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Bayesian Validation of Computer Models

Summary: [This abstract is based on the authors' abstract.] A Bayesian approach to computer model validation is proposed that avoids problems encountered in approaches proposed by earlier researchers. This approach focuses on first deriving the posteriors of the computer model and model bias separately, then deriving the posterior of the true output. The result is a clear decomposition of the expected prediction error of the true output that explains how combining computer outputs and physical experiments can provide more accurate prediction than either can provide alone. Supplemental materials are available online.

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  • Topics: Design of Experiments, Problem Solving
  • Keywords: Computer models, Bayesian methods, Gaussian curve, Bias, Validation, Experiments
  • Author: Wang, Shuchun; Chen, Wei; Tsui, Kwok-Leung
  • Journal: Technometrics