Using clustering and robust estimators to detect outliers in multivariate data

dc.contributor.authorPires, Ana
dc.contributor.authorSantos-Pereira, Carla
dc.date.accessioned2018-10-11T16:19:37Z
dc.date.available2018-10-11T16:19:37Z
dc.date.issued2005
dc.description.abstractIntroduction Outlier identi¯cation is important in many applications of multivariate analysis. Either because there is some speci¯c interest in ¯nding anomalous observations or as a pre-processing task before the application of some multivariate method, in order to preserve the results from possible harmful e®ects of those observations. It is also of great interest in discriminant analysis if, when predicting group membership, one wants to have the possibility of labelling an observation as "does not belong to any of the available groups". The identi¯cation of outliers in multivariate data is usually based on Mahalanobis distance. The use of robust estimates of the mean and the covariance matrix is advised in order to avoid the masking e®ect (Rousseeuw and von Zomeren, 1990; Rocke and Woodru®, 1996; Becker and Gather, 1999). However, the performance of these rules is still highly dependent of multivariate normality of the bulk of the data. The aim of the method here described is to remove this dependency. The ¯rst version of this method appeared in Santos-Pereira and Pires (2002). In this talk we discuss some re¯nements and also the relation with a recently proposed similar method (Hardin and Rocke, 2004).pt_PT
dc.identifier.citationPires, A. and Santos-Pereira, C. (2005). Using clustering and robust estimators to detect outliers in multivariate data. Proceedings of the international conference on robust statistics ICORS 2005. Disponível no Repositório UPT, http://hdl.handle.net/11328/2345pt_PT
dc.identifier.urihttp://hdl.handle.net/11328/2345
dc.language.isoengpt_PT
dc.rightsopen accesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectOutlierspt_PT
dc.subjectClusteringpt_PT
dc.subjectDiscriminant analysispt_PT
dc.titleUsing clustering and robust estimators to detect outliers in multivariate datapt_PT
dc.typeconferenceObjectpt_PT
degois.publication.titleinternational conference on robust statistics ICORS 2005pt_PT
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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