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Visualizing Principal Components Analysis for Multivariate Process Data

Søren Bisgaard,Xuan Huang-2008-07-01-Journal of Quality Technology
8

TL;DRAbstract

In this article, we suggest a simple method for visualizing the results of principal components analysis (PCA) intended to complement existing graphical methods for multivariate time series data applicable for process analysis and control. The idea is to visualize multivariate data as a surface that in turn can be decomposed with PCA. The surface plots developed in this paper are intended for statistical process analysis but may also help visualize economic data and, in particular, cointegration.

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In this article, we suggest a simple method for visualizing the results of principal components analysis (PCA) intended to complement existing graphical methods for multivariate time series data applicable for process analysis and control. The idea is to visualize multivariate data as a surface that in turn can be decomposed with PCA. The surface plots developed in this paper are intended for statistical process analysis but may also help visualize economic data and, in particular, cointegration.

Keywords

Multivariate statisticsPrincipal component analysisComputer scienceMultivariate analysisProcess (computing)Data miningStatistical graphicsStatistical process control

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