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