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Mohsen Ebadi, Shojaeddin Chenouri, Dennis K. J. Lin & Stefan H. Steiner. (2022) Statistical monitoring of the covariance matrix in multivariate processes: A literature review. Journal of Quality Technology 54:3, pages 269-289.
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Hongying Jing, Jian Li & Kaizong Bai. (2022) Directional monitoring and diagnosis for covariance matrices. Journal of Applied Statistics 49:6, pages 1449-1464.
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Jimoh Olawale Ajadi, Zezhong Wang & Inez Maria Zwetsloot. (2021) A review of dispersion control charts for multivariate individual observations. Quality Engineering 33:1, pages 60-75.
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Konstantinos A. Tasias & George Nenes. (2020) Monitoring location and scale of multivariate processes subject to a multiplicity of assignable causes. Quality Technology & Quantitative Management 17:5, pages 592-608.
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Georgios Bartzis & Sotirios Bersimis. (2020) Performance comparisons of bivariate dispersion control charts. Communications in Statistics: Case Studies, Data Analysis and Applications 6:1, pages 69-85.
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Sueli A. Mingoti & Letícia P. Pinto. (2019) Step-Down diagnostic analysis for monitoring the covariance matrix of bivariate normal processes. Communications in Statistics - Simulation and Computation 48:9, pages 2615-2624.
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Galal M. Abdella, Jinho Kim, Sangahn Kim, Khalifa N. Al-Khalifa, Myong K. (MK) Jeong, Abdel Magid Hamouda & Elsayed A. Elsayed. (2019) An adaptive thresholding-based process variability monitoring. Journal of Quality Technology 51:3, pages 242-256.
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Nadeera Gnan Tilshan Gunaratne, Malihe Akhavan Abdollahian, Shamsul Huda & John Yearwood. (2017) Exponentially weighted control charts to monitor multivariate process variability for high dimensions. International Journal of Production Research 55:17, pages 4948-4962.
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K.P. Tran, P. Castagliola & G. Celano. (2016) Monitoring the ratio of two normal variables using Run Rules type control charts. International Journal of Production Research 54:6, pages 1670-1688.
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Aamir Saghir. (2015) The bivariate dispersion control charts for non-normal processes. International Journal of Production Research 53:7, pages 1964-1979.
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Xiaobei Shen, Fugee Tsung & Changliang Zou. (2014) A new multivariate EWMA scheme for monitoring covariance matrices. International Journal of Production Research 52:10, pages 2834-2850.
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WilliamH. Woodall. (2014) Discussion of “Latent Structures-Based Multivariate Statistical Process Control: A Paradigm Shift”. Quality Engineering 26:1, pages 92-95.
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William H. Woodall & Douglas C. Montgomery. (2014) Some Current Directions in the Theory and Application of Statistical Process Monitoring. Journal of Quality Technology 46:1, pages 78-94.
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Zhonghua Li, Changliang Zou, Zhaojun Wang & Longcheen Huwang. (2013) A Multivariate Sign Chart for Monitoring Process Shape Parameters. Journal of Quality Technology 45:2, pages 149-165.
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Bo Li, Kaibo Wang & ArthurB. Yeh. (2013) Monitoring the covariance matrix via penalized likelihood estimation. IIE Transactions 45:2, pages 132-146.
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MatthiasH. Y. Tan & Jianjun Shi. (2012) A Bayesian Approach for Interpreting Mean Shifts in Multivariate Quality Control. Technometrics 54:3, pages 294-307.
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Roberto Quinino, A. Costa & Linda Lee Ho. (2012) A Single Statistic for Monitoring the Covariance Matrix of Bivariate Processes. Quality Engineering 24:3, pages 423-430.
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Yanting Li & Fugee Tsung. (2011) Detecting and diagnosing covariance matrix changes in multistage processes. IIE Transactions 43:4, pages 259-274.
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MarionR. Reynolds$suffix/text()$suffix/text() & Gyo-Young Cho. (2011) Multivariate Control Charts for Monitoring the Mean Vector and Covariance Matrix with Variable Sampling Intervals. Sequential Analysis 30:1, pages 1-40.
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Robert L. Mason, Youn-Min Chou & John C. Young. (2010) Decomposition of Scatter Ratios Used in Monitoring Multivariate Process Variability. Communications in Statistics - Theory and Methods 39:12, pages 2128-2145.
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Muhammad Riaz & Aamir Saghir. (2009) A mean deviation-based approach to monitor process variability. Journal of Statistical Computation and Simulation 79:10, pages 1173-1193.
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WilliamH. Woodall. (2009) Discussion on “Optimal Sequential Surveillance for Finance, Public Health, and Other Areas” by Marianne Frisén. Sequential Analysis 28:3, pages 338-341.
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RobertL. Mason, Youn-Min Chou & JohnC. Young. (2009) Monitoring Variation in a Multivariate Process When the Dimension is Large Relative to the Sample Size. Communications in Statistics - Theory and Methods 38:6, pages 939-951.
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Guoxi Zhang & Shing I. Chang. (2008) Multivariate EWMA control charts using individual observations for process mean and variance monitoring and diagnosis. International Journal of Production Research 46:24, pages 6855-6881.
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Muhammad Riaz & RonaldJ. M. M. Does. (2008) An Alternative to the Bivariate Control Chart for Process Dispersion. Quality Engineering 21:1, pages 63-71.
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AntonioF. B. Costa & MarcelaA. G. Machado. (2008) A New Chart for Monitoring the Covariance Matrix of Bivariate Processes. Communications in Statistics - Simulation and Computation 37:7, pages 1453-1465.
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Peihua Qiu. (2008) Distribution-free multivariate process control based on log-linear modeling. IIE Transactions 40:7, pages 664-677.
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Longcheen Huwang, Arthur B. Yeh & Chien-Wei Wu. (2007) Monitoring Multivariate Process Variability for Individual Observations. Journal of Quality Technology 39:3, pages 258-278.
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