A framework for sequential multiblock component methods
作者： Sijmen de Jong , Age K. Smilde , Johan A. Westerhuis
DOI: 10.1002/CEM.811
关键词:
摘要: Multiblock or multiset methods are starting to be used in chemistry and biology study complex data sets. In chemometrics, sequential multiblock popular; that is, calculate one component at a time use deflation for finding the next component. this paper framework is provided methods, including hierarchical PCA (HPCA; two versions), consensus (CPCA; versions) generalized (GPCA). Properties of derived characteristics discussed. All illustrated with real five-block example from chromatography. The only clear optimization criteria GPCA version CPCA. Of these, shown give inferior results compared Copyright © 2003 John Wiley & Sons, Ltd.
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