Kriging metamodelling in simulation: A review

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This article reviews Kriging (also called spatial correlation modeling). It presents the basic Kriging assumptions and formulas—contrasting Kriging and classic linear regression metamodels. Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor. Besides classic one-shot statistical designs such as Latin Hypercube Sampling, it reviews sequentialized and customized designs for sensitivity analysis and optimization. It ends with topics for future research.
Original languageEnglish
Pages (from-to)707-716
JournalEuropean Journal of Operational Research
Volume192
Issue number3
Publication statusPublished - 2009

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Metamodeling
Kriging
Linear regression
Sensitivity analysis
Simulation
Sampling
Latin Hypercube Sampling
Bootstrapping
Spatial Correlation
Metamodel
Sensitivity Analysis
Predictors
Review
Optimization
Modeling
Estimate

Cite this

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title = "Kriging metamodelling in simulation: A review",
abstract = "This article reviews Kriging (also called spatial correlation modeling). It presents the basic Kriging assumptions and formulas—contrasting Kriging and classic linear regression metamodels. Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor. Besides classic one-shot statistical designs such as Latin Hypercube Sampling, it reviews sequentialized and customized designs for sensitivity analysis and optimization. It ends with topics for future research.",
author = "J.P.C. Kleijnen",
note = "Appeared earlier as CentER DP 2007-13",
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language = "English",
volume = "192",
pages = "707--716",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science BV",
number = "3",

}

Kriging metamodelling in simulation : A review. / Kleijnen, J.P.C.

In: European Journal of Operational Research, Vol. 192, No. 3, 2009, p. 707-716.

Research output: Contribution to journalArticleScientificpeer-review

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