The Library
In search of lost mixing time : adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p
Tools
Griffin, J., Latuszynski, Krzysztof and Steel, Mark F. J. (2021) In search of lost mixing time : adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p. Biometrika, 108 (1). pp. 53-69. doi:10.1093/biomet/asaa055 ISSN 0006-3444.
|
PDF
WRAP-in-search-lost-mixing-time-Steel-2020.pdf - Accepted Version - Requires a PDF viewer. Download (401Kb) | Preview |
Official URL: https://doi.org/10.1093/biomet/asaa055
Abstract
The availability of datasets with large numbers of variables is rapidly increasing. The effective application of Bayesian variable selection methods for regression with these datasets has proved difficult since available Markov chain Monte Carlo methods do not perform well in typical problem sizes of interest. We propose new adaptive Markov chain Monte Carlo algorithms to address this shortcoming. The adaptive design of these algorithms exploits the observation that in large-pā , small-n settings, the majority of the p variables will be approximately uncorrelated a posteriori. The algorithms adaptively build suitable nonlocal proposals that result in moves with squared jumping distance significantly larger than standard methods. Their performance is studied empirically in high-dimensional problems and speed-ups of up to four orders of magnitude are observed.
Item Type: | Journal Article | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Subjects: | Q Science > QA Mathematics | |||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | |||||||||
Library of Congress Subject Headings (LCSH): | Data sets , Bayesian statistical decision theory , Markov processes, Monte Carlo method, Regression analysis | |||||||||
Journal or Publication Title: | Biometrika | |||||||||
Publisher: | Oxford University Press | |||||||||
ISSN: | 0006-3444 | |||||||||
Official Date: | March 2021 | |||||||||
Dates: |
|
|||||||||
Volume: | 108 | |||||||||
Number: | 1 | |||||||||
Page Range: | pp. 53-69 | |||||||||
DOI: | 10.1093/biomet/asaa055 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||
Copyright Holders: | Biometrika Trust | |||||||||
Date of first compliant deposit: | 15 July 2020 | |||||||||
Date of first compliant Open Access: | 5 October 2021 | |||||||||
RIOXX Funder/Project Grant: |
|
|||||||||
Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year