Use of eigenvalues for determining the number of components in window factor analysis of spectroscopic and chromatographic data

Three methods for determining eigenvalues, namely (1) mean-centred sequential scores, (2) mean-centred sequential loadings and (3) uncentred data, are described, and compared on simulations and real data of two-way data matrices. The sequential direction may be time (high-performance liquid chromato...

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Bibliographic Details
Published in:Chemometrics and intelligent laboratory systems 1995, Vol.27 (1), p.73-87
Main Authors: Brereton, Richard G., Gurden, Stephen P., Groves, John A.
Format: Article
Language:English
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Summary:Three methods for determining eigenvalues, namely (1) mean-centred sequential scores, (2) mean-centred sequential loadings and (3) uncentred data, are described, and compared on simulations and real data of two-way data matrices. The sequential direction may be time (high-performance liquid chromatography (HPLC)) or wavelength (infrared spectroscopy (IR)), with the non-sequential direction wavelength (HPLC) or sample number (IR). It is shown that method 1 is very dependent on peak shapes. Method 2 works well except when there is low variability in the non-sequential direction. Method 3 performs poorly in the presence of heteroscedastic noise. It is concluded that standard statistical approaches for eigenanalysis must be used with caution in chemometric methods for window factor analysis (WFA).
ISSN:0169-7439
1873-3239
DOI:10.1016/0169-7439(95)80008-W