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Multiblock and Path Modeling with OnPLS
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Computational Life Science Cluster (CLiC))
Umeå University, Faculty of Science and Technology, Department of Chemistry. (Computational Life Science Cluster (CLiC))
2013 (English)In: New Perspectives in Partial Least Squares and Related Methods (Part IV) / [ed] Herve Abdi, Wynne W. Chin, Vincenzo Esposito Vinzi, Giorgio Russolillo, Laura Trinchera, Springer Science+Business Media B.V., 2013, 56, , 209-220 p.209-220 p.Conference paper, Published paper (Refereed)
Abstract [en]

OnPLS was recently proposed as a general extension of O2PLS for applications in multiblock and path model analysis. OnPLS is very similar to O2PLS in the case with two matrices, but generalizes symmetrically to cases with more than two matrices without giving preference to any matrix.

OnPLS extracts a minimal number of globally joint components that exhibit maximal covariance and correlation. A number of locally joint components are also extracted. These are shared between some matrices, but not between all. These components are also maximally covarying with maximal correlation. The variation that remains after the joint and locally joint variation has been extracted is unique to a particular matrix. This unique variation is orthogonal to all other matrices and captures phenomena specific in its matrix.

The method's utility has been demonstrated by its application to synthetic datasets with very good results in terms of its ability to decompose the matrices. It has been shown that OnPLS affords a reduced number of globally joint components and increased intercorrelations of scores, and that it greatly facilitates interpretation of the models. Preliminary results in the application on real data has also given positive results. The results are similar to previous results using other multiblock and path model methods, but afford an increased interpretability because of the locally joint and unique components.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2013, 56. , 209-220 p.209-220 p.
Series
Springer Proceedings in Mathematics & Statistics, ISSN 2194-1009 ; 56
Keyword [en]
OnPLS, Principal component analysis, Multi-block analysis
National Category
Chemical Sciences Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-85510DOI: 10.1007/978-1-4614-8283-3_14ISI: 000337590300014ISBN: 978-1-4614-8282-6 (print)ISBN: 978-1-4614-8283-3 (print)OAI: oai:DiVA.org:umu-85510DiVA: diva2:694098
Conference
7th Meeting of the Partial Least Squares (PLS). Univ Texas, Houston, TX, MAY 19-22, 2012
Available from: 2014-02-05 Created: 2014-02-05 Last updated: 2017-01-16Bibliographically approved

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Trygg, Johan

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