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Bayesian forecasting for complex systems using computer simulators

Craig, P.S.; Goldstein, M.; Rougier, J.C.; Seheult, A.H.


J.C. Rougier

A.H. Seheult


Although computer models are often used for forecasting future outcomes of complex systems, the uncertainties in such forecasts are not usually treated formally. We describe a general Bayesian approach for using a computer model or simulator of a complex system to forecast system outcomes. The approach is based on constructing beliefs derived from a combination of expert judgments and experiments on the computer model. These beliefs, which are systematically updated as we make runs of the computer model, are used for either Bayesian or Bayes linear forecasting for the system. Issues of design and diagnostics are described in the context of forecasting. The methodology is applied to forecasting for an active hydrocarbon reservoir.


Craig, P., Goldstein, M., Rougier, J., & Seheult, A. (2001). Bayesian forecasting for complex systems using computer simulators. Journal of the American Statistical Association, 96(454), 717-729.

Journal Article Type Article
Publication Date Jun 1, 2001
Deposit Date Apr 25, 2007
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 96
Issue 454
Pages 717-729