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Research Article

Adaptive multivariate EWMA charts for monitoring sparse mean shifts based on parameter optimization design

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Pages 2670-2683 | Received 18 Dec 2020, Accepted 13 Mar 2021, Published online: 30 Mar 2021

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Muhammad Imran, Jinsheng Sun, Fatima Sehar Zaidi, Zameer Abbas & Hafiz Zafar Nazir. (2023) On designing efficient multivariate exponentially weighted moving average control chart for compositional data using variable sample size. Journal of Statistical Computation and Simulation 93:10, pages 1622-1643.
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Abdul Haq & Anila Anis Abbasi. (2023) New weighted adaptive CUSUM charts for monitoring the generalized variance of a bivariate normal process. Journal of Statistical Computation and Simulation 93:4, pages 604-633.
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Articles from other publishers (4)

XueLong Hu, SuYing Zhang, Jing Zhang & Aamir Saghir. (2023) Efficient CUSUM control charts for monitoring the multivariate coefficient of variation. Computers & Industrial Engineering 179, pages 109159.
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Jalal Taji, Hiwa Farughi & Hasan Rasay. (2022) Economic-statistical design of fully adaptive multivariate control charts under effects of multiple assignable causes. Computers & Industrial Engineering 173, pages 108676.
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Abdul Haq & Michael B. C. Khoo. (2022) An adaptive multivariate EWMA mean chart with variable sample sizes and/or variable sampling intervals. Quality and Reliability Engineering International 38:7, pages 3322-3341.
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Nurudeen A. Adegoke, Muhammad Riaz, Khadijat Oladayo Ganiyu & Saddam Akber Abbasi. (2021) One-Sided and Two One-Sided Multivariate Homogeneously Weighted Moving Charts for Monitoring Process Mean. IEEE Access 9, pages 80388-80404.
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