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The PLS model space revisited
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Research Group for Chemometrics)
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Computational Life Science Cluster (CLiC))
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2008 (English)In: Journal of Chemometrics, Vol. 23, no 2, 67-68 p.Article in journal (Other (popular science, discussion, etc.)) Published
Abstract [en]

Pell, Ramos and Manne (PRM) in a recent article in this journal claim that the conventional PLS algorithm with orthogonal scores has an inherent inconsistency in that it uses different model spaces for calculating the prediction model coefficients and for calculating the X-space model and it's residuals [1]. We disagree with PRM. All PLS model scores, residuals, coefficients, etc., obtained by the conventional PLS algorithm do come from the same underlying latent variable (LV) model, and not from different models or model spaces as PRM suggest. PRM have simply posed a different model with different assumptions and obtained slightly different results, as should have been expected.

Place, publisher, year, edition, pages
John Wiley & Sons, Ltd , 2008. Vol. 23, no 2, 67-68 p.
Keyword [en]
partial least squares, latent variable regression
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:umu:diva-11493DOI: 10.1002/cem.1171OAI: oai:DiVA.org:umu-11493DiVA: diva2:151164
Available from: 2009-01-13 Created: 2009-01-13 Last updated: 2013-02-28

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Wold, SvanteTrygg, Johan

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