Correspondence Kayoung Park, Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA. Email: kypark@odu.edu Abstract In practice, quality characteristics do not always follow a normal distribution, and quality control processes sometimes generate non-normal response outcomes, including continuous non-normal data and discrete count data. Thus, achieving better results in such situations requires a new control chart derived from various types of response variables. This study proposes a procedure for monitoring response variables that uses control charts based on randomized quantile residuals obtained from a fitted regression model. Simulation studies demonstrate the performance of the proposed control charts under various situations. We illustrate the procedure using two real-data examples, based on normal and negative binomial regression models, respectively. The simulation and real-data results support our proposed procedure.

中文翻译：

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基于随机分位数残差的控制图

通讯作者 Kayoung Park，美国弗吉尼亚州诺福克市奥多明尼安大学数学与统计系。电子邮件：kypark@odu.edu 摘要 在实践中，质量特性并不总是遵循正态分布，质量控制过程有时会产生非正态响应结果，包括连续非正态数据和离散计数数据。因此，在这种情况下获得更好的结果需要从各种类型的响应变量派生出新的控制图。本研究提出了一种监测响应变量的程序，该程序使用基于从拟合回归模型中获得的随机分位数残差的控制图。仿真研究证明了所提出的控制图在各种情况下的性能。我们使用两个真实数据示例来说明该过程，分别基于正态和负二项式回归模型。模拟和实际数据结果支持我们提出的程序。