Extensions of Correspondence Analysis for the Statistical Exploration of Multidimensional Contingency Tables
In this paper four different generalizations of canonical correlation analysis to Q ≥ 3 sets of random variables are proposed, their application to indicator variables is studied, and the resulting extensions of correspondence analysis (CA) to Q-dimensional contingency tables are presented. The determination of canonical variates leads to generalized eigenvalue problems which can be solved using a globally convergent algorithm, based on Watson’s iteration.
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