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Publisert 2002

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Publikasjonsdetaljer

Tidsskrift : Journal of Chemometrics , vol. 16 , p. 313–318 , 2002

Internasjonale standardnummer :
Trykt : 0886-9383
Elektronisk : 1099-128X

Publikasjonstype : Vitenskapelig artikkel

Bidragsytere : Høy, Martin; Westad, Frank Ove; Martens, Harald

Har du spørsmål om noe vedrørende publikasjonen, kan du kontakte Nofimas bibliotekleder.

Kjetil Aune
Bibliotekleder
kjetil.aune@nofima.no

Sammendrag

A method is presented for making principal component regression (PCR), partial least squares regression (PLSR) and other regressions based on bilinear modelling (BLM) less sensitive to overfit. The idea is to use generalized ridge regression to calculate the Y-loadings in order to prevent small, uncertain values of the score vectors from causing inflation of variance in the regression coefficients. Thus we combine the stabilizing power of ridge regression with the modelling power and interpretability of bilinear models. The method is intended to provide better predictive ability and improved stability for regression models. Copyright (C) 2002 John Wiley Sons, Ltd.