A multiple covariance approach to PLS regression with several predictor groups: Structural Equation Exploratory Regression
Bry, Xavier; Verron, Thomas; Cazes, Pierre (2008), A multiple covariance approach to PLS regression with several predictor groups: Structural Equation Exploratory Regression. https://basepub.dauphine.fr/handle/123456789/3757
TypeDocument de travail / Working paper
External document linkhttp://hal.archives-ouvertes.fr/hal-00239491/en/
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Abstract (EN)A variable group Y is assumed to depend upon R thematic variable groups X 1, ..., X R . We assume that components in Y depend linearly upon components in the Xr's. In this work, we propose a multiple covariance criterion which extends that of PLS regression to this multiple predictor groups situation. On this criterion, we build a PLS-type exploratory method - Structural Equation Exploratory Regression (SEER) - that allows to simultaneously perform dimension reduction in groups and investigate the linear model of the components. SEER uses the multidimensional structure of each group. An application example is given.
Subjects / KeywordsLinear Regression; Latent Variables; PLS Path Modelling; PLS Regression; Structural Equation Models; SEER
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