CHAVENT, Marie; VANESSA, K.; SARACCO, Jérôme

doi:10.1007/s11634-012-0105-3

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CHAVENT, Marie
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]

VANESSA, K.
Aménités et dynamiques des espaces ruraux [UR ADBX]

SARACCO, Jérôme
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]

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Advances in Data Analysis and Classification. 2012, vol. 6, p. 131-146

Springer Verlag

Résumé en anglais

Kiers (1991) considered the orthogonal rotation in PCAMIX, a principal component method for a mixture of qualitative and quantitative variables. PCAMIX includes the ordinary principal component analysis (PCA) and multiple correspondence analysis (MCA) as special cases. In this paper, we give a new presentation of PCAMIX where the principal components and the squared loadings are obtained from a Singular Value Decomposition. The loadings of the quantitative variables and the principal coordinates of the categories of the qualitative variables are also obtained directly. In this context, we propose a computationaly efficient procedure for varimax rotation in PCAMIX and a direct solution for the optimal angle of rotation. A simulation study shows the good computational behavior of the proposed algorithm. An application on a real data set illustrates the interest of using rotation in MCA. All source codes are available in the R package "PCAmixdata".< Réduire

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MIXTURE OF QUALITATIVE AND QUANTITATIVE DATA MULTIPLE CORRESPONDENCE ANALYSIS

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Orthogonal rotation in PCAMIX

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