dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:23:58Z
dc.date.available2014-05-27T11:23:58Z
dc.date.created2014-05-27T11:23:58Z
dc.date.issued2009-09-01
dc.identifierPesquisa Operacional, v. 29, n. 3, p. 547-562, 2009.
dc.identifier0101-7438
dc.identifier1678-5142
dc.identifierhttp://hdl.handle.net/11449/71125
dc.identifier10.1590/S0101-74382009000300005
dc.identifierS0101-74382009000300005
dc.identifier2-s2.0-77955602950
dc.identifier2-s2.0-77955602950.pdf
dc.description.abstractThe T2 chart and the generalized variance |S| chart are the usual tools for monitoring the mean vector and the covariance matrix of multivariate processes. The main drawback of these charts is the difficulty to obtain and to interpret the values of their monitoring statistics. In this paper, we study control charts for monitoring bivariate processes that only requires the computation of sample means (the ZMAX chart) for monitoring the mean vector, sample variances (the VMAX chart) for monitoring the covariance matrix, or both sample means and sample variances (the MCMAX chart) in the case of the joint control of the mean vector and the covariance matrix.
dc.languageeng
dc.relationPesquisa Operacional
dc.relation0,365
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectBivariate processes
dc.subjectControl charts
dc.subjectCovariance matrix
dc.subjectMean vector
dc.titleMonitoring bivariate processes
dc.typeArtículos de revistas


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