Published 2000

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Publication details

Journal : Journal of Near Infrared Spectroscopy , vol. 8 , p. 117–124 , 2000

International Standard Numbers :
Printed : 0967-0335
Electronic : 1751-6552

Publication type : Academic article

Contributors : Westad, Frank Ove; Martens, Harald

Issue : 2

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Kjetil Aune
Chief Librarian


A jack-knife based method for variable selection in partial least squares regression is presented. The method is based on significance tests of model parameters, in this paper applied to regression coefficients. The method is tested on a near infrared (NIR) spectral data set recorded on beer samples, correlated to extract concentration and compared to other methods with known merit. The results show that the jack-knife based variable selection performs as well or better than other variable selection methods do. Furthermore, results show that the method is robust towards various cross-validation schemes (the number of segments and how they are chosen).