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Ӧ�ø���ͳ�� 2008, 24(3) 297-311 DOI:
ISSN: 1001-4268 CN: 31-1256 |
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����֤���˵��ܿ�ƽ�����г��ȳ�ִ�ʱ, ���ؿ���ͼ�������ŵ�: һ����Ƚ�GLR (������Ȼ��) ��GEWMA (����ָ��Ȩ���ƶ�ƽ��)����ͼ�����Դ������ĸ�����; �����ܹ��Ͽ�ؼ���ֵ�仯�Ĵ�С. ��ֵģ��Ҳ����: ���ؿ���ͼ���������乹�ɵĵ�������ͼ, �����ڼ��δ֪�ľ�ֵ�䶯����Ҳ���ڵ�����CUSUM, EWMA, ����EWMA��GLR����ͼ. |
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Statistical
process
control
change
point
detection
average
run
length.
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A Multi-Chart Approach for Mean Shift Detection |
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Han Dong, Tsung Fugee, Hu Xijian |
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Department of Mathematics, Shanghai Jiao Tong University; Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology; School of Mathematics and System Science, Xinjiang University |
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Abstract:
In this paper we consider a multi-chart for detecting a unknown shift in the mean of an identically distributed process. It is shown that the multi-chart has usually two advantages: one is in that it can much reduce computational complexity compared to the GLR (generalized likelihood ratio) and GEWMA (generalized exponentially weighted moving average) control charts when the in-control ARL (average run length) is large; the other is that it can quickly detect the size of the mean shift. Moreover, the numerical simulations show that the multi-chart can not only perform better than its constituent charts which consist of the multi-chart in the sense that the average of the ARLs of the constituent charts is large than that of the multi-chart, but also be superior on the whole to a single CUSUM, EWMA, EWMA multi-chart and GLR control charts in detecting the various mean shifts when the in-control ARL is not large. |
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Keywords:
Statistical process control
change point detection
average run length.
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