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Distribution-free exponentially weighted moving average control charts for monitoring unknown location

Listed author(s):
  • Graham, M.A.
  • Mukherjee, A.
  • Chakraborti, S.
Registered author(s):

    Distribution-free (nonparametric) control charts provide a robust alternative to a data analyst when there is lack of knowledge about the underlying distribution. A two-sided nonparametric Phase II exponentially weighted moving average (EWMA) control chart, based on the exceedance statistics (EWMA-EX), is proposed for detecting a shift in the location parameter of a continuous distribution. The nonparametric EWMA chart combines the advantages of a nonparametric control chart (known and robust in-control performance) with the better shift detection properties of an EWMA chart. Guidance and recommendations are provided for practical implementation of the chart along with illustrative examples. A performance comparison is made with the traditional (normal theory) EWMA chart for subgroup averages and a recently proposed nonparametric EWMA chart based on the Wilcoxon–Mann–Whitney statistics. A summary and some concluding remarks are given.

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    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 56 (2012)
    Issue (Month): 8 ()
    Pages: 2539-2561

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    Handle: RePEc:eee:csdana:v:56:y:2012:i:8:p:2539-2561
    DOI: 10.1016/j.csda.2012.02.010
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    1. Graham, M.A. & Chakraborti, S. & Human, S.W., 2011. "A nonparametric exponentially weighted moving average signed-rank chart for monitoring location," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2490-2503, August.
    2. Su, Yan & Shu, Lianjie & Tsui, Kwok-Leung, 2011. "Adaptive EWMA procedures for monitoring processes subject to linear drifts," Computational Statistics & Data Analysis, Elsevier, vol. 55(10), pages 2819-2829, October.
    3. S. Chakraborti & P. Laan & M. A. Wiel, 2004. "A class of distribution-free control charts," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(3), pages 443-462.
    4. Maravelakis, Petros E. & Castagliola, Philippe, 2009. "An EWMA chart for monitoring the process standard deviation when parameters are estimated," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2653-2664, May.
    5. S. W. Human & P. Kritzinger & S. Chakraborti, 2011. "Robustness of the EWMA control chart for individual observations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2071-2087.
    6. Huwang, Longcheen & Huang, Chun-Jung & Wang, Yi-Hua Tina, 2010. "New EWMA control charts for monitoring process dispersion," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2328-2342, October.
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