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Por favor, use este identificador para citar o enlazar este ítem: http://uvadoc.uva.es/handle/10324/21848
Título: Grouping Around Different Dimensional Affine Subspaces
Autor: García Escudero, Luis Ángel
Gordaliza, Alfonso
Matrán Bea, Carlos
Mayo Iscar, Agustín
Año del Documento: 2013
Documento Fuente: Statistical Models for Data Analysis 2013. Studies in Classification, Data Analysis, and Knowledge Organization 201, Edited by Paolo Giudici, Salvatore Ingrassia, Maurizio Vichi,
Resumen: Grouping around affine subspaces and other types of manifolds is receiving a lot of attention in the literature due to its interest in several fields of application. Allowing for different dimensions is needed in many applications. This work extends the TCLUST methodology to deal with the problem of grouping data around different dimensional linear subspaces in the presence of noise. Two ways of considering error terms in the orthogonal of the linear subspaces are considered.
Materias (normalizadas): Estadística
Idioma: spa
URI: http://uvadoc.uva.es/handle/10324/21848
Derechos: info:eu-repo/semantics/openAccess
Aparece en las colecciones:DEP24 - Capítulos de monografías

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