Abstract
Carroll's method for generalized canonical analysis of two or more sets of variables is shown to optimize the sum of squared inner-product matrix correlations between a consensus matrix and matrices with canonical variates for each set of variables. In addition, the method that analogously optimizes the sum of squared RV matrix correlations (proposed by Escoufier, 1973) between a consensus matrix and matrices with canonical variates, can be interpreted as an application of Carroll and Chang's IDIOSCAL. A simple algorithm is developed for this and other applications of IDIOSCAL where the similarity matrices are positive semi-definite.
Published Version
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