Please use this identifier to cite or link to this item:
http://hdl.handle.net/2282/285
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| Title: | Informative PLS score-loading plots for process understanding |
| Authors: | Ergon, Rolf |
| Issue Date: | 2004 |
| Publishers version: | http://dx.doi.org/10.1016/j.jprocont.2004.02.004 |
| Abstract: | Principal component regression (PCR) based on principal component analysis (PCA) and partial least squares regression (PLSR)
are well known projection methods for analysis of multivariate data. They result in scores and loadings that may be visualized in a
score-loading plot (biplot) and used for process monitoring. The difficulty with this is that often more than two principal or PLS
components have to be used, resulting in a need to monitor more than one such plot. However, it has recently been shown that for a
scalar response variable all PLSR/PCR models can be compressed into equivalent PLSR models with two components only. After a
summary of the underlying theory, the present paper shows how such two-component PLS (2PLS) models can be utilized in
informative score-loading biplots for process understanding and monitoring. The possible utilization of known projection model
monitoring statistics and variable contribution plots is also discussed, and a new method for visualization of contributions directly
in the biplot is presented. An industrial data example is included. |
| Keywords: | PLS
Score-loading correspondence
Biplot
Process understanding and monitoring |
| Publisher: | Elsevier |
| Document type: | Journal article |
| URI: | http://hdl.handle.net/2282/285 |
| Appears in Collections: | Institutt for elektro, IT og kybernetikk
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