Bayesian Methods for Large Physical SystemsAlan Craig, Peter Craig, Michael Goldstein, Jonathan Rougier, Allan Seheult David Wooff
Department of Mathematical Sciences
University of Durham, Durham DH1 3LE, England
Tel: +44 (0) 191 374 2361
Fax: +44 (0) 191 374 7388
Research supported by the UK Engineering and Physical Sciences Research Council, grant references GR/H52177 and GR/L10031 (final report).
There are several research groups working this this area, but our group is the only group focussed on the problem of large computer simulators, in which there may be hundreds of relevent simulator input variables and simulator outputs, and in which each run of the simulator might take hours or days to complete. These types of simulator are found in applications such as hydrocarbon reservoir management, oceanography and climate modelling, hydrology and environmental monitoring. We are able to handle the huge computational demands of large simulators because we adopt the Bayes linear approach. Details of this approach may be found on the Bayes Linear homepage.
We collaborate actively with commercial partners. We also have extensive software written as libraries of the statistical computing environment R, which are available for use by academics and not-for-profit organisations. Please contact Jonathan Rougier for more details.
On this page you can find information and/or links to the following:
This page is maintained by Jonathan Rougier. Last modified: Wed Aug 7 11:00:53 BST 2002