057 | ||||
DOI: | 10.1007/s11222-011-9276-6 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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