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• W2756265939 abstract "Most existing control charts monitoring the covariance matrix of multiple variables were restricted to multivariate normal distribution. When the process distribution is non-normal, the performance of these control charts could potentially be (highly) affected, especially for heavy-tail distributions. To construct a robust multivariate control chart for monitoring the covariance matrix, we applied spatial sign covariance matrix and maximum norm to the exponentially weighted moving average (EWMA) scheme and proposed a Phase II control chart. The novel chart is distribution-free under the family of elliptical directions distributions. Comparison studies demonstrate that the novel method is very powerful in detecting various shifts, especially for heavy-tailed distributions. The implementation of the proposed control chart is demonstrated by a white wine data." @default.
• W2756265939 created "2017-09-25" @default.
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• W2756265939 date "2017-09-12" @default.
• W2756265939 modified "2023-10-16" @default.
• W2756265939 title "A robust multivariate sign control chart for detecting shifts in covariance matrix under the elliptical directions distributions" @default.
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• W2756265939 doi "https://doi.org/10.1080/16843703.2017.1372852" @default.
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