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The importance of the scales in heterogeneous robust clustering

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  • Garcia-Escudero, L.A.
  • Gordaliza, A.

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  • Garcia-Escudero, L.A. & Gordaliza, A., 2007. "The importance of the scales in heterogeneous robust clustering," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4403-4412, May.
    • Handle: RePEc:eee:csdana:v:51:y:2007:i:9:p:4403-4412
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    References listed on IDEAS

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    1. Hennig, Christian & Christlieb, Norbert, 2002. "Validating visual clusters in large datasets: fixed point clusters of spectral features," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 723-739, October.
    2. Hawkins D. M. & Olive D. J., 2002. "Inconsistency of Resampling Algorithms for High-Breakdown Regression Estimators and a New Algorithm," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 136-159, March.
    3. Croux, Christophe & Haesbroeck, Gentiane, 1999. "Influence Function and Efficiency of the Minimum Covariance Determinant Scatter Matrix Estimator," Journal of Multivariate Analysis, Elsevier, vol. 71(2), pages 161-190, November.
    4. Woodruff, David L. & Reiners, Torsten, 2004. "Experiments with, and on, algorithms for maximum likelihood clustering," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 237-253, September.
    5. Hardin, Johanna & Rocke, David M., 2004. "Outlier detection in the multiple cluster setting using the minimum covariance determinant estimator," Computational Statistics & Data Analysis, Elsevier, vol. 44(4), pages 625-638, January.
    6. Hawkins, Douglas M. & Olive, David J., 1999. "Improved feasible solution algorithms for high breakdown estimation," Computational Statistics & Data Analysis, Elsevier, vol. 30(1), pages 1-11, March.
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    Cited by:

    1. L. A. García-Escudero & A. Gordaliza & C. Matrán & A. Mayo-Iscar, 2018. "Comments on “The power of monitoring: how to make the most of a contaminated multivariate sample”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(4), pages 605-608, December.
    2. Luis García-Escudero & Alfonso Gordaliza & Carlos Matrán & Agustín Mayo-Iscar, 2010. "A review of robust clustering methods," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 4(2), pages 89-109, September.
    3. Schyns, M. & Haesbroeck, G. & Critchley, F., 2010. "RelaxMCD: Smooth optimisation for the Minimum Covariance Determinant estimator," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 843-857, April.
    4. C. Ruwet & L. García-Escudero & A. Gordaliza & A. Mayo-Iscar, 2012. "The influence function of the TCLUST robust clustering procedure," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(2), pages 107-130, July.

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