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Communications in Statistics - Simulation and Computation Volume 28, 1999 - Issue 4
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Original Articles

Power comparisons for a hotelling's t2 STATISTIC

Youn‐Min Chou Division of Mathematics and Statistics, The University of Texas at San Antonio, 6900 North Loop 1604 West, San Antonio, TX 78249-0664
,
Robert L. Mason Statistical Analysis Section, Southwest Research Institutea, San Antonio, TX 78228-0510
&
John C. Young Department of Mathematics, McNeese State University, Lake Charles, LA 70609-2340
Pages 1031-1050 | Received 01 Aug 1998, Published online: 27 Jun 2007

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Xiaosong Wu, Rui Miao, Zefeng Li, Jie Ren, Jie Zhang, Zhibin Jiang & Xuening Chu. (2015) Process monitoring research with various estimator-based MEWMA control charts. International Journal of Production Research 53:14, pages 4337-4350.
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Shui-Pin Lee, An-Kuo Chao, Fugee Tsung, David Shan Hill Wong, Sheng-Tsiang Tseng & Shi-Shang Jang. (2011) Monitoring Batch Processes with Multiple On–Off Steps in Semiconductor Manufacturing. Journal of Quality Technology 43:2, pages 142-157.
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RobertL. Mason, Youn-Min Chou & JohnC. Young. (2008) Identifying Variables Contributing to Outliers in Phase I. Communications in Statistics - Theory and Methods 37:7, pages 1103-1118.
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James D. Williams, William H. Woodall, Jeffrey B. Birch & Joe H. Sullivan. (2006) Distribution of Hotelling's T2 Statistic Based on the Successive Differences Estimator. Journal of Quality Technology 38:3, pages 217-229.
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Robert L. Mason, Youn-Min Chou, Joe H. Sullivan, Zachary G. Stoumbos & John C. Young. (2003) Systematic Patterns in T2 Charts. Journal of Quality Technology 35:1, pages 47-58.
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Robert L. Mason, Youn-Min Chou & John C. Young. (2001) Applying Hotelling's T2 Statistic to Batch Processes. Journal of Quality Technology 33:4, pages 466-479.
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Youn-Min Chou, Robert L. Mason & John C. Young. (2001) THE CONTROL CHART FOR INDIVIDUAL OBSERVATIONS FROM A MULTIVARIATE NON-NORMAL DISTRIBUTION. Communications in Statistics - Theory and Methods 30:8-9, pages 1937-1949.
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Amzar Omairi & Zool Hilmi Ismail. (2021) Towards Machine Learning for Error Compensation in Additive Manufacturing. Applied Sciences 11:5, pages 2375.
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Muhammad Ahsan, Muhammad Mashuri, Hidayatul Khusna & Wibawati. Bootstrap based T2 chart with hybrid James Stein and SDCM for network anomaly detection. Bootstrap based T2 chart with hybrid James Stein and SDCM for network anomaly detection.
Muhammad Ahsan, Muhammad Mashuri, Muhammad Hisyam Lee, Heri Kuswanto & Dedy Dwi Prastyo. (2020) Robust adaptive multivariate Hotelling's T2 control chart based on kernel density estimation for intrusion detection system. Expert Systems with Applications 145, pages 113105.
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Qun-Xiong Zhu, Yi Luo & Yan-Lin He. (2019) Novel Distributed Alarm Visual Analysis Using Multicorrelation Block-Based PLS and Its Application to Online Root Cause Analysis. Industrial & Engineering Chemistry Research 58:45, pages 20655-20666.
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Luis Alberto Pargas Carmona. A Graphical Approach for Interpreting Out-of-Control Signals in Multivariate Control Charts. A Graphical Approach for Interpreting Out-of-Control Signals in Multivariate Control Charts.
Muhammad Ahsan, Muhammad Mashuri, Heri Kuswanto, Dedy Dwi Prastyo & Hidayatul Khusna. (2018) T 2 Control Chart based on Successive Difference Covariance Matrix for Intrusion Detection System . Journal of Physics: Conference Series 1028, pages 012220.
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Insha Ullah, Matthew D.M. Pawley, Adam N.H. Smith & Beatrix Jones. (2017) Improving the detection of unusual observations in high‐dimensional settings. Australian & New Zealand Journal of Statistics 59:4, pages 449-462.
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Piotr Porwik, Rafal Doroz & Tomasz Orczyk. (2014) The k-NN classifier and self-adaptive Hotelling data reduction technique in handwritten signatures recognition. Pattern Analysis and Applications 18:4, pages 983-1001.
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Aneetha Avalappampatty Sivasamy & Bose Sundan. (2015) A Dynamic Intrusion Detection System Based on Multivariate Hotelling’s T 2 Statistics Approach for Network Environments . The Scientific World Journal 2015, pages 1-9.
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Ziyaur Rahman, Akhtar Siddiqui, Srikant Bykadi & Mansoor A. Khan. (2014) Determination of tacrolimus crystalline fraction in the commercial immediate release amorphous solid dispersion products by a standardized X-ray powder diffraction method with chemometrics. International Journal of Pharmaceutics 475:1-2, pages 462-470.
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James D. Williams. 2011. Statistical Analysis of Profile Monitoring. Statistical Analysis of Profile Monitoring 129 156 .
Xiao Hu, Raj Subbu, Piero Bonissone, Hai Qiu & Naresh Iyer. (2008) Multivariate anomaly detection in real-world industrial systems. Multivariate anomaly detection in real-world industrial systems.
James D. Williams, William H. Woodall & Jeffrey B. Birch. (2007) Statistical monitoring of nonlinear product and process quality profiles. Quality and Reliability Engineering International 23:8, pages 925-941.
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Xiao Hu, Hai Qiu & Naresh Iyer. (2007) Multivariate change detection for time series data in aircraft engine fault diagnostics. Multivariate change detection for time series data in aircraft engine fault diagnostics.
S. Bersimis, S. Psarakis & J. Panaretos. (2006) Multivariate statistical process control charts: an overview. Quality and Reliability Engineering International 23:5, pages 517-543.
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Nong Ye, Darshit Parmar & Connie M. Borror. (2005) A Hybrid SPC Method with the Chi‐Square Distance Monitoring Procedure for Large‐scale, Complex Process Data. Quality and Reliability Engineering International 22:4, pages 393-402.
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Nong Ye, Connie M. Borror & Darshit Parmar. (2003) Scalable Chi‐Square Distance versus Conventional Statistical Distance for Process Monitoring with Uncorrelated Data Variables. Quality and Reliability Engineering International 19:6, pages 505-515.
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N. Ye, S.M. Emran, Q. Chen & S. Vilbert. (2002) Multivariate statistical analysis of audit trails for host-based intrusion detection. IEEE Transactions on Computers 51:7, pages 810-820.
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M Xie, T N Goh & V KuralmaniM. Xie, T. N. Goh & V. Kuralmani. 2002. Statistical Models and Control Charts for High-Quality Processes. Statistical Models and Control Charts for High-Quality Processes 237 261 .

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