QR-PLSR: REDUCED-RANK REGRESSION FOR HIGH-SPEED HARDWARE IMPLEMENTATION

摘要

A version of PLS regression is described that intends to combine the computer hardware implementation advantages of the algebraic technique of 'QR decomposition' with the statistical, interpretative and computational advantages of PLS regression. With a QR decomposition based on Givens rotations, the QR-PLS technique appears to be suited for hardware parallelization without sacrificing the modelling flexibility of PLSR.