Comparing computer experiments for fitting high-order polynomial metamodels
| dc.contributor.author | Johnson, Rachel T. | |
| dc.contributor.author | Montgomery, Douglas C. | |
| dc.contributor.author | Jones, Bradley | |
| dc.contributor.author | Parker, Peter T. | |
| dc.date.accessioned | 2014-03-24T19:54:36Z | |
| dc.date.available | 2014-03-24T19:54:36Z | |
| dc.date.issued | 2010-01 | |
| dc.identifier.citation | Journal of Quality Technology, Jan. 2010, vo.42, no.1, pp.86-102. | |
| dc.identifier.uri | http://hdl.handle.net/10945/39563 | |
| dc.description | The 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.publisher | ABI/INFORM Global | en_US |
| dc.rights | This 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.title | Comparing computer experiments for fitting high-order polynomial metamodels | en_US |
| dc.type | Article | en_US |
| dc.contributor.corporate | Naval Postgraduate School, Monterey, California | |
| dc.contributor.department | Operations Research | |
| dc.subject.author | optimal design | en_US |
| dc.subject.author | response surface | en_US |
| dc.subject.author | space-filling design | en_US |
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