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Phase II monitoring of general linear profiles in the presence of between-profile autocorrelation

机译:在轮廓间自相关的情况下,对一般线性轮廓进行II期监控

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摘要

In this paper, an approach based on the U statistic is first proposed to eliminate the effect of between-profile autocorrelation of error terms in Phase-II monitoring of general linear profiles. Then, a control chart based on the adjusted parameter estimates is designed to monitor the parameters of the model. The performance of the proposed method is compared with the ones of some existing methods in terms of average run length for weak, moderate, and strong autocorrelation coefficients under different shift scenarios. The results show that the proposed method provides significantly better results than the competing methods to detect shifts in the regression parameters, while the competing methods perform better in detecting shifts in the standard deviation. At the end, the applicability of the proposed method is illustrated by an example. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:在本文中,首先提出了一种基于U统计量的方法,以消除误差项之间的轮廓间自相关在一般线性轮廓的II期监视中的影响。然后,基于调整后的参数估计值的控制图被设计为监视模型的参数。在不同移位场景下,针对弱,中和强自相关系数的平均游程长度,将所提方法的性能与现有方法进行了比较。结果表明,所提出的方法提供了比竞争方法更好的结果来检测回归参数的偏移,而竞争方法在检测标准偏差的偏移方面表现更好。最后通过一个例子说明了所提出方法的适用性。版权所有(c)2015 John Wiley&Sons,Ltd.

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