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Multioutput Least Square SVR Based Multivariate EWMA Control Chart
9 references·2 citing·45 second hop
Multioutput Least Square SVR Based Multivariate EWMA Control Chart (2018)Multioutput Least Square SVR Based Multiv…SPC Procedures for Monitoring Autocorrelated Processes (2007)SPC Procedures for Monitoring…Monitoring the cross-covariances of a multivariate time series (2005)Monitoring the cross-covarian…Effect of Autocorrelation on Performance of the MCUSUM Control Chart (2005)Effect of Autocorrelation on …Multivariate Quality Control Chart for Autocorrelated Processes (2004)Multivariate Quality Control …Research Issues and Ideas in Statistical Process Control (1999)Research Issues and Ideas in …Ewma charts for multivariate time series (1997)Ewma charts for multivariate …Predicting Shifts in the Mean of a Multivariate Time Series Process: An Application in Predicting Business Failures (1993)Predicting Shifts in the Mean…A Multivariate Exponentially Weighted Moving Average Control Chart (1992)A Multivariate Exponentially …The Effect of Serial Correlation on the Performance of CUSUM Tests (1974)The Effect of Serial Correlat…Integrating machine learning based EWMA control charts for multivariate process monitoring (2025)Integrating machine learning …Machine learning based parameter-free adaptive EWMA control chart to monitor process dispersion (2024)Machine learning based parame…Out of the Crisis (1982)Introduction to Statistical Quality Control (1992)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Kollár Ádám Ferenc levelezése (2000)Using Control Charts to Monitor Process and Product Quality Profiles (2004)Effects of Parameter Estimation on Control Chart Properties: A Literature Review (2006)CONTINUOUS INSPECTION SCHEMES (1954)Fitting autoregressive models for prediction (1969)ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)Predicting Corporate Financial Distress: A Time-Series CUSUM Methodology (1999)Fraudulent financial reporting detection and business failure prediction models: a comparison (2008)Predicting Financial Distress: A Comparison of Survival Analysis and Decision Tree Techniques (2015)Time-Series Modeling for Statistical Process Control (1988)Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)The influence of parameter estimation on the ARL of Shewhart type charts for time series (2000)Using vector autoregressive residuals to monitor multivariate processes in the presence of serial correlation (2006)EWMA Control Charts for Monitoring Optimal Portfolio Weights (2007)Economic Control of Quality of Manufactured Product. (1932)Forecasting methods and applications (1993)Properties and Use of the Shewhart Method and Its Followers (2007)Multioutput least square SVR-based multivariate EWMA control chart: The performance evaluation and application (2018)A review of dispersion control charts for multivariate individual observations (2020)Control Chart Tests Based on Geometric Moving Averages (1959)A review of multivariate control charts (1995)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)Multivariate Quality Control (1947)Some Statistical Process Control Methods for Autocorrelated Data (1991)The quality control chart for monitoring multivariate autocorrelated processes (2006)The Effect of Autocorrelation on the Hotelling T2 Control Chart (2014)A nonparametric CUSUM chart for monitoring multivariate serially correlated processes (2020)A Test for a Change in a Parameter Occurring at an Unknown Point (1955)Time Series Analysis: Forecasting and Control (1977)Detecting Initialization Bias in Simulation Output (1982)Confidence Interval Estimation Using Standardized Time Series (1983)A Statistical Control Chart for Stationary Process Data (1998)Introduction to Time Series and Forecasting (2002)CUSUM Monitoring of First-Order Integer-Valued Autoregressive Processes of Poisson Counts (2009)Bridging the gap between theory and practice in basic statistical process monitoring (2016)Statistical Learning Methods Applied to Process Monitoring: An Overview and Perspective (2016)Design and Analysis of Experiments (2017)Artificial neural networks in applying MCUSUM residuals charts for AR(1) processes (2007)Economic design of Shewhart control charts for monitoring autocorrelated data with skip sampling strategies (2014)Application of Machine Learning in Statistical Process Control Charts: A Survey and Perspective (2021)
this work references cited by second hop

References

  • 1992A Multivariate Exponentially Weighted Moving Average Control Chart1,231 cited
  • 1999Research Issues and Ideas in Statistical Process Control631 cited
  • 1974The Effect of Serial Correlation on the Performance of CUSUM Tests275 cited
  • 1993Predicting Shifts in the Mean of a Multivariate Time Series Process: An Application in Predicting Business Failures141 cited
  • 2007SPC Procedures for Monitoring Autocorrelated Processes114 cited
  • 2004Multivariate Quality Control Chart for Autocorrelated Processes87 cited
  • 1997Ewma charts for multivariate time series70 cited
  • 2005Effect of Autocorrelation on Performance of the MCUSUM Control Chart66 cited
  • 2005Monitoring the cross-covariances of a multivariate time series32 cited

Cited by

  • 2025Integrating machine learning based EWMA control charts for multivariate process monitoring20 cited
  • 2024Machine learning based parameter-free adaptive EWMA control chart to monitor process dispersion16 cited

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