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Advantages of orthogonal inspection in chemometrics
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Computational Life Science Cluster (CLiC))
Department of Chemistry and Molecular Biology, Gothenburg University.
2012 (English)In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 26, no 6, 231-235 p.Article in journal (Refereed) Published
Abstract [en]

The demand for chemometrics tools and concepts to study complex problems in modern biology and medicine has prompted chemometricians to shift their focus away from a traditional emphasis on model predictive capacity toward optimizing information exchange via model interpretation for biological validation. The interpretation of projection-based latent variable models is not straightforward because of its confounding of different systematic variations in the model components. Over the last 15 years, this has spurred the development of orthogonal-based methods that are capable of separating the correlated variation (to Y) from the noncorrelated (orthogonal to Y) variations in a single model. Here, we aim to provide a conceptual explanation of the advantages of orthogonal variation inspection in the context of Partial Least Squares (PLS) in multivariate classification and calibration. We propose that by inspecting the orthogonal variation, both model interpretation and information quality are improved by enhancement of the resulting level of knowledge. Although the predictive capacity of PLS using orthogonal methods may be identical to that of PLS alone, the combined result can be superior when it comes to the model interpretation. By discussing theory and examples, several new advantages revealed by inspection of orthogonal variation are highlighted.

Place, publisher, year, edition, pages
John Wiley & Sons, 2012. Vol. 26, no 6, 231-235 p.
Keyword [en]
OSC, PLS, OPLS, OPLS-DA, orthogonal variation, predictive variation
National Category
Chemical Sciences
URN: urn:nbn:se:umu:diva-54099DOI: 10.1002/cem.2441ISI: 000305510100005OAI: diva2:515981
Available from: 2012-04-17 Created: 2012-04-17 Last updated: 2012-09-05

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Pinto, Rui ClimacoTrygg, Johan
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