Informative PLS score-loading plots for process understanding and monitoring
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 pr...
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| Format: | Article |
| Language: | English |
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Norwegian Society of Automatic Control
2005-01-01
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| Series: | Modeling, Identification and Control |
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| Online Access: | http://www.mic-journal.no/PDF/2005/MIC-2005-1-2.pdf |
| _version_ | 1811314404932714496 |
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| author | Rolf Ergon |
| author_facet | Rolf Ergon |
| author_sort | Rolf Ergon |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T11:11:05Z |
| format | Article |
| id | doaj.art-7711b28721484d63a3a6a35d38ce9c17 |
| institution | Directory Open Access Journal |
| issn | 0332-7353 1890-1328 |
| language | English |
| last_indexed | 2024-04-13T11:11:05Z |
| publishDate | 2005-01-01 |
| publisher | Norwegian Society of Automatic Control |
| record_format | Article |
| series | Modeling, Identification and Control |
| spelling | doaj.art-7711b28721484d63a3a6a35d38ce9c172022-12-22T02:49:07ZengNorwegian Society of Automatic ControlModeling, Identification and Control0332-73531890-13282005-01-01261233710.4173/mic.2005.1.2Informative PLS score-loading plots for process understanding and monitoringRolf ErgonPrincipal 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.http://www.mic-journal.no/PDF/2005/MIC-2005-1-2.pdfPLSscore-loading correspondencebiplot |
| spellingShingle | Rolf Ergon Informative PLS score-loading plots for process understanding and monitoring Modeling, Identification and Control PLS score-loading correspondence biplot |
| title | Informative PLS score-loading plots for process understanding and monitoring |
| title_full | Informative PLS score-loading plots for process understanding and monitoring |
| title_fullStr | Informative PLS score-loading plots for process understanding and monitoring |
| title_full_unstemmed | Informative PLS score-loading plots for process understanding and monitoring |
| title_short | Informative PLS score-loading plots for process understanding and monitoring |
| title_sort | informative pls score loading plots for process understanding and monitoring |
| topic | PLS score-loading correspondence biplot |
| url | http://www.mic-journal.no/PDF/2005/MIC-2005-1-2.pdf |
| work_keys_str_mv | AT rolfergon informativeplsscoreloadingplotsforprocessunderstandingandmonitoring |