2006
DOI: 10.1198/016214506000000898
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Empirical Bayesian Analysis for Computer Experiments Involving Finite-Difference Codes

Abstract: Computer experiments are increasingly used in scientific investigations as substitutes for physical experiments in cases where the latter are difficult or impossible to perform. A computer experiment consists of several runs of a computer model or "code" for the purpose of better understanding the input → output relationship. One practical difficulty in the use of these models is that a single run may require a prohibitive amount of computational resources in some situations. A recent approach uses statistical… Show more

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Cited by 15 publications
(11 citation statements)
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“…, x r ). Therefore the computer model may be viewed as having an extra factor t, but a scalar output (e.g., Kennedy and O'Hagan 2001;Drignei and Morris 2006). Then one can apply the global output variance decomposition as…”
Section: Functional Anova For Time Series Outputmentioning
confidence: 99%
“…, x r ). Therefore the computer model may be viewed as having an extra factor t, but a scalar output (e.g., Kennedy and O'Hagan 2001;Drignei and Morris 2006). Then one can apply the global output variance decomposition as…”
Section: Functional Anova For Time Series Outputmentioning
confidence: 99%
“…Modeling directly the large output datasets by dense covariance matrices is unpractical, as demonstrated by Drignei and Morris (2006). Instead, a statistical model that closely follows the iterative finite difference relationship will be used, hence incorporating the output data generating mechanism.…”
Section: The Statistical Modelmentioning
confidence: 99%
“…Straightforward generalizations of the univariate case to accommodate analysis of such large output datasets have computational limitations, as pointed out by Drignei and Morris (2006). Straightforward generalizations of the univariate case to accommodate analysis of such large output datasets have computational limitations, as pointed out by Drignei and Morris (2006).…”
Section: Introductionmentioning
confidence: 99%
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