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O2-PLS for qualitative and quantitative analysis in multivariate calibration
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Computational Life Science Cluster (CLiC))
2002 (English)In: Journal of Chemometrics: 6 , Pages, Vol. 16, no 6, 283-93 p.Article in journal (Refereed) Published
Abstract [en]

In this paper the O-PLS method [1] has been modified to further improve its interpretational functionality to give (a) estimates of the pure constituent profiles in X as well as model (b) the Y-orthogonal variation in X, (c) the X-orthogonal variation in Y and (d) the joint X-Y covariation. It is also predictive in both ways, X Y. We call this the O2-PLS approach. In earlier papers we discussed the improved interpretation using O-PLS compared to the partial least squares projections to latent structures (PLS) when systematic Y-orthogonal variation in X exists, i.e. when a PLS model has more components than the number of Y variables. In this paper we show how the parameters in the PLS model are affected and to what degree the interpretational ability of the PLS components changes with the amount of Y-orthogonal variation. In both real and synthetic examples, the O2-PLS method provided improved interpretation of the model and gave a good estimate of the pure constituent profiles, and the prediction ability was similar to the standard PLS model. The method is discussed from geometric and algebraic points of view, and a detailed description of this modified O2-PLS method is given and reviewed.

Place, publisher, year, edition, pages
2002. Vol. 16, no 6, 283-93 p.
Keyword [en]
O-PLS, O2-PLS, PLS, multivariate calibration, preprocessing, pure profile estimation
National Category
Computer and Information Science Biological Sciences
Identifiers
URN: urn:nbn:se:umu:diva-9117DOI: doi:10.1002/cem.724OAI: oai:DiVA.org:umu-9117DiVA: diva2:148788
Available from: 2008-03-03 Created: 2008-03-03 Last updated: 2012-09-05

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Trygg, Johan

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