Reference : Robustness properties of the TCLUST procedure
Scientific congresses and symposiums : Unpublished conference/Abstract
Physical, chemical, mathematical & earth Sciences : Mathematics
Robustness properties of the TCLUST procedure
Ruwet, Christel mailto [Université de Liège - ULiège > Département de mathématique > Statistique mathématique >]
García-Escudero, Luis Angel mailto [Universidad de Valladolid - UVa > Departamento de Estadística e Investigación Operation > > >]
Gordaliza, Alfonso mailto [Universidad de Valladolid - UVa > Departamento de Estadística e Investigación Operation > > >]
Mayo-Iscar, Agustin mailto [Universidad de Valladolid - UVa > > > >]
International conference on robust statistics 2011
du 27 juin 2011 au 1 juillet 2011
Universidad de Valladolid
[en] Breakdown point ; Dissolution point ; Heterogeneous clustering ; Influence function ; Isolation Robustness ; Trimming
[en] The TCLUST procedure is a robust clustering procedure introduced by García-Escudero et al. (2008). It performs clustering with the aim of fitting clusters with different scatters and weights. As the corresponding objective function can be unbounded, a restriction is added on the eigenvalues-ratio of the scatter matrices. The robustness of the method is guaranteed by allowing the trimming of a given proportion of observations. As García-Escudero and Gordaliza (1999) have done for the k-means and trimmed k-means methodologies, the robustness properties of the TCLUST procedure are studied by means of the influence function and the breakdown point. In order to be able to compare the robustness of TCLUST with other clustering methods, dissolution point and isolation robustness (Hennig, 2008) are also considered. It turns out that the TCLUST procedure has a behavior close to that of the trimmed k-means.

File(s) associated to this reference

Additional material(s):

File Commentary Size Access
Restricted access
Icors2011.pdf1.72 MBRequest copy

Bookmark and Share SFX Query

All documents in ORBi are protected by a user license.