完整後設資料紀錄
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dc.contributor.authorWang, Hsiuyingen_US
dc.contributor.authorHuwang, Longcheenen_US
dc.contributor.authorYu, Jeng Hungen_US
dc.date.accessioned2015-12-02T02:59:04Z-
dc.date.available2015-12-02T02:59:04Z-
dc.date.issued2015-10-01en_US
dc.identifier.issn0377-2217en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.ejor.2015.02.046en_US
dc.identifier.urihttp://hdl.handle.net/11536/127832-
dc.description.abstractIn this study, we focus on improving parameter estimation in Phase I study to construct more accurate Phase II control limits for monitoring multivariate quality characteristics. For a multivariate normal distribution with unknown mean vector, the usual mean estimator is known to be inadmissible under the squared error loss function when the dimension of the variables is greater than 2. Shrinkage estimators, such as the James-Stein estimators, are shown to have better performance than the conventional estimators in the literature. We utilize the James-Stein estimators to improve the Phase I parameter estimation. Multivariate control limits for the Phase II monitoring based on the improved estimators are proposed in this study. The resulting control charts, JS-type charts, are shown to have substantial performance improvement over the existing ones. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectAverage run lengthen_US
dc.subjectControl charten_US
dc.subjectMultivariate normal distributionen_US
dc.subjectJames-Stein estimatoren_US
dc.titleMultivariate control charts based on the James-Stein estimatoren_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.ejor.2015.02.046en_US
dc.identifier.journalEUROPEAN JOURNAL OF OPERATIONAL RESEARCHen_US
dc.citation.volume246en_US
dc.citation.spage119en_US
dc.citation.epage127en_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.identifier.wosnumberWOS:000356742800010en_US
dc.citation.woscount1en_US
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