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Effect of multivariate process instability on principal component analysis: a case study.

Donald S Holmes·A Erhan Mergen
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Abstract

With the rising use of principal component analysis/partial least squares (PCA/PLS) in the process analytical technology (PAT) initiative of the pharmaceutical industry, it seems appropriate to view that approach from a statistical process control (SPC) perspective. The purpose of this study was to demonstrate the effect of process instability (ie, state of statistical out-of-control) on use of PCA/PLS. The demonstrated differences in results should encourage PCA/PLS users to incorporate SPC as an active part of their process analytical control (PAC) toolkit to check for stability prior to drawing conclusions based on PCA/PLS analysis.

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Chi-Square DistributionComputer SimulationLeast-Squares AnalysisMultivariate AnalysisPrincipal Component AnalysisJournal Article

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Donald S Holmes, A Erhan Mergen. 2005-04-29. Effect of multivariate process instability on principal component analysis: a case study.. https://doi.org/10.1208/aapsj070111

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