A general trimming approach to robust cluster analysis

• Autores: Luis Angel García Escudero , Alfonso Gordaliza Ramos , Carlos Matrán Bea , Agustín Mayo Iscar
• Localización: XXX Congreso Nacional de Estadística e Investigación Operativa y de las IV Jornadas de Estadística Pública: actas, 2007, ISBN 978-84-690-7249-3
• Idioma: inglés
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• Resumen

  • We introduce a new method for performing clustering with the aim of ¯tting clusters with di®erent scatters and weights. It is designed by allowing to handle a proportion ® of contaminating data to guarantee the robustness of the method.

    As a characteristic feature, restrictions on the ratio between the maximum and the minimum eigenvalues of the groups scatter matrices are introduced. This makes the problem to be well-de¯ned and guarantees the consistency of the sample solutions to the population ones.

    The method covers a wide range of clustering approaches depending on the strength of the chosen restrictions. The proposal includes an algorithm (the TCLUST method) for approximately solving the sample problem.