More recently in statistical quality control studies, researchers are paying more attention to quality characteristics having nonnormal distributions. In the present article, a generalized multiple dependent state (GMDS) sampling control chart is proposed based on the transformation of gamma quality characteristics into a normal distribution. The parameters for the proposed control charts are obtained using in-control average run length (ARL) at specified shape parametric values for different specified average run lengths. The out-of-control ARL of the proposed gamma control chart using GMDS sampling is explored using simulation for various shift size changes in scale parameters to study the performance of the control chart. The proposed gamma control chart performs better than the existing multiple dependent state sampling (MDS) based on gamma distribution and traditional Shewhart control charts in terms of average run lengths. A case study with real-life data from ICU intake to death caused by COVID-19 has been incorporated for the realistic handling of the proposed control chart design.

中文翻译：

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基于广义多相关状态采样的伽玛分布变量监测由COVID-19引起的死亡率

最近在统计质量控制研究中，研究人员越来越关注具有非正态分布的质量特征。在本文中，基于将伽玛质量特征转换为正态分布，提出了广义多相关状态（GMDS）采样控制图。拟议控制图的参数是通过使用控制内平均行程长度（ARL）在不同的指定平均行程长度的指定形状参数值下获得的。通过模拟对比例参数的各种移位大小变化进行仿真，探索了使用GMDS采样的拟议伽玛控制图的失控ARL，以研究控制图的性能。提出的伽玛控制图在平均游程长度方面比基于伽玛分布和传统Shewhart控制图的现有多依存状态采样（MDS）更好。案例研究结合了从ICU摄入到死于由COVID-19引起的死亡的真实数据，对拟议的控制图设计进行了实际处理。