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| Reference : The influence function of the TCLUST robust clustering procedure |
| Scientific journals : Article | |||
| Physical, chemical, mathematical & earth Sciences : Mathematics | |||
| http://hdl.handle.net/2268/92958 | |||
| The influence function of the TCLUST robust clustering procedure | |
| English | |
Ruwet, Christel  [Université de Liège - ULg > Département de mathématique > Statistique mathématique >] | |
| García-Escudero, Luis Angel [Universidad deValladolid - UVa > > > >] | |
| Gordaliza, Alfonso [Universidad deValladolid - UVa > > > >] | |
| Mayo-Iscar, Agustin [Universidad deValladolid - UVa > > > >] | |
| 2012 | |
| Advances in Data Analysis and Classification [=ADAC] | |
| 6 | |
| 2 | |
| 107-130 | |
| Yes (verified by ORBi) | |
| International | |
| 1862-5347 | |
| 1862-5355 | |
| [en] Heterogeneous Clustering ; Influence function ; Robustness ; Trimmin | |
| [en] The TCLUST procedure performs robust
clustering with the aim of finding clusters with different scatter structures and proportions. An Eigenvalue Ratio constraint is considered by TCLUST in order to avoid finding spurious clusters. In order to guarantee the robustness of the method against the presence of outliers and background noise, the method allows for trimming of a given proportion of observations self determined by the data. This article studies robustness properties of the TCLUST procedure by means of the influence function, obtaining a robustness behavior close to that of the trimmed k-means. | |
| Spanish Ministerio de Ciencia e Innovación ; Communauté française de Belgique - CfB | |
| http://hdl.handle.net/2268/92958 | |
| 10.1007/s11634-012-0107-1 | |
| The original publication is available at www.springerlink.com |
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