The HPPLS Procedure

Principal Components Regression

Like the SIMPLS method, principal component regression (PCR) defines all the scores in terms of the original (centered and scaled) predictors bold upper X. However, unlike both the PLS and SIMPLS methods, the PCR method chooses the X-weights and X-scores without regard to the response data. The X-scores are chosen to explain as much variation in bold upper X as possible; equivalently, the X-weights for the PCR method are the eigenvectors of the predictor covariance matrix bold upper X prime bold upper X. Again, the X- and Y-loadings are defined as in PLS; but, as in SIMPLS, it is easy to compute overall model coefficients for the original (centered and scaled) responses bold upper Y in terms of the original predictors bold upper X.

Last updated: December 09, 2022