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- Galindo-Prieto, BeatrizUmeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC) ; Industrial Doctoral School IDS) (author)
Variable influence on projection (VIP) for OPLS models and its applicability in multivariate time series analysis
- Article/chapterEnglish2015
Publisher, publication year, extent ...
- Elsevier,2015
- printrdacarrier
Numbers
- LIBRIS-ID:oai:DiVA.org:umu-106759
- https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-106759URI
- https://doi.org/10.1016/j.chemolab.2015.05.001DOI
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- Language:English
- Summary in:English
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Notes
- Abstract Recently a new parameter to infer variable importance in orthogonal projections to latent structures (OPLS) was presented. Called OPLS-VIP (variable influence on projection), this parameter is here applied in multivariate time series analysis to achieve an improved diagnosis of process dynamics. To this end, OPLS-VIP has been tested in three real-world industrial data sets; the first data set corresponds to a pulp manufacturing process using a continuous digester, the second one involves data from an industrial heater that experienced problems, and the third data set contains measures of the chemical oxygen demand into the effluent of a newsprint mill. The outcomes obtained using OPLS-VIP are benchmarked against classical PLS-VIP results. It is demonstrated how OPLS-VIP provides a better diagnosis and understanding of the time series behavior than PLS-VIP.
Subject headings and genre
- NATURVETENSKAP Kemi hsv//swe
- NATURAL SCIENCES Chemical Sciences hsv//eng
- VIP
- Variable influence on projection
- Multivariate time series analysis
- OPLS
- Variable selection
- Process monitoring
Added entries (persons, corporate bodies, meetings, titles ...)
- Eriksson, LennartMKS Umetrics AB, Umeå, Sweden (author)
- Trygg, JohanUmeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC)(Swepub:umu)jotr0001 (author)
- Umeå universitetKemiska institutionen (creator_code:org_t)
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- In:Chemometrics and Intelligent Laboratory Systems: Elsevier146, s. 297-3040169-74391873-3239
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