Multivariate outlier detection based on a robust Mahalanobis distance with shrinkage estimators

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dc.citation.journalTitleSTATISTICAL PAPERSeng
dc.contributor.authorCabana E.
dc.contributor.authorLillo R.E.
dc.contributor.authorLaniado H.
dc.contributor.departmentUniversidad EAFIT. Escuela de Cienciasspa
dc.contributor.researchgroupModelado Matemáticospa
dc.date.accessioned2021-04-12T14:07:18Z
dc.date.available2021-04-12T14:07:18Z
dc.date.issued2019-01-01
dc.description.abstractA collection of robust Mahalanobis distances for multivariate outlier detection is proposed, based on the notion of shrinkage. Robust intensity and scaling factors are optimally estimated to define the shrinkage. Some properties are investigated, such as affine equivariance and breakdown value. The performance of the proposal is illustrated through the comparison to other techniques from the literature, in a simulation study and with a real dataset. The behavior when the underlying distribution is heavy-tailed or skewed, shows the appropriateness of the method when we deviate from the common assumption of normality. The resulting high true positive rates and low false positive rates in the vast majority of cases, as well as the significantly smaller computation time show the advantages of our proposal. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=9902
dc.identifier.doi10.1007/s00362-019-01148-1
dc.identifier.issn09325026
dc.identifier.issn16139798
dc.identifier.otherWOS;000497418400001
dc.identifier.otherSCOPUS;2-s2.0-85075360711
dc.identifier.urihttp://hdl.handle.net/10784/27814
dc.language.isoengeng
dc.publisherSpringer Verlag
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075360711&doi=10.1007%2fs00362-019-01148-1&partnerID=40&md5=44300a8bbc2101dd94758a7730bff452
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/0932-5026
dc.sourceSTATISTICAL PAPERS
dc.subject.keywordComedian matrixeng
dc.subject.keywordMultivariate distanceeng
dc.subject.keywordMultivariate L1-medianeng
dc.subject.keywordRobust location and covariance matrix estimationeng
dc.titleMultivariate outlier detection based on a robust Mahalanobis distance with shrinkage estimatorseng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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