Chi-Square quantile-based multivariate variance monitoring for individual observations |
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Authors: | Wook-Yeon Hwang |
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Affiliation: | College of Global Business, Dong-A University, SeoGu GudukRo, Busan, South Korea |
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Abstract: | Under the normality assumption, some statistics for monitoring a multivariate process variance for individual observations can be used to detect a variance shift, but the distribution of their in-control run length has a high variance as well as the median that is extremely smaller than the mean, which leads to many false alarms in the in-control process. In this paper, we propose a chi-square quantile-based monitoring statistic which is free of the problems. The numerical experiments show that the proposed monitoring statistics outperform the existing monitoring statistics in terms of the detection of a shift for the variance. |
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Keywords: | Chi-square quantile Covariance matrix Individual observations Multivariate variance monitoring |
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