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Estimation of partial least squares regression prediction uncertainty when the reference values carry a sizeable measurement error


  • Fernández Pierna, J.A. , Jin, L. , Wahl, F. , Faber, M. & Massart, D. (2003). Estimation of partial least squares regression prediction uncertainty when the reference values carry a sizeable measurement error. Chemom. Intell. Lab. Syst. 65: 281-291.
Type Journal Article
Year 2003
Title Estimation of partial least squares regression prediction uncertainty when the reference values carry a sizeable measurement error
Journal Chemom. Intell. Lab. Syst.
Label U15-0516
Recnumber 345
Volume 65
Pages 281-291
Date November 2003
Type of article scientifique, recherche
Endnote Keywords Multivariate calibration|Partial least squares regression|Uncertainty estimation|Standard error of prediction|Monte Carlo simulation|Bootstrap|Noise addition|Near infrared spectroscopy|
Abstract The prediction uncertainty is studied when using a multivariate partial least squares regression (PLSR) model constructed with reference values that contain a sizeable measurement error. Several approximate expressions for calculating a sample-specific standard error of prediction have been proposed in the leterature. In addition, Monte Carlo simulation methods such as the bootstrap and the noise addition can give an estimate of this uncertainty. In this paper, two approximate expressions are compared with the simulation methods for three near-infrared date sets.
Author address Fernandez Pierna Juan Antonio, Quality Department of Agro-food Products, Walloon Agricultural Research Centre (CRA-W), Chaussée de Namur, 24, B-5030 Gembloux, fernandez@cra.wallonie.be
Fichier Estimation of partial least squares regression prediction uncertainty when the reference values carry a sizeable measurement error
Caption U15-0516-fernandez-2003.pdf
Authors Fernández Pierna, J.A. , Jin, L. , Wahl, F. , Faber, M. & Massart, D.