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Partial Least-Squares Quantitative Analysis of Infrared Spectroscopic Data. Part I: Algorithm Implementation

Volume 42, Number 2 (Feb. 1988) Page 217-227

Fuller, M.P.; Ritter, G.L.; Draper, C.S.

Various approaches to infrared multicomponent quantitative analysis including K-matrix, multivariate least-squares, principal component regression (PCR), and partial least-squares (PLS) are compared. The advantages and disadvantages of each are discussed. A particular implementation of the PLS method is detailed, with emphasis on the methods provided for calibration optimization and evaluation.