A multiple covariance approach to PLS regression with several predictor groups: Structural Equation Exploratory Regression

Bry, Xavier; Verron, Thomas; Cazes, Pierre

A multiple covariance approach to PLS regression with several predictor groups: Structural Equation Exploratory Regression

Authors

Bry, Xavier

Verron, Thomas

Cazes, Pierre

Description

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.