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EWMA Control Charts for the Smallest and Largest Observations

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References

1990Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements1,939 cited
1972An Approach to the Probability Distribution of Cusum Run Length886 cited
1997Introduction to Statistical Quality Control420 cited
1992An EWMA for Monitoring a Process Standard Deviation328 cited
1993The Exponentially Weighted Moving Variance209 cited
1991Some Omnibus Exponentially Weighted Moving Average Statistical Process Monitoring Schemes196 cited
1995Joint Monitoring of Process Mean and Variance Using Exponentially Weighted Moving Average Control Charts168 cited
1995Statistical Process Control of Multiple Stream Processes61 cited

Cited by

2011Extended maximum generally weighted moving average control chart for monitoring process mean and variability50 cited
2005Adjusted-loss-function charts with variable sample sizes and sampling intervals39 cited
2010The Max EWMAMS control chart for joint monitoring of process mean and variance with individual observations32 cited
2005Generally weighted moving average control chart for monitoring process variability31 cited
2006Monitoring Process Variability Using EWMA27 cited
2006A CUSUM scheme with variable sample sizes for monitoring process shifts25 cited

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2006A single CUSUM chart using a single observation to monitor a variable23 cited

2016Statistically constrained economic design of maximum double EWMA control charts based on loss functions19 cited

2014A Sum of Squares Generally Weighted Moving Average Control Chart19 cited

2008A VARIABLE SAMPLE SIZE S2-EWMA CONTROL CHART FOR MONITORING THE PROCESS VARIANCE19 cited

2005Weighted-loss-function control charts17 cited

2007Monitoring process variability using exponentially weighted moving sample variance control charts16 cited

2013Maximum Chi-Square Generally Weighted Moving Average Control Chart for Monitoring Process Mean and Variability16 cited

2016The effects of measurement error on the MAX EWMAMS control chart14 cited

2008Monitoring process variability using exponentially weighted moving sample variance control charts13 cited

2020A two-step method for monitoring normally distributed multi-stream processes in high dimensions13 cited