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Eigenvectors of a kurtosis matrix as interesting directions to reveal cluster structure

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorPeña, Daniel
dc.contributor.authorPrieto Fernández, Francisco Javier
dc.contributor.authorViladomat Comerma, Julia
dc.date.accessioned2012-07-11T11:28:25Z
dc.date.available2012-07-11T11:28:25Z
dc.date.issued2010-10
dc.description.abstractIn this paper we study the properties of a kurtosis matrix and propose its eigenvectors as interesting directions to reveal the possible cluster structure of a data set. Under a mixture of elliptical distributions with proportional scatter matrix, it is shown that a subset of the eigenvectors of the fourth-order moment matrix corresponds to Fisher's linear discriminant subspace. The eigenvectors of the estimated kurtosis matrix are consistent estimators of this subspace and its calculation is easy to implement and computationally efficient, which is particularly favourable when the ratio n/p is large.
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationJournal of Multivariate Analysis, 2010, v. 101, n. 9 (oct. 2010), p. 1995-2007
dc.identifier.doi10.1016/j.jmva.2010.04.014
dc.identifier.issn0047-259X
dc.identifier.publicationfirstpage1995
dc.identifier.publicationissue9
dc.identifier.publicationlastpage2007
dc.identifier.publicationtitleJournal of Multivariate Analysis
dc.identifier.publicationvolume101
dc.identifier.urihttps://hdl.handle.net/10016/14888
dc.language.isoeng
dc.publisherElsevier
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.jmva.2010.04.014
dc.rights©2010 Elsevier Inc.
dc.rights.accessRightsopen access
dc.subject.ecienciaEstadística
dc.subject.otherCluster analysis
dc.subject.otherDimension reduction
dc.subject.otherFisher subspace
dc.subject.otherKurtosis matrix
dc.subject.otherMultivariate kurtosis
dc.subject.otherProjection pursuit
dc.titleEigenvectors of a kurtosis matrix as interesting directions to reveal cluster structure
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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