Keywords
non redondancy
simultaneity
biplots
ordinary least squares
correlation
simple linear regression dependencia entre conjuntos de variables
no redundancia
simultaneidad
biplots
mínimos cuadrados ordinarios
correlación
regresión lineal simple
How to Cite
Abstract
Some recent developments in factor analysis of multi-sets are introduced in this short course. The more usual factor analyses are based on the singular values de-composition. So, the analyses of two matrices here are introduced from a qualitative criterion, for a non redundancy of partial relations between "common factors". A proposal for extending the simple linear regression, here considered between the two sets of the individuals which define the two sets of variables, lead to specific measures for each matrix. Some juxtapositions of graphics then are justified. The whole previous approach is extended for analyzing the dependency of K matrices with one matrix. The ACOM of Chessel and Hanafi (1996) then is considered as a PCA of sets of variables.
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