Multivariate Process Analysis
Multivariate Process Analysis is a statistical methodology that distinguishes itself from univariate or bivariate approaches by simultaneously analyzing multiple interrelated process variables to identify complex patterns, correlations, and causal relationships within dynamic systems, particularly for monitoring, controlling, or optimizing critical process parameters in industrial and scientific applications.
573
Publications
35.9K
Citations
1.2K
Authors
448
Institutions
Publications per year
2017–2026
158
Parents
573
Process monitoring and diagnosis by multiblock PLS methods
John F. MacGregor, Christiane Jaeckle, Costas Kiparissides et al. · AIChE Journal · 1994 · 772 citations
1–5 of 573
1.2K
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14
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Hong Kong University of Science and Technology, Hong Kong SAR China
14 publications · 902 citations
13
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13
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12
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1–5 of 1.2K
448
East China University of Science and Technology
Shanghai, China
22 h-index
84 publications
4.8K citations

McMaster University
Hamilton, Canada
20 h-index
47 publications
12.9K citations

Zhejiang University of Technology
Hangzhou, China
16 h-index
42 publications
1.7K citations
State Key Laboratory of Industrial Control Technology
Hangzhou, China
16 h-index
40 publications
2.1K citations

Northeastern University
Shenyang, China
16 h-index
44 publications
1.9K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
16 h-index
33 publications
2K citations
Tsinghua University
Beijing, China
14 h-index
28 publications
1.2K citations

University of Alberta
Edmonton, Canada
13 h-index
23 publications
2.6K citations
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32 publications · 3.1K citations
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40 publications · 2.6K citations
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45 publications · 2.1K citations
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26 publications · 2.9K citations
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20 publications · 3.7K citations
18
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