Visualizing principal components analysis for multivariate process data

被引：3
|
作者：
Bisgaard, Soren [1 ,2 ]
Huang, Xuan [1 ]
机构：
[1] Univ Massachusetts, Amherst, MA 01002 USA
[2] Univ Amsterdam, NL-1012 WX Amsterdam, Netherlands
来源：
JOURNAL OF QUALITY TECHNOLOGY | 2008年 / 40卷 / 03期
关键词：
cointegration; data mining; econometrics; multivariate analysis; statistical graphics; statistical process control;
D O I：
10.1080/00224065.2008.11917735
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
引用
收藏
页码：299 / 309
页数：11
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