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Control Chart for Autocorrelated Processes with Heavy Tailed Distributions

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  • Thaga Keoagile

    (Department of Statistics, University of Botswana, Private Bag 0022, Gaborone, Botswana. THAGAK@mopipi.ub.bw)

Abstract

Standard control charts are constructed under the assumption that the observations taken from the process of interest are independent over time; however, in practice the observations in many cases are actually correlated. This paper considers the problem of monitoring a process in which the observations can be represented as a first-order autoregressive model following a heavy tailed distribution. We propose a chart based on computing the control limits using the process mean and the standard error of the least absolute deviation for the case when the process quality characteristics follows a heavy tailed t-distribution. This chart has narrow control limits since the standard error of the least absolute deviation is smaller than that of the ordinary least square estimator in the case of heavy tailed distributions.

Suggested Citation

  • Thaga Keoagile, 2008. "Control Chart for Autocorrelated Processes with Heavy Tailed Distributions," Stochastics and Quality Control, De Gruyter, vol. 23(2), pages 197-206, January.
    • Handle: RePEc:bpj:ecqcon:v:23:y:2008:i:2:p:197-206:n:4
    DOI: 10.1515/EQC.2008.197
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    References listed on IDEAS

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    1. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626, September.
    2. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models 2 volume set," Cambridge Books, Cambridge University Press, number 9780521478373, July.
    3. Thaga K. & Kgosi P. M. & Gabaitiri L., 2007. "Max-Chart for Autocorrelated Processes," Stochastics and Quality Control, De Gruyter, vol. 22(1), pages 87-105, January.
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