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Communications in statistics. Theory and methods 39, 3 (2010) 483-492
DMFA: dual multiple factor analysis
Sébastien Lê 1, 2, Jérome Pagès 1, 2
(2010)

In this article, we propose a new method called Dual Multiple Factor Analysis (DMFA), which is an extension of DMFA in the case where individuals are structured according to a partition. The heart of the method rests on a factor analysis known as internal, in reference to the internal correspondence analysis, for which data are systematically centered by group. This analysis is an internal PCA when all the variables are quantitative. DMFA provides the classic results of a PCA as well as additional outputs induced by the consideration of a partition on individuals, such as the superimposed representation of the L scatter plots of variables associated with the L groups of individuals and the representation of the scatter plot of the correlations matrices associated each one with a group of individuals.
1:  Institut de Recherche Mathématique de Rennes (IRMAR)
CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne
2:  Agrocampus Ouest
Institut supérieur des sciences agronomiques, agroalimentaires, horticoles et du paysage – Ministère de l'agriculture, de l'agroalimentaire et de la forêt
Statistique
Mathematics/Statistics

Statistics/Statistics Theory
Common structures – Dual multiple factor analysis – geometrical interpretation – groups of individuals