The Library
Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets
Tools
Tools
Tools
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. doi:10.3150/08-BEJ176
![[img]](http://wrap.warwick.ac.uk/style/images/fileicons/application_pdf.png)
|
PDF
WRAP_Sherlock_euclid.bj.1251463281.pdf - Published Version - Requires a PDF viewer. Download (393Kb) |
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 | ||||
| Official Date: | August 2009 | ||||
| Dates: |
|
||||
| Volume: | Vol.15 | ||||
| Number: | No.3 | ||||
| Number of Pages: | 25 | ||||
| Page Range: | pp. 774-798 | ||||
| DOI: | 10.3150/08-BEJ176 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Open Access |
Data sourced from Thomson Reuters' Web of Knowledge
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
