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Improved selectivity in spectroscopy by multivariate calibration
Author(s) -
Martens Harald,
Karstang Terje,
Næs Tormod
Publication year - 1987
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180010403
Subject(s) - calibration , partial least squares regression , outlier , multivariate statistics , chemometrics , multivariate analysis , analytical chemistry (journal) , computer science , biological system , chemistry , pattern recognition (psychology) , statistics , mathematics , artificial intelligence , chromatography , biology
This paper illustrates some advantages of indirect multivariate calibration over conventional calibration: selectivity enhancement and outlier detection. Partial least squares (PLS) calibration is applied for quantitative analysis in the presence of interferences that would make both conventional single‐wavelength calibration and direct multicomponent analysis impossible. The PLS algorithm is illustrated graphically, and the importance of outlier detection is demonstrated.