OnPLS path modelling

Löfstedt, TommyUmeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC) (author)

OnPLS was recently presented as a general extension of O2PLS to the multiblock case. OnPLS is equivalent to O2PLS in the case of two matrices, but generalises symmetrically to cases with more than two matrices, i.e. without giving preference to any one of the matrices.This article presents a straight-forward extension to this method and thereby also introduces the OPLS framework to the field of PLS path modelling. Path modelling links a number of data blocks to each other, thereby establishing a set of paths along which information is considered to flow between blocks, representing for instance a known time sequence, an assumed causality order, or some other chosen organising principle. Compared to existing methods for path analysis, OnPLS path modelling extracts a minimum number of predictive components that are maximally covarying with maximised correlation. This is a significant contribution to path modelling, because other methods may yield score vectors with variation that obstructs the interpretation. The method achieves this by extracting a set of "orthogonal" components that capture local phenomena orthogonal to the variation shared with all the connected blocks.Two applications will be used to illustrate the method. The first is based on a simulated dataset that show how the interpretation is improved by removing orthogonal variation and the second on a real data process for monitoring of protein structure changes during cheese ripening by analysing infrared data.

Hanafi, MohamedUnité de Recherches "Sensometrics and Chemometrics", ONIRIS, Site de la Géraudière, BP 82 225 Nantes 44322 Cedex 03, France (author)
Mazerolles, GérardINRA-UMR 1083 SPO, INRA, 2 Place Viala, 34060 Montpellier, France (author)
Trygg, JohanUmeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC)(Swepub:umu)jotr0001 (author)
Umeå universitetKemiska institutionen (creator_code:org_t)

In:Chemometrics and Intelligent Laboratory Systems: Elsevier118, s. 139-1490169-74391873-3239

By the author/editor: Löfstedt, Tommy; Hanafi, Mohamed; Mazerolles, Géra ...; Trygg, Johan

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