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The OPLS methodology for analysis of multi‐block batch process data
Author(s) -
Gabrielsson Jon,
Jonsson Hans,
Airiau Christian,
Schmidt Bernd,
Escott Richard,
Trygg Johan
Publication year - 2006
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1009
Subject(s) - variation (astronomy) , block (permutation group theory) , computer science , process (computing) , data mining , variable (mathematics) , data type , data analysis , mathematics , mathematical analysis , physics , geometry , astrophysics , programming language , operating system
With increasing availability of different process analysers multiple data sources are commonly available and this will impose new challenges and enable new types of investigations. The ability to separate joint, complementary and redundant information in multiple block data will be of increasing importance. In this study data from a batch mini plant were collected and O2PLS was implemented to facilitate a combined analysis of spectroscopic and process data. This enables assessment of both the joint and complementary variations in the respective data sets. The different types of variation that were separated were then modelled together to evaluate their individual correlation to a time response. By combining data of different origin an uncomplicated summary of the variation was accomplished and a deeper understanding of process interactions was gained. The analysis of separated variation with a response variable proved useful for verifying the supposed correlation between the joint variation and time. Copyright © 2007 John Wiley & Sons, Ltd.