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A simulation study and evaluation of multivariate forecast based control charts applied to ARMA processes
9 references·4 citing·37 second hop
A simulation study and evaluation of multivariate forecast based control charts applied to ARMA processes (2003)A simulation study and evaluation of mult…The AutoregressiveT2 Chart for Monitoring Univariate Autocorrelated Processes (2002)The AutoregressiveT2 Chart fo…EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes (1999)EWMA Control Charts for Monit…Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes (1999)Control Charts for Monitoring…Combined Control Charts for Forecast-Based Monitoring Schemes (1996)Combined Control Charts for F…Run-Length Distributions of Special-Cause Control Charts for Correlated Processes (1994)Run-Length Distributions of S…An evaluation of forecast-based quality control schemes (1994)An evaluation of forecast-bas…A Multivariate Exponentially Weighted Moving Average Control Chart (1992)A Multivariate Exponentially …Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)Exponentially Weighted Moving…Time-Series Modeling for Statistical Process Control (1988)Time-Series Modeling for Stat…Multivariate auto‐correlated process control by a residual‐based mixed CUSUM‐EWMA model (2023)Multivariate auto‐correlated …USAGE OF CONTROL CHARTS FOR TIME SERIES ANALYSIS IN FINANCIAL MANAGEMENT (2014)USAGE OF CONTROL CHARTS FOR T…The Usage of Time Series Control Charts for Financial Process Analysis (2012)The Usage of Time Series Cont…One-Class Classification-Based Control Charts for Monitoring Autocorrelated Multivariate Processes (2010)One-Class Classification-Base…Time Series Analysis Forecasting and Control (1971)A New SPC Monitoring Method: The ARMA Chart (2000)Distribution-free multivariate process control based on log-linear modeling (2008)A survey of control-chart pattern-recognition literature (1991–2010) based on a new conceptual classification scheme (2012)Time Series Analysis Forecasting and Control. (1971)The State of Statistical Process Control as We Proceed into the 21st Century (2000)A Rank-Based Multivariate CUSUM Procedure (2001)The Performance of Exponentially Weighted Moving Average Charts With Estimated Parameters (2001)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)A Reference-Free Cuscore Chart for Dynamic Mean Change Detection and a Unified Framework for Charting Performance Comparison (2006)Optimal Properties of Exponentially Weighted Forecasts (1960)A review of multivariate control charts (1995)Research Issues and Ideas in Statistical Process Control (1999)Control Chart Tests Based on Geometric Moving Averages (1959)Multivariate SPC Methods for Process and Product Monitoring (1996)Control Chart Tests Based on Geometric Moving Averages (2000)Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications (2014)Smoothing, Forecasting and Prediction of Discrete Time Series. (1964)Introduction to Statistical Quality Control (1992)Autocorrelated process monitoring using triggered cuscore charts (2002)Detecting process mean shift in the presence of autocorrelation: a neural-network based monitoring scheme (2004)Practical Design of Generalized Likelihood Ratio Control Charts for Autocorrelated Data (2008)Time Series Analysis: Forecasting and Control. (1978)Dual CUSUM control schemes for detecting a range of mean shifts (2005)SPC Procedures for Monitoring Autocorrelated Processes (2007)Directional MEWMA Schemes for Multistage Process Monitoring and Diagnosis (2008)Multivariate Generalizations of Cumulative Sum Quality-Control Schemes (1988)Performance Evaluation of One‐Class Classification‐based Control Charts through an Industrial Application (2012)A One-Class Classification-Based Control Chart Using the K -Means Data Description Algorithm (2014)Synthetic charts to control bivariate processes with autocorrelated data (2016)Robustness of Forecast-Based Monitoring Schemes (1998)Scenario analysis of demand in a technology market using leading indicators (2001)A CUSUM Scheme for Autocorrelated Observations (2002)Exact Results for Shewhart Control Charts With Supplementary Runs Rules (1987)Statistical process control procedures for correlated observations (1991)Statistical Process Monitoring and Feedback Adjustment: A Discussion (1992)
this work references cited by second hop

References

  • 1990Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements1,939 cited
  • 1992A Multivariate Exponentially Weighted Moving Average Control Chart1,231 cited
  • 1988Time-Series Modeling for Statistical Process Control724 cited
  • 1994Run-Length Distributions of Special-Cause Control Charts for Correlated Processes304 cited
  • 1999EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes303 cited
  • 1999Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes197 cited
  • 2002The AutoregressiveT2 Chart for Monitoring Univariate Autocorrelated Processes136 cited
  • 1994An evaluation of forecast-based quality control schemes69 cited
  • 1996Combined Control Charts for Forecast-Based Monitoring Schemes58 cited

Cited by

  • 2010One-Class Classification-Based Control Charts for Monitoring Autocorrelated Multivariate Processes22 cited
  • 2014USAGE OF CONTROL CHARTS FOR TIME SERIES ANALYSIS IN FINANCIAL MANAGEMENT21 cited
  • 2012The Usage of Time Series Control Charts for Financial Process Analysis16 cited
  • 2023Multivariate auto‐correlated process control by a residual‐based mixed CUSUM‐EWMA model15 cited

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