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New control charts for monitoring covariance matrix with individual observations

Ostadsharif Memar, A ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. DOI: 10.1002/qre.998
  3. Publisher: 2009
  4. Abstract:
  5. It has recently been shown that the performance of multivariate exponentially weighted mean square and multivariate exponentially weighted moving variance charts of Huwang et al. (J. Qual. Technol. 2007; 39:258-278) in monitoring the variability of a multivariate process for individual observations is better than existing schemes. Both of these control charts monitor a distinct matrix which is an estimator of the in-control covariance matrix. Instead of using the trace, in this paper, we propose a L1-norm and a L2-norm-based distance between diagonal elements of the estimators from their expected values to design new control charts in monitoring the covariance matrix of a multivariate process. The results of simulations show that employing the new control statistics significantly improve the ability of the change detection process in the covariance matrix. © 2009 John Wiley &Sons, Ltd
  6. Keywords:
  7. L 1-norm-based distance ; L2-norm-based distance ; Change detection ; Control charts ; Diagonal elements ; Expected values ; In-control ; Matrix ; Multivariate exponentially weighted mean square deviation ; Multivariate exponentially weighted moving variance ; Multivariate process ; Weighted mean ; Flowcharting ; Graphic methods ; Covariance matrix
  8. Source: Quality and Reliability Engineering International ; Volume 25, Issue 7 , 2009 , Pages 821-838 ; 07488017 (ISSN)
  9. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/qre.998