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Multivariate control chart based on the highest possibility region

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  • Ting-Ting Gang
  • Jun Yang
  • Yu Zhao

Abstract

The T -super-2 control chart is widely adopted in multivariate statistical process control. However, when dealing with asymmetrical or multimodal distributions using the traditional T -super-2 control chart, some points with relatively high occurrence possibility might be excluded, while some points with relatively low occurrence possibility might be accepted. Motived by the thought of the highest posterior density credible region, we develop a control chart based on the highest possibility region to solve this problem. It is shown that the proposed multivariate control chart will not only meet the false alarm requirement, but also ensure that all the in-control points are with relatively high occurrence possibility. The advantages and effectiveness of the proposed control chart are demonstrated by some numerical examples in the end.

Suggested Citation

  • Ting-Ting Gang & Jun Yang & Yu Zhao, 2013. "Multivariate control chart based on the highest possibility region," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1673-1681, August.
  • Handle: RePEc:taf:japsta:v:40:y:2013:i:8:p:1673-1681
    DOI: 10.1080/02664763.2013.790007
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    Cited by:

    1. YangXia Luo, 2017. "Statistics and recognition for software birthmark based on clustering analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 308-324, January.

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