| Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and the flexibility of PLS path modeling (the researcher decides which blocks are connected and which are not). Searching for a fixed point of the stationary equations related to RGCCA, a new monotonically convergent algorithm, very similar to the PLS algorithm proposed by Herman Wold, is obtained. Finally, a practical example is discussed. |
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| The Seminars in Econometrics Series is supported by the Tinbergen Institute, ERIM and the Journal of Applied Econometrics. This extra seminar is also supported by the Erasmus Research Centre on Business Intelligence (ECBI). |
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