Variable influence on projection (VIP) for OPLS models and its applicability in multivariate time series analysis

Galindo-Prieto, Beatriz (author): Umeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC) ; Industrial Doctoral School IDS)

Trygg, Johan (author): Umeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC)

(creator_code:org_t)

Elsevier, 2015
2015
English.
In: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 146, s. 297-304

Related links:: https://urn.kb.se/re...; show more...; https://doi.org/10.1...; show less...

Abstract Subject headings

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.

By the author/editor: Galindo-Prieto, ...; Eriksson, Lennar ...; Trygg, Johan

About the subject

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