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Advantages of orthogonal inspection in chemometrics

Journal article
Authors R. C. Pinto
J. Trygg
Johan Gottfries
Published in Journal of Chemometrics
Volume 26
Issue 6
Pages 231-235
ISSN 0886-9383
Publication year 2012
Published at Department of Chemistry and Molecular Biology
Pages 231-235
Language en
Links dx.doi.org/10.1002/cem.2441
Keywords OSC, PLS, OPLS, OPLS-DA, orthogonal variation, predictive variation, partial least-squares, near-infrared spectra, simultaneous, spectrophotometric determination, pls plus st, signal correction, multivariate calibration, latent structures, preprocessing methods, discriminant-analysis, spectroscopic data
Subject categories Chemical Sciences

Abstract

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. Copyright (c) 2012 John Wiley & Sons, Ltd.

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