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dc.contributor.authorCuadras, C.M. (Carlos Maria)
dc.contributor.authorOller Sala, Josep Maria
dc.contributor.authorArcas i Pons, Antoni
dc.contributor.authorRíos, Martín
dc.identifier.issn0210-8054 (versió paper)
dc.description.abstractSe exponen diversos métodos geométricos, insistiendo en qué propiedades se fundamentan, en orden a probar que diferentes espacios geométricos (euclídeo, no euclídeo, ultramétrico, aditivo, riemanniano) juegan un importante papel en el análisis estadístico de datos.
dc.description.abstractIn this paper we discuss the important role of the geometric approach in statistical data analysis. We show as Borne geometric structures, as euclidean, non-euclidean, ultrametric, additive and riemannian spaces, may be considered as the theoretical foundations of some statistical criteria and proximity data analysis. We specially study the representation of a set with a statistical distance on a geometric model space.
dc.format.extentp. 219-250
dc.publisherUniversitat Politècnica de Barcelona. Centre de Càlcul
dc.relation.ispartofQüestiió. 1985, vol. 9, núm. 4
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.subject.otherMultivariate analysis
dc.subject.otherMultivariate data analysis
dc.subject.otherUltrametric distance
dc.subject.otherAdditive inequality
dc.subject.otherGeodesic distance
dc.subject.otherMultidimensional scaling
dc.titleMétodos geométricos de la estadística
dc.title.alternativeGeometric methods in statistics
dc.subject.lemacAnàlisi multivariable
dc.subject.amsClassificació AMS::62 Statistics::62H Multivariate analysis
dc.rights.accessOpen Access

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