Cookies

We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.


Durham Research Online
You are in:

Small sample Bayesian designs for complex high-dimensional models based on information gained using fast approximations.

Cumming, J. A. and Goldstein, M. (2009) 'Small sample Bayesian designs for complex high-dimensional models based on information gained using fast approximations.', Technometrics., 51 (4). pp. 377-388.

Abstract

We consider the problem of designing for complex high-dimensional computer models that can be evaluated at different levels of accuracy. Ordinarily, this requires performing many expensive evaluations of the most accurate version of the computer model to obtain a reasonable coverage of the design space. In some cases, it is possible to supplement the information from the accurate model evaluations with a large number of evaluations of a cheap, approximate version of the computer model to enable a more informed design choice. We describe an approach that combines the information from both the approximate model and the accurate model into a single multiscale emulator for the computer model. We then propose a design strategy for selecting a small number of expensive evaluations of the accurate computer model based on our multiscale emulator and a decomposition of the input parameter space. We illustrate our methodology with an example concerning a computer simulation of a hydrocarbon reservoir.

Item Type:Article
Full text:(AM) Accepted Manuscript
Download PDF
(225Kb)
Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1198/TECH.2009.08015
Publisher statement:This is an Accepted Manuscript of an article published by Taylor & Francis Group in Technometrics on 01/01/2012, available online at: http://www.tandfonline.com/10.1198/TECH.2009.08015.
Record Created:08 Aug 2016 12:05
Last Modified:08 Aug 2016 12:09

Social bookmarking: del.icio.usConnoteaBibSonomyCiteULikeFacebookTwitterExport: EndNote, Zotero | BibTex
Look up in GoogleScholar | Find in a UK Library