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

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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.

Keywords: Detergent analysis; Infrared spectroscopy; Partial least-squares analysis; Quantitative analysis; Statistical analysis

Document Type: Research Article


Affiliations: Application Specific Products Group, Nicolet Instrument Corporation, 5225 Verona Road, P.O. Box 4508, Madison, Wisconsin 53711-0508

Publication date: February 1, 1988

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