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
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,
Abstract
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
Derechos
openAccess
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Except where otherwise noted, this item's license is described as Attribution 4.0 International