Trivariate Copulas on the MEWMA Control Chart

Authors

  • Sasigarn Kuvattana Applied Statistics, Basic Science, Maejo University Phrae Campus, Phrae, Thailand
  • Saowanit Sukparungsee Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand

Keywords:

Average run length (ARL), Monte Carlo simulation, Kendall’s tau

Abstract

Copulas are used to model multivariate distribution with continuous margins and dependence observations. This paper proposes four types of copulas on the multivariate exponentially weighted moving average (MEWMA) control chart for trivariate case. Observations are generated by an exponential distribution based on the Monte Carlo simulation for the Clayton, Frank, Gumbel and normal copulas and the mean shifts are 1.05, 1.25, 1.5, 2, 2.5 and 3. The performance of the control charts describes in terms of the average run length (ARL). Levels of the dependence of random variables are measured by Kendall’s tau gif.latex?(\tau&space;) as 0.2, 0.5 and 0.8 for small, moderate and large dependencies. The results reveal that the Clayton copula performs the ARL1 values less than the others for almost mean shifts.

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Published

2022-09-29

How to Cite

Kuvattana, S. ., & Sukparungsee , S. . (2022). Trivariate Copulas on the MEWMA Control Chart. Thailand Statistician, 20(4), 928–938. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/247475

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Section

Articles