Reference : Robustness properties of the TCLUST procedure

	Document type :	Scientific congresses and symposiums : Unpublished conference
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Mathematics
	To cite this reference:	http://hdl.handle.net/2268/95884

Title :	Robustness properties of the TCLUST procedure
Language :	English
Author, co-author :	Ruwet, Christel [Université de Liège - ULg > Département de mathématique > Statistique mathématique >]
	García-Escudero, Luis Angel [Universidad de Valladolid - UVa > Departamento de Estadística e Investigación Operation > > >]
	Gordaliza, Alfonso [Universidad de Valladolid - UVa > Departamento de Estadística e Investigación Operation > > >]
	Mayo-Iscar, Agustin [Universidad de Valladolid - UVa > > > >]
Publication date :	27-Jul-2011
Audience :	International
Event name :	International conference on robust statistics 2011
Event date :	du 27 juin 2011 au 1 juillet 2011
Event organizer :	Universidad de Valladolid
Event place (city) :	Valladolid
Event country :	Spain
Keywords :	[en] Breakdown point ; Dissolution point ; Heterogeneous clustering ; Influence function ; Isolation Robustness ; Trimming
Abstract :	[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.
Permalink :	http://hdl.handle.net/2268/95884

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