Summary
We shall briefly review recent progress in Global Quantitative Uncertainty and Sensitivity Analysis (UA/SA) techniques, relating these to multidimensional global calibration approaches of the “Monte Carlo filtering” type. Global quantitative techniques for Sensitivity Analysis (SA), that are based on the decomposition of the variance of the target model output, have received a considerable boost in recent years, due both to more efficient computational strategies and to a widening of their range of applications. Monte Carlo Filtering, and the GLUE (Generalised Likelihood Uncertainty Estimate) approach that derives from it are also promising tools to use in the presence of structural model uncertainty, as in the case of petroleum engineering that was the focus of the ECMI2002 mini-symposium “Advanced Mathematical Tools for Petroleum System Modelling”.
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References
Learner, E.E.: Specification Searches: Ad Hoc Inference with Nonexperimental Data New York: John Wiley & Sons (1987)
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© 2004 Springer-Verlag Berlin Heidelberg
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Giglioli, N., Tarantola, S., Saltelli, A. (2004). Global Uncertainty and Sensitivity Analysis and Neighbourhoods. In: Buikis, A., Čiegis, R., Fitt, A.D. (eds) Progress in Industrial Mathematics at ECMI 2002. The European Consortium for Mathematics in Industry, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-09510-2_36
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DOI: https://doi.org/10.1007/978-3-662-09510-2_36
Publisher Name: Springer, Berlin, Heidelberg
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