Optimised score plot by principal components of predictions
Publikasjonsdetaljer
Tidsskrift : Chemometrics and Intelligent Laboratory Systems , vol. 68 , p. 61–74 , 2003
Utgiver : Elsevier
Internasjonale standardnummer
:
Trykt
:
0169-7439
Elektronisk
:
1873-3239
Publikasjonstype : Vitenskapelig artikkel
Sak : 1-2
Lenker
:
DOI
:
doi.org/10.1016/S0169-7439(03)...
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Kjetil Aune
Bibliotekleder
kjetil.aune@nofima.no
Sammendrag
A common problem in statistics/chemometrics is to relate two data matrices (X and Y) to each other, with the purpose of either prediction or interpretation. Usually, one is interested in understanding which directions in Y-space that can be predicted by which directions in X-space. Several methods exist for this, for instance, PLS regression and canonical correlation. The present paper presents a new plot for visualising the relationship between X and Y. The plot is based on a decomposition of the X-space that is optimal with respect to Y-variance. The new procedure can accompany any regression method. (C) 2003 Elsevier Science B.V. All rights reserved.