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Durham University

Department of Mathematical Sciences

Staff

Publication details for Michael Goldstein

Goldstein, M. & Rougier, J.C. (2006). Bayes Linear Calibrated Prediction for Complex Systems. Journal of the American Statistical Association 101(475): 1132-1143.

Author(s) from Durham

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.