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Original Articles

A risk-adjusted EWMA chart with dynamic probability control limits for monitoring survival time

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Pages 1333-1354 | Received 17 May 2019, Accepted 09 Sep 2019, Published online: 24 Sep 2019

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Read on this site (4)

Navid Rafiei, Shervin Asadzadeh & Seyed Taghi Akhavan Niaki. (2023) Multi-objective design of risk-adjusted control chart in healthcare systems with economic and statistical considerations. Communications in Statistics - Simulation and Computation 52:7, pages 2967-2984.
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Faiza Asif, Muhammad Noor-ul-Amin & Afshan Riaz. (2022) Accelerated failure time model based risk adjusted MA-EWMA control chart. Communications in Statistics - Simulation and Computation 0:0, pages 1-11.
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Maryam Keshavarz, Shervin Asadzadeh & Seyed Taghi Akhavan Niaki. (2021) Risk-adjusted frailty-based CUSUM control chart for phase I monitoring of patients’ lifetime. Journal of Statistical Computation and Simulation 91:2, pages 334-352.
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Chia-Yen Lee, Kai Chang & Chien Ho. Autoencoder-based detector for distinguishing process anomaly and sensor failure. International Journal of Production Research 0:0, pages 1-16.
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Articles from other publishers (4)

Muhammad Noor-ul-Amin, Imad Khan, Ali Rashash R. Alzahrani, Amel Ayari-Akkari & Bakhtiyar Ahmad. (2024) Risk adjusted EWMA control chart based on support vector machine with application to cardiac surgery data. Scientific Reports 14:1.
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Longhui Li, Yanli Liu, Yanfen Shang & Zixian Liu. (2023) A new phase Ⅱ risk-adjusted CUSUM chart for monitoring surgical performance. Computers & Industrial Engineering 186, pages 109738.
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Daniel Gomon, Julie Sijmons, Hein Putter, Jan Willem Dekker, Rob Tollenaar, Michel Wouters, Pieter Tanis, Marta Fiocco & Mirko Signorelli. (2023) Inspecting the quality of care: a comparison of CUSUM methods for inter hospital performance. Health Services and Outcomes Research Methodology.
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Jing Wu. (2022) Multi Platform Public Opinion Risk Monitoring and Early Warning Algorithm Based on Multimodal Neural Network. Multi Platform Public Opinion Risk Monitoring and Early Warning Algorithm Based on Multimodal Neural Network.

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