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A control chart approach to select eigenvalues in principal component and correspondence analysis

Gilbert Saporta 1
1 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
CEDRIC - Centre d'études et de recherche en informatique et communications
Abstract : A vast literature (Cattell, Horn, Velicer) has been devoted to the assessment of the proper number of eigenvalues that have to be retained in Principal Components Analysis. Most of the publications are based on either (non-realistic) distributional assumptions for the underlying populations or on empirical criteria. Techniques that are based on bootstrap or cross-validation have been proposed (Diana, Krzanowski ,Wold) but requires a lot of computation. For Multiple Correspondence Analysis, the problem is similar, but there are few publications. In this paper a simple technique based on a control chart approach is proposed for selecting the number of principal components to retain for the analysis.
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Gilbert Saporta. A control chart approach to select eigenvalues in principal component and correspondence analysis. 54th Session of the International Statistical Institute, International Statistical Institute, Aug 2003, Berlin, Germany. ⟨hal-01124809⟩

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