A Framework for Validation of Computer Models

نویسندگان

  • Maria J. Bayarri
  • James O. Berger
  • Rui Paulo
  • Jerry Sacks
  • John A. Cafeo
  • James C. Cavendish
  • Chin-Hsu Lin
  • Jian Tu
چکیده

In this paper, we present a framework that enables computer model evaluation oriented towards answering the question: Does the computer model adequately represent reality? The proposed validation framework is a six-step procedure based upon a mix of Bayesian statistical methodology and likelihood methodology. The methodology is particularly suited to treating the major issues associated with the validation process: quantifying multiple sources of error and uncertainty in computer models; combining multiple sources of information; and updating validation assessments as new information is acquired. Moreover, it allows inferential statements to be made about predictive error associated with model predictions in untested situations. The framework is illustrated on two test bed models (a pedagogic example and a resistance spot weld model) that provide context for each of the six steps in the proposed validation process. ∗David Higdon and Marc Kennedy were central to the development of an earlier version of this framework.

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عنوان ژورنال:
  • Technometrics

دوره 49  شماره 

صفحات  -

تاریخ انتشار 2007