Section: New Results

Othogonal Rotation in PCAMIX

Participants : Marie Chavent, Jérôme Saracco.

The aim of this work is to propose an efficient algorithm for rotation in PCAMIX, a principal component method for a mixture of qualitative and quantitative variables. 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”. This work is in revision for publication [45] and has been presented in [36] .