Partial least squares regression with Curds and Whey

In order to make use of information between correlated responses in calibration, a new PLS method called PLS with Curds and Whey (PLS-C&W) is introduced. It combines PLS regression with a canonical analysis between the PLS estimates and the responses. The estimates are suitably shrunk in the canonical co-ordinate system using generalized cross-validation (GCV). The results obtained from five data sets show that PLS-C&W methods yield calibration models of high prediction ability.