DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, Xi | ko |
dc.contributor.author | Kim, Kyoung-Kuk | ko |
dc.date.accessioned | 2014-08-29T02:12:17Z | - |
dc.date.available | 2014-08-29T02:12:17Z | - |
dc.date.created | 2014-05-20 | - |
dc.date.created | 2014-05-20 | - |
dc.date.created | 2014-05-20 | - |
dc.date.created | 2014-05-20 | - |
dc.date.issued | 2014-02 | - |
dc.identifier.citation | ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION, v.24, no.2 | - |
dc.identifier.issn | 1049-3301 | - |
dc.identifier.uri | http://hdl.handle.net/10203/188996 | - |
dc.description.abstract | Stochastic kriging has been studied as an effective metamodeling technique for approximating response surfaces in the context of stochastic simulation. In a simulation experiment, an analyst typically needs to estimate relevant metamodel parameters and further do prediction; therefore, the impact of parameter estimation on the performance of the metamodel-based predictor has drawn some attention in the literature. However, how the standard stochastic kriging predictor is affected by the presence of bias in finite-sample estimates has not yet been fully investigated. In this article, we study the predictive performance and investigate optimal budget allocation rules subject to a fixed computational budget constraint. Furthermore, we extend the analysis to two-level or nested simulation, which has been recently documented in the risk management literature, with biased estimators. | - |
dc.language | English | - |
dc.publisher | ASSOC COMPUTING MACHINERY | - |
dc.title | Stochastic kriging with biased sample estimates | - |
dc.type | Article | - |
dc.identifier.wosid | 000334526100002 | - |
dc.identifier.scopusid | 2-s2.0-84897431730 | - |
dc.type.rims | ART | - |
dc.citation.volume | 24 | - |
dc.citation.issue | 2 | - |
dc.citation.publicationname | ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION | - |
dc.identifier.doi | 10.1145/2567893 | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.contributor.localauthor | Kim, Kyoung-Kuk | - |
dc.contributor.nonIdAuthor | Chen, Xi | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Simulation output analysis | - |
dc.subject.keywordAuthor | simulation theory | - |
dc.subject.keywordAuthor | simulation experimental design | - |
dc.subject.keywordAuthor | metamodeling | - |
dc.subject.keywordAuthor | nested simulation | - |
dc.subject.keywordAuthor | optimal budget allocation | - |
dc.subject.keywordAuthor | Simulation output analysis | - |
dc.subject.keywordAuthor | simulation theory | - |
dc.subject.keywordAuthor | simulation experimental design | - |
dc.subject.keywordAuthor | metamodeling | - |
dc.subject.keywordAuthor | nested simulation | - |
dc.subject.keywordAuthor | optimal budget allocation | - |
dc.subject.keywordPlus | EFFICIENT NESTED SIMULATION | - |
dc.subject.keywordPlus | EXPECTED SHORTFALL | - |
dc.subject.keywordPlus | RISK MEASUREMENT | - |
dc.subject.keywordPlus | PREDICTION | - |
dc.subject.keywordPlus | VARIANCE | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordPlus | EFFICIENT NESTED SIMULATION | - |
dc.subject.keywordPlus | EXPECTED SHORTFALL | - |
dc.subject.keywordPlus | RISK MEASUREMENT | - |
dc.subject.keywordPlus | PREDICTION | - |
dc.subject.keywordPlus | VARIANCE | - |
dc.subject.keywordPlus | MODELS | - |
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