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NTIS 바로가기Journal of statistical computation and simulation, v.74 no.1, 2004년, pp.47 - 62
Wong, H. B. (National University of Singapore Department of Statistics and Applied Probability 3 Science Drive 2 Singapore Singapore 117543) , Gan, F. F. (National University of Singapore Department of Statistics and Applied Probability 3 Science Drive 2 Singapore Singapore 117543) , Chang, T. C. (University of Macau Macao South China P.O. Box 3001)
The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) charts are often recommended for process monitoring when a quick detection of small or moderate sustained shifts in the process mean is desired. In general, the moving average (MA) chart is slightly less sensitive than the EWMA or CUSUM chart in detecting the intended shift but the overall performance is quite similar. The in-control run length distributions of the MA chart and the corresponding EWMA chart are nearly identical. The MA chart is much simpler to understand because it is based on the simple average, and the MA is used widely in the financial sector for smoothing stock and index trends. We develop a simple design procedure for the MA chart and the combined MA-Shewhart scheme for an easy implementation.
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