Robust online detection on highly censored data using a semi-parametric EWMA chart-Reference-Cited by-同舟云学术

Robust online detection on highly censored data using a semi-parametric EWMA chart

Published:2022-11-11 Issue: Volume: Page:1-17
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Yu Miaomiao¹,Zhao Wei²,Zhou Yong¹,Wu Chunjie³

Affiliation:

1. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics and Academy of Statistics and Interdisciplinary Sciences, East China Normal University, Shanghai, People's Republic of China

2. Department of Industrial Engineering, Tsinghua University, Beijing, People's Republic of China

3. School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, People's Republic of China

Funder

National Key R&D Program of China

State Key Program of National Natural Science Foundation of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

National Bureau of Statistics of China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2022.2139379

Reference35 articles.

1. Some Current Directions in the Theory and Application of Statistical Process Monitoring

2. Effect of Hydrocortisone on Development of Shock Among Patients With Severe Sepsis

3. Financial development and deployment of renewable energy technologies

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On Aggregation of Uncensored and Censored Observations;Mathematical Methods of Statistics;2024-06

2. Monitoring gamma type-I censored data using an exponentially weighted moving average control chart based on deep learning networks;Scientific Reports;2024-03-18

3. Residual Control Chart Based on a Convolutional Neural Network and Support Vector Regression for Type-I Censored Data with the Weibull Model;Mathematics;2023-12-25