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The L-Curve Criterion as a Model Selection Tool in PLS Regression
Joint Authors
Allal, Jelloul
Kerkri, Abdelmounaim
Zarrouk, Zoubir
Source
Journal of Probability and Statistics
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-10-30
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Partial least squares (PLS) regression is an alternative to the ordinary least squares (OLS) regression, used in the presence of multicollinearity.
As with any other modelling method, PLS regression requires a reliable model selection tool.
Cross validation (CV) is the most commonly used tool with many advantages in both preciseness and accuracy, but it also has some drawbacks; therefore, we will use L-curve criterion as an alternative, given that it takes into consideration the shrinking nature of PLS.
A theoretical justification for the use of L-curve criterion is presented as well as an application on both simulated and real data.
The application shows how this criterion generally outperforms cross validation and generalized cross validation (GCV) in mean squared prediction error and computational efficiency.
American Psychological Association (APA)
Kerkri, Abdelmounaim& Allal, Jelloul& Zarrouk, Zoubir. 2019. The L-Curve Criterion as a Model Selection Tool in PLS Regression. Journal of Probability and Statistics،Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1186845
Modern Language Association (MLA)
Kerkri, Abdelmounaim…[et al.]. The L-Curve Criterion as a Model Selection Tool in PLS Regression. Journal of Probability and Statistics No. 2019 (2019), pp.1-7.
https://search.emarefa.net/detail/BIM-1186845
American Medical Association (AMA)
Kerkri, Abdelmounaim& Allal, Jelloul& Zarrouk, Zoubir. The L-Curve Criterion as a Model Selection Tool in PLS Regression. Journal of Probability and Statistics. 2019. Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1186845
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186845