Detection of outliers in multivariate data: a method based on clustering and robust estimators.

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dc.contributor.authorPires, Ana M.
dc.contributor.authorSantos-Pereira, Carla
dc.date.accessioned2014-05-30T14:13:48Z
dc.date.available2014-05-30T14:13:48Z
dc.date.issued2002
dc.descriptionOutlier identification is important in many applications in multivariate analysis. Either because there is some specific interest in finding anomalous observations or as a pre-processing task before the application of multivariate method in order to preserve the results from possible harmful effects of those observations. [...]
dc.identifier.citationSantos-Pereira, C., & Pires, A.M. (2002). Detection of outliers in multivariate data: a method based on clustering and robust estimators. In W. Hordle, & B. Ronz,(editors), Proceedings in Computational Statistics (pp.291-296), COMSTAT, Barcelona.pt
dc.identifier.urihttp://hdl.handle.net/11328/755
dc.language.isoengpt
dc.rightsopen accesspt
dc.subjectMultivariate analysispt
dc.subjectOutlier detectionpt
dc.subjectRobust estimationpt
dc.subjectClusteringpt
dc.subjectSupervised classificationpt
dc.titleDetection of outliers in multivariate data: a method based on clustering and robust estimators.pt
dc.typeconferenceObjectpt
dspace.entity.typePublicationen
person.affiliation.nameREMIT
person.familyNameSantos-Pereira
person.givenNameCarla
person.identifier.ciencia-idDD11-7CE2-337F
person.identifier.orcid0000-0002-3545-6265
person.identifier.ridG-9695-2016
person.identifier.scopus-author-id12794047600
relation.isAuthorOfPublication646900de-975c-4251-8c3f-476dfee276b5
relation.isAuthorOfPublication.latestForDiscovery646900de-975c-4251-8c3f-476dfee276b5

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