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WSC
2008

Stochastic kriging for simulation metamodeling

13 years 6 months ago
Stochastic kriging for simulation metamodeling
We extend the basic theory of kriging, as applied to the design and analysis of deterministic computer experiments, to the stochastic simulation setting. Our goal is to provide flexible, interpolation-based metamodels of simulation output performance measures as functions of the controllable design or decision variables. To accomplish this we characterize both the intrinsic uncertainty inherent in a stochastic simulation and the extrinsic uncertainty about the unknown response surface. We use tractable examples to demonstrate why it is critical to characterize both types of uncertainty, derive general results for experiment design and analysis, and present a numerical example that illustrates the stochastic kriging method.
Bruce E. Ankenman, Barry L. Nelson, Jeremy Staum
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where WSC
Authors Bruce E. Ankenman, Barry L. Nelson, Jeremy Staum
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