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On the Robustness of the Shewhart Control Chart to Different Types of Dependencies in Data
16 references·4 citing·35 second hop
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References

  • 1999An Introduction to Copulas7,743 cited
  • 1993Statistical Inference Procedures for Bivariate Archimedean Copulas1,252 cited
  • 1986The Joy of Copulas: Bivariate Distributions with Uniform Marginals790 cited
  • 1988Time-Series Modeling for Statistical Process Control724 cited
  • 1999Research Issues and Ideas in Statistical Process Control631 cited
  • 1991Some Statistical Process Control Methods for Autocorrelated Data604 cited
  • 1984The Shewhart Control Chart—Tests for Special Causes586 cited
  • 1987Exact Results for Shewhart Control Charts With Supplementary Runs Rules455 cited
  • 2004Goodness-of-fit tests for copulas336 cited
  • 1993The Effect of Sample Size on Estimated Limits forXandXControl Charts323 cited
  • 1994Run-Length Distributions of Special-Cause Control Charts for Correlated Processes304 cited
  • 1999EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes303 cited
  • 1974The Effect of Serial Correlation on the Performance of CUSUM Tests275 cited
  • 1978Modification of Control Chart Limits in the Presence of Data Correlation236 cited
  • 1999Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes197 cited

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  • 1998A Statistical Control Chart for Stationary Process Data189 cited
  • Cited by

    • 2016Copula modelling for multivariate statistical process control: a review14 cited
    • 2017Multivariate copulas on the MCUSUM control chart13 cited
    • 2014A control chart using copula-based Markov chain models13 cited
    • 2022Copula-based CUSUM charts for monitoring infectious disease using Markovian Poisson processes12 cited