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Auxiliary information based joint monitoring control chart using generalized likelihood ratio test statistic

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  • Muhammad Noor-ul-Amin
  • Waqas Kazmi

Abstract

The use of auxiliary variable has given considerable attention to improving the sensitivity of control charts to observe the changes in process parameters. Exponentially weighted moving average (EWMA) control chart is effective to identify the small or moderate changes in the process parameters. This study is designed to develop EWMA control chart by using auxiliary information for joint monitoring of process mean and variance using the generalized likelihood ratio test statistic named as MdELRt-EWMA control chart. Performance measures average run length (ARL) and the standard deviation of the run length (SDRL) are used to assess the efficiency of the proposed chart. An extensive Monte Carlo simulations are performed to evaluate the sensitivity of the MdELRt-EWMA control chart. A comparative study is conducted and observed the superiority of the proposed control chart over the competitors.

Suggested Citation

  • Muhammad Noor-ul-Amin & Waqas Kazmi, 2022. "Auxiliary information based joint monitoring control chart using generalized likelihood ratio test statistic," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(8), pages 2438-2460, April.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:8:p:2438-2460
    DOI: 10.1080/03610926.2020.1776328
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