Goldstein, M. and Rougier, J. C. (2006) 'Bayes linear calibrated prediction for complex systems.', Journal of the American Statistical Association., 101 (475). pp. 1132-1143.
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.
| Item Type: | Article |
|---|---|
| Keywords: | Emulator, Calibration, Hat run, Thermohaline circulation (THC). |
| Full text: | (AM) Accepted Manuscript Download PDF (236Kb) |
| Status: | Peer-reviewed |
| Publisher Web site: | http://dx.doi.org/10.1198/016214506000000203 |
| Publisher 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. |
| Date accepted: | No date available |
| Date deposited: | 12 August 2016 |
| Date of first online publication: | September 2006 |
| Date first made open access: | No date available |
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