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The utility of multivariate design in PLS modeling
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Research Group for Chemometrics)
2004 (English)In: Journal of Chemometrics, Vol. 18, no 3-4, p. 156-165Article in journal (Refereed) Published
Abstract [en]

We discuss the use of multivariate design to ensure representativity and balance of the training set data for PLS multivariate modeling. Three application areas are used to illustrate the discussion, namely multivariate calibration in process analytical chemistry, quantitative structure activity relationships (QSAR) in medicinal and pharmaceutical chemistry, and data mining. In both QSAR and data mining, the multivariate design is also useful for the balanced sampling of data from a large, complex, and unbalanced data repository.

Place, publisher, year, edition, pages
2004. Vol. 18, no 3-4, p. 156-165
Keyword [en]
PLS, QSAR, NIR, D-opt., Experimental Design
Identifiers
URN: urn:nbn:se:umu:diva-14855DOI: 10.1002/cem.861OAI: oai:DiVA.org:umu-14855DiVA, id: diva2:154527
Available from: 2007-06-19 Created: 2007-06-19 Last updated: 2018-06-09Bibliographically approved

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Wold, SvanteLinusson, Anna

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CiteExportLink to record
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  • apa
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