Citation

Yeong, Wai Chung and Thien, Bryan Chek Hui and Lim, Sok Li and Khoo, Michael B. C. and Shi, Yang (2026) A synthetic multivariate exponentially weighted moving average chart for the coefficient of variation. Journal of Statistical Computation and Simulation. pp. 1-21. ISSN 0094-9655

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Abstract

The synthetic multivariate exponentially weighted moving average (MEWMA) chart, which combines the features of the MEWMA and multivariate synthetic charts, is proposed to improve sensitivity in detecting upward shifts in the coefficient of variation (γ ) for multivariate normal processes. In this chart,the MEWMA charting statistics that fall beyond the control limits are not immediately detected as out-of-control samples. Instead, the chart waits until two charting statistics fall beyond the limits and only signals an out-of-control condition when the distance between them is less than a threshold. This papershowsthe chart’s operations, formulae for the various run length metrics, and algorithms to determine the chart’s optimal charting parameters. Through numerical examples, the proposed chartsignificantly outperformsthe MEWMA,synthetic and Shewhart (γ ) charts, with percentages of improvement between 8.86% and 52.57%, 0.88% and 63.78% and 17.65% and 75.06%, respectively. The chart is then implemented on an illustrative example.

Item Type:	Article
Uncontrolled Keywords:	Average run length, expected average run length
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Sep 2026 06:40
Last Modified:	02 Sep 2026 06:40
URII:	http://shdl.mmu.edu.my/id/eprint/16532

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