Some simple rules for interpreting outputs of principal components and correspondence analysis
Résumé
A large literature has been devoted to the assessment of the right number of eigenvalues in PCA and CA (two-way and multiple). Most of the publications are based on distributional assuptions for the sample, or on bootstrap techniques. After having recalled some of the most important results, we present simple thresholds based on a « control chart » approach for eigenvalues as well as for contributions, distances
Domaines
Statistiques [math.ST]Origine | Fichiers produits par l'(les) auteur(s) |
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