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dc.contributor.authorJohnson, Rachel T.
dc.contributor.authorMontgomery, Douglas C.
dc.contributor.authorJones, Bradley
dc.contributor.authorParker, Peter T.
dc.date.accessioned2014-03-24T19:54:36Z
dc.date.available2014-03-24T19:54:36Z
dc.date.issued2010-01
dc.identifier.citationJournal of Quality Technology, Jan. 2010, vo.42, no.1, pp.86-102.
dc.identifier.urihttp://hdl.handle.net/10945/39563
dc.descriptionThe use of simulation as a modeling and analysis tool is wide spread. Simulation is an enabling tool for experimentally virtually on a validated computer environment. Often the underlying function for a computer experiment result has too much curvalture to be adequately modeled by a low-order polynomial. In such cases, finding an appropriate experimental design is not easy. We evaluate several computer experiments assuming the modeler is interested in fitting a high-order polynomial to the response data considering both optimal and space-filling designs. We also introduce a new class of hybrid designs that can be used for deterministic or stochastic simulation mmodels.en_US
dc.publisherABI/INFORM Globalen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleComparing computer experiments for fitting high-order polynomial metamodelsen_US
dc.typeArticleen_US
dc.contributor.corporateNaval Postgraduate School, Monterey, California
dc.contributor.departmentOperations Research
dc.subject.authoroptimal designen_US
dc.subject.authorresponse surfaceen_US
dc.subject.authorspace-filling designen_US


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