Variable influence on projection (VIP) for OPLS models and its applicability in multivariate time series analysis
2015 (English)In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 146, 297-304 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 146, 297-304 p.
VIP, Variable influence on projection, Multivariate time series analysis, OPLS, Variable selection, Process monitoring
IdentifiersURN: urn:nbn:se:umu:diva-106759DOI: 10.1016/j.chemolab.2015.05.001OAI: oai:DiVA.org:umu-106759DiVA: diva2:844653