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Research Article
On robust partial least squares (PLS) methods
Article first published online: 26 FEB 1999
DOI: 10.1002/(SICI)1099-128X(199811/12)12:6<365::AID-CEM519>3.0.CO;2-G
Copyright © 1998 John Wiley & Sons, Ltd.
1099-128X/asset/cover.gif?v=1&s=2e3045c3733baa4258989f44bd61b29dd74ee736 "Journal of Chemometrics")
Additional Information
How to Cite
Gil, J. A. and Romera, R. (1998), On robust partial least squares (PLS) methods. Journal of Chemometrics, 12: 365–378. doi: 10.1002/(SICI)1099-128X(199811/12)12:6<365::AID-CEM519>3.0.CO;2-G
Publication History
- Issue published online: 26 FEB 1999
- Article first published online: 26 FEB 1999
- Manuscript Accepted: 10 AUG 1998
- Manuscript Received: 10 OCT 1997
Funded by
- DGICYT, Spain. Grant Number: PB93-0232
- Abstract
- Cited By
Keywords:
- partial least squares;
- robust regression methods;
- robust covariance matrices;
- Stahel–Donoho estimator
Abstract
PLS regression methods have been used in applied fields for two decades. Techniques based on iteratively reweighted regression have appeared in the specialized literature with the contaminated data case. We propose a new robust PLS technique based on statistical procedures for covariance matrix robustification. We select the well-known Stahel–Donoho estimator (SDE). We include computational results comparing performance in terms of the standard PLS PRESS reduction if the robust PLS techniques are used. We use simulated and real data and include computational results showing the better robustness and efficiency for the new robust PLS method.Copyright © 1998 John Wiley & Sons, Ltd.