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ERIC Number: EJ921257
Record Type: Journal
Publication Date: 2011-Apr
Pages: 28
Abstractor: As Provided
Reference Count: 42
ISBN: N/A
ISSN: ISSN-0033-3123
Regularized Generalized Canonical Correlation Analysis
Tenenhaus, Arthur; Tenenhaus, Michel
Psychometrika, v76 n2 p257-284 Apr 2011
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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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A