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TheT2chart with mixed samples to control bivariate autocorrelated processes

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References

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2010Effect of measurement error and autocorrelation on theX¯chart102 cited
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1996Variable Sampling IntervalXCharts in the Presence of Correlation81 cited
2005Properties of theT2Control Chart When Parameters Are Estimated80 cited
2006The quality control chart for monitoring multivariate autocorrelated processes61 cited
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2011Variable parameter and double sampling charts in the presence of correlation: The Markov chain approach56 cited
2014Economic design of Shewhart control charts for monitoring autocorrelated data with skip sampling strategies48 cited
2007Artificial neural networks in applying MCUSUM residuals charts for AR(1) processes47 cited
2008Support vector regression based residual MCUSUM control chart for autocorrelated process

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43 cited

2008Shift detection and source identification in multivariate autocorrelated processes42 cited

2007Economic and economic-statistical design of a chi-square chart for CBM39 cited

Cited by

2022The Shewhart-type RZ control chart for monitoring the ratio of autocorrelated variables22 cited
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2020On autoregressive model selection for the exponentially weighted moving average control chart of residuals in monitoring the mean of autocorrelated processes19 cited
2016Synthetic charts to control bivariate processes with autocorrelated data19 cited
2020A combined mixed- s -skip sampling strategy to reduce the effect of autocorrelation on the X scheme with and without measurement errors19 cited
2018New sampling strategies to reduce the effect of autocorrelation on the synthetic T2 chart to monitor bivariate process18 cited
2019Shewhart-type monitoring schemes with supplementary w-of-w runs-rules to monitor the mean of autocorrelated samples18 cited
2021A new double sampling scheme to monitor the process mean of autocorrelated observations using an AR(1) model with a skip sampling strategy16 cited
2017Monitoring bivariate and trivariate mean vectors with a Shewhart chart15 cited
2018Attribute control charts for monitoring the covariance matrix of bivariate processes13 cited
2020The new synthetic and runs-rules schemes to monitor the process mean of autocorrelated observations with measurement errors12 cited
2021Improved simple linear profiling method with application to chemical gas sensors11 cited
2017The S chart with variable charting statistic to control bi and trivariate processes11 cited
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