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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(More)
Measures of surprise refer to quantiications of the degree of incompatibility of data with some hypothesized model H 0 without any reference to alternative models. Traditional measures of surprise have been the p-values, which are however known to grossly overestimate the evidence against H 0. Strict Bayesian analysis calls for an explicit speciication of(More)
A key question in evaluation of computer models is Does the computer model adequately represent reality? A complete Bayesian approach to answering this question is developed for the challenging practical context in which the computer model (and reality) produce functional data. The methodology is particularly suited to treating the major issues associated(More)
Risk assessment of rare natural hazards— such as large volcanic block and ash or pyroclastic flows— is addressed. Assessment is approached through a combination of computer modeling, statistical modeling, and extreme-event probability computation. A computer model of the natural hazard is used to provide the needed extrapolation to unseen parts of the(More)