Métodos geométricos de la estadística

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hdl:2099/3924
Document typeArticle
Defense date1985-12
PublisherUniversitat Politècnica de Barcelona. Centre de Càlcul
Rights accessOpen Access
This work is protected by the corresponding intellectual and industrial property rights.
Except where otherwise noted, its contents are licensed under a Creative Commons license
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Attribution-NonCommercial-NoDerivs 2.5 Spain
Abstract
Se 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. In 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.
ISSN0210-8054 (versió paper)
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