Monitoring multivariate process variability via eigenvalues
Fan,Jinyu1; Shu,Lianjie1; Zhao,Honghao2; Yeung,Hangfai1
Source PublicationComputers and Industrial Engineering
ABS Journal Level2

Various methods have been proposed to monitor changes in a process covariance matrix. In view that a covariance matrix can be fully defined by its eigenvalues and eigenvectors, this paper suggests monitoring the covariance matrix based on eigenvalues as another alternative. Although there are some recent discussions about the use of eigenvalues for hypothesis testing in multivariate analysis, the use of them for monitoring covariance matrix changes has been less studied in multivariate quality control. The simulation results show that the proposed method performs especially well under simultaneous shifts in both variance and correlation elements and competitively under shifts in variance or correlation elements only, compared to the existing approaches. This demonstrates a good property of the proposed method being able to provide a robust detection performance under a wide variety of scenarios. A real example is also provided to illustrate the implementation of the proposed method.

KeywordCovariance Matrix Eigenvalues Multivariate Statistical Process Control Sparsity Variability
URLView the original
Indexed BySSCI ; SSCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Industrial
WOS IDWOS:000418207900020
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Cited Times [WOS]:9   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Corresponding AuthorShu,Lianjie
Affiliation1.Faculty of Business Administration,University of Macau,,Macao
2.School of Business,Macau University of Science and Technology,,Macao
First Author AffilicationFaculty of Business Administration
Corresponding Author AffilicationFaculty of Business Administration
Recommended Citation
GB/T 7714
Fan,Jinyu,Shu,Lianjie,Zhao,Honghao,et al. Monitoring multivariate process variability via eigenvalues[J]. Computers and Industrial Engineering,2017,113:269-281.
APA Fan,Jinyu,Shu,Lianjie,Zhao,Honghao,&Yeung,Hangfai.(2017).Monitoring multivariate process variability via eigenvalues.Computers and Industrial Engineering,113,269-281.
MLA Fan,Jinyu,et al."Monitoring multivariate process variability via eigenvalues".Computers and Industrial Engineering 113(2017):269-281.
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