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Robust T~2 control chart using median-based estimators

机译:使用基于中位数的估算器的鲁棒T〜2控制图

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One of the most widely used multivariate control charts is the Hotelling T-2. In order to construct a Hotelling T(2)control chart, the mean vector (mu) and the variance-covariance matrix (sigma) must be first estimated. The classical estimators of mu and sigma are usually used to design Hotelling T(2)control chart. The classical estimators are sensitive to the presence of outliers. One way to deal with outliers is to use robust estimators. In this study, a robust T(2)control chart is proposed. The mean vector is obtained from the sample median. The median absolute deviation and the comedian are used as the estimates of the elements of the variance-covariance matrix. The proposed robust estimators of the mean vector and the variance-covariance matrix are compared with the sample mean vector and the sample variance-covariance matrix, and the M estimator of these parameters, through efficiency and robustness measures. The performances of the proposed robust T(2)control chart and the classical and the M estimators are also compared by means of average run length. Simulation results reveal that the proposed robust T(2)control chart has much better performance than the traditional Hotelling T(2)and similar performance to the M estimator in detecting shifts in process mean vector. Use of other robust estimators to estimate the process parameters is an area for further research.
机译:最广泛使用的多变量控制图之一是Hotelling T-2。为了构建热均匀的T(2)控制图,必须首先估计平均载体(MU)和方差协方差矩阵(Sigma)。 Mu和Sigma的经典估计通常用于设计热控T(2)控制图。经典估算器对异常值的存在敏感。处理异常值的一种方法是使用强大的估计。在本研究中,提出了一种强大的T(2)控制图。平均载体从样品中值获得。中位绝对偏差和喜剧演员用作方差协方差矩阵的元素的估计。通过效率和鲁棒性测量将所提出的平均载体和方差协方差矩阵和这些参数的M个估计器进行比较了平均载体和方差协方差矩阵的鲁棒估计器。所提出的鲁棒T(2)控制图和经典和M估计的性能也通过平均运行长度进行比较。仿真结果表明,所提出的鲁棒T(2)控制图比传统的热控T(2)和与M估计器类似的性能相似的性能更好的性能。使用其他强大估算器来估计过程参数是进一步研究的区域。

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