Cross fitted partial least squares (CF-PLS): an alternative algorithm for a more reliable PLS
Article first published online: 10 FEB 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Journal of Chemometrics
Volume 25, Issue 4, pages 208–215, April 2011
How to Cite
Cloarec, O. (2011), Cross fitted partial least squares (CF-PLS): an alternative algorithm for a more reliable PLS. J. Chemometrics, 25: 208–215. doi: 10.1002/cem.1380
- Issue published online: 14 APR 2011
- Article first published online: 10 FEB 2011
- Manuscript Accepted: 6 JAN 2011
- Manuscript Revised: 3 JAN 2011
- Manuscript Received: 25 AUG 2010
- partial least squares (PLS);
- simulation, validation
This paper presents a modified version of the NIPALS algorithm for PLS regression with one single response variable. This version, denoted a CF-PLS, provides significant advantages over the standard PLS. First of all, it strongly reduces the over-fit of the regression. Secondly, R2 for the null hypothesis follows a Beta distribution only function of the number of observations, which allows the use of a probabilistic framework to test the validity of a component. Thirdly, the models generated with CF-PLS have comparable if not better prediction ability than the models fitted with NIPALS. Finally, the scores and loadings of the CF-PLS are directly related to the R2, which makes the model and its interpretation more reliable. Copyright © 2011 John Wiley & Sons, Ltd.