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Robust MEWMA-type Control Charts for Monitoring the Covariance Matrix of Multivariate Processes

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dc.contributor.authorXiao, Peien
dc.contributor.committeechairReynolds, Marion R. Jr.en
dc.contributor.committeememberKim, Dong-Yun Hanen
dc.contributor.committeememberDu, Pangen
dc.contributor.committeememberWoodall, William H.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2013-03-07T09:00:07Zen
dc.date.available2013-03-07T09:00:07Zen
dc.date.issued2013-03-06en
dc.description.abstractIn multivariate statistical process control it is generally assumed that the process variables follow a multivariate normal distribution with mean vector " and covariance matrix •, but this is rarely satisfied in practice. Some robust control charts have been developed to monitor the mean and variance of univariate processes, or the mean vector " of multivariate processes, but the development of robust multivariate charts for monitoring • has not been adequately addressed. The control charts that are most affected by departures from normality are actually the charts for • not the charts for ". In this article, the robust design of several MEWMA-type control charts for monitoring • is investigated. In particular, the robustness and efficiency of different MEWMA-type control charts are compared for the in-control and out-of-control cases over a variety of multivariate distributions. Additionally, the total extra quadratic loss is proposed to evaluate the overall performance of control charts for multivariate processes.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:338en
dc.identifier.urihttp://hdl.handle.net/10919/19280en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectMultivariate control charten
dc.subjectnon-normal processesen
dc.subjectRobustnessen
dc.subjectQuadratic lossen
dc.titleRobust MEWMA-type Control Charts for Monitoring the Covariance Matrix of Multivariate Processesen
dc.typeDissertationen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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