A single statistic for monitoring the covariance matrix of bivariate processes

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dc.contributor.authorQuinino, Roberto
dc.contributor.authorCosta, A. [UNESP]
dc.contributor.authorHo, Linda Lee
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Federal de Minas Gerais (UFMG)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T15:33:21Z
dc.date.available2014-05-20T15:33:21Z
dc.date.issued2012-01-01
dc.description.abstractIn this article, we present a new control chart for monitoring the covariance matrix in a bivariate process. In this method, n observations of the two variables were considered as if they came from a single variable (as a sample of 2n observations), and a sample variance was calculated. This statistic was used to build a new control chart specifically as a VMIX chart. The performance of the new control chart was compared with its main competitors: the generalized sampled variance chart, the likelihood ratio test, Nagao's test, probability integral transformation (v(t)), and the recently proposed VMAX chart. Among these statistics, only the VMAX chart was competitive with the VMIX chart. For shifts in both variances, the VMIX chart outperformed VMAX; however, VMAX showed better performance for large shifts (higher than 10%) in one variance.en
dc.description.affiliationUniv São Paulo, BR-05508900 São Paulo, Brazil
dc.description.affiliationUniversidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
dc.description.affiliationSão Paulo State Univ, Dept Prod Engn, São Paulo, Brazil
dc.description.affiliationUnespSão Paulo State Univ, Dept Prod Engn, São Paulo, Brazil
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.format.extent423-430
dc.identifierhttp://dx.doi.org/10.1080/08982112.2012.682046
dc.identifier.citationQuality Engineering. Philadelphia: Taylor & Francis Inc, v. 24, n. 3, p. 423-430, 2012.
dc.identifier.doi10.1080/08982112.2012.682046
dc.identifier.issn0898-2112
dc.identifier.urihttp://hdl.handle.net/11449/42000
dc.identifier.wosWOS:000305516200007
dc.language.isoeng
dc.publisherTaylor & Francis Inc
dc.relation.ispartofQuality Engineering
dc.relation.ispartofjcr1.238
dc.relation.ispartofsjr0,804
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectBivariate processesen
dc.subjectControl charten
dc.subjectVariance monitoringen
dc.titleA single statistic for monitoring the covariance matrix of bivariate processesen
dc.typeArtigo
dcterms.licensehttp://journalauthors.tandf.co.uk/permissions/reusingOwnWork.asp
dcterms.rightsHolderTaylor & Francis Inc
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Engenharia, Guaratinguetápt

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