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Variable selection in model-based clustering using multilocus genotype data

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  • Wilson Toussile
  • Elisabeth Gassiat

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  • Wilson Toussile & Elisabeth Gassiat, 2009. "Variable selection in model-based clustering using multilocus genotype data," 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. 3(2), pages 109-134, September.
    • Handle: RePEc:spr:advdac:v:3:y:2009:i:2:p:109-134
    DOI: 10.1007/s11634-009-0043-x
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    References listed on IDEAS

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    1. Cathy Maugis & Gilles Celeux & Marie-Laure Martin-Magniette, 2009. "Variable Selection for Clustering with Gaussian Mixture Models," Biometrics, The International Biometric Society, vol. 65(3), pages 701-709, September.
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    Cited by:

    1. Anzanello, Michel J. & Fogliatto, Flavio S., 2011. "Selecting the best clustering variables for grouping mass-customized products involving workers' learning," International Journal of Production Economics, Elsevier, vol. 130(2), pages 268-276, April.

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    More about this item

    Keywords

    Model-based clustering; Penalized maximum likelihood criteria; Population genetics; Variable selection; C89; 62H30;
    All these keywords.

    JEL classification:

    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

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