Abstract
The proposed model allows analyses which are more powerful than Factorial Discriminant or Correspondence Analyses; it may be considered as a useful complement to Multivariate Analysis of Variance. Comparing to MANOVA, statistics are not carried out from variables, but from statistical units. The statistical unit space, linked to the variable space by an isometry, contains two orthogonal subspaces associated to mean and residual values as well.
Finally, inertia of configurations of points in the unit space, used in particular to determine factorial axes, can measure either symmetrical or dissymmetrical association coefficients from explanatory variables to independent variables.
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Schektman, Y., Abdesselam, R. (2000). A Geometrical Relational Model for Data Analysis. In: Gaul, W., Opitz, O., Schader, M. (eds) Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58250-9_29
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DOI: https://doi.org/10.1007/978-3-642-58250-9_29
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