Professor Michael Goldstein michael.goldstein@durham.ac.uk
Professor
Bayes Linear Calibrated Prediction for Complex Systems
Goldstein, M.; Rougier, J.C.
Authors
J.C. Rougier
Abstract
A calibration-based approach is developed for predicting the behavior of a physical system that is modeled by a computer simulator. The approach is based on Bayes linear adjustment using both system observations and evaluations of the simulator at parameterizations that appear to give good matches to those observations. This approach can be applied to complex high-dimensional systems with expensive simulators, where a fully Bayesian approach would be impractical. It is illustrated with an example concerning the collapse of the thermohaline circulation (THC) in the Atlantic Ocean.
Citation
Goldstein, M., & Rougier, J. (2006). Bayes Linear Calibrated Prediction for Complex Systems. Journal of the American Statistical Association, 101(475), 1132-1143. https://doi.org/10.1198/016214506000000203
Journal Article Type | Article |
---|---|
Publication Date | Sep 1, 2006 |
Deposit Date | Apr 25, 2007 |
Publicly Available Date | Mar 29, 2024 |
Journal | Journal of the American Statistical Association |
Print ISSN | 0162-1459 |
Electronic ISSN | 1537-274X |
Publisher | Taylor and Francis Group |
Peer Reviewed | Peer Reviewed |
Volume | 101 |
Issue | 475 |
Pages | 1132-1143 |
DOI | https://doi.org/10.1198/016214506000000203 |
Keywords | Emulator, Calibration, Hat run, Thermohaline circulation (THC). |
Related Public URLs | http://www.maths.dur.ac.uk/stats/people/jcr/BLCP-a4.pdf |
Files
Accepted Journal Article
(241 Kb)
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Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis Group in The Journal of the American Statistical Association on 01/09/2006, available online at: http://www.tandfonline.com/10.1198/016214506000000203.
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