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Data evaluation in chromatography by principal component analysis
Author(s) -
Cserháti T.
Publication year - 2010
Publication title -
biomedical chromatography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.4
H-Index - 65
eISSN - 1099-0801
pISSN - 0269-3879
DOI - 10.1002/bmc.1294
Subject(s) - principal component analysis , chromatography , chemistry , gas chromatography , high performance liquid chromatography , multivariate statistics , artificial intelligence , computer science , machine learning
Abstract The newest achievements in the employment of principal component analysis, a multivariate mathematical statistical method, in the evaluation of chromatographic retention data are compiled. The results obtained by various chromatographic technologies such as gas–liquid chromatography, thin–layer chromatography, high‐performance liquid chromatography and electrically driven systems are compiled and briefly discussed. Copyright © 2009 John Wiley & Sons, Ltd.