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dc.contributor.authorCabana, Elisa 
dc.contributor.authorLillo, Rosa Elvira
dc.description.abstractA robust multivariate quality control technique for individual observations is proposed, based on the robust reweighted shrinkage estimators. A simulation study is done to check the performance and compare the method with the classical Hotelling approach, and the robust alternative based on the reweighted minimum covariance determinant estimator. The results show the appropriateness of the method even when the dimension or the Phase I contamination are high, with both independent and correlated variables, showing additional advantages about computational efficiency. The approach is illustrated with two real data-set examples from production
dc.titleRobust multivariate control chart based on shrinkage for individual observationses
dc.typeconference objectes
dc.conference.date20-21 June 2022es
dc.conference.placeUniversity of Naples Federico II, Italyes
dc.conference.titleISBIS CONFERENCE 2022 on "Statistics and Data Science in Business and Industry"*
dc.rights.accessRightsopen accesses
dc.subject.keywordmultivariate process controles
dc.subject.keywordHotelling T2es
dc.subject.keywordreweighted MCDes
dc.subject.keywordreweighted shrinkage estimatores

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