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Methods for outlier detection in prediction


  • Fernández Pierna, J.A. , Wahl, F. , De Noord, O. & Massart, D. (2002). Methods for outlier detection in prediction. Chemom. Intell. Lab. Syst. 63: (1), 27-39.
Type Journal Article
Year 2002
Title Methods for outlier detection in prediction
Journal Chemom. Intell. Lab. Syst.
Label U15-0526
Recnumber 357
Volume 63
Issue 1
Pages 27-39
Date 28/08/2002
Endnote Keywords multivariate calibration, chemometrics, prediction outliers|least-squares regression|multivariate calibration|error|unscrambler|critique|
Abstract If a prediction sample is different from the calibration samples, it can be considered as an outlier in prediction. In this work, two techniques, the use of the uncertainty estimation and convex hull method are studied to detect such prediction outliers. Classical techniques (Mahalanobis distance and X-residuals), potential functions and robust techniques are used for comparison. It is concluded that the combination of the convex hull and the uncertainty estimation offers a practical way for detecting outliers in prediction. By adding the potential function method, inliers can also be detected. (C) 2002 Elsevier Science B.V All rights reserved.
Notes EnglishArticleCHEMOMETR INTELL LAB SYST581UC
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
File Methods for outlier detection in prediction
Caption U15-0526-fernandez-2002.pdf
Authors Fernández Pierna, J.A. , Wahl, F. , De Noord, O. & Massart, D.