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Zbl 1233.62208
Li, Gang; Qin, S.Joe; Zhou, Donghua
Geometric properties of partial least squares for process monitoring. (English)
[J] Automatica 46, No. 1, 204-210 (2010). ISSN 0005-1098

Summary: Projection to latent structures or partial least squares (PLS) produces output-supervised decomposition on input X, while principal component analysis (PCA) produces unsupervised decomposition of input X. The effect of output Y on the X-space decomposition in PLS is analyzed and geometric properties of the PLS structure are revealed. Several PLS algorithms are compared in a geometric way for the purpose of process monitoring. A numerical example and a case study are given to illustrate the analysis results.

MSC 2000:: *62P30 Applications in engineering and industry
62H25 Factor analysis, etc.
65C60 Computational problems in statistics

Keywords: PLS; weight-deflated PLS (W-PLS); simplified PLS (SIMPLS)

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Zentralblatt MATH Berlin [Germany]