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Change detection in the Cox Proportional Hazards models from different reliability data
Author(s) -
Li Zhiguo,
Zhou Shiyu,
Sievenpiper Crispian,
Choubey Suresh
Publication year - 2010
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1132
Subject(s) - reliability (semiconductor) , proportional hazards model , reliability engineering , computer science , regression analysis , statistics , data mining , engineering , mathematics , power (physics) , physics , quantum mechanics
The Proportional Hazards (PH) model is an important type of failure time regression model which relates the occurrence probability of critical failures to influential factors. However, little research work has been done on detecting changes in the PH models fitted based on different sets of reliability data. This paper develops the methods for change detection in the Cox PH models, also known as Semiparametric PH model, for reliability prediction and/or assessment of the time‐to‐failure data collected from different subjects. The effectiveness of the developed methods is illustrated through numerical studies and real‐world data analysis. The developed technique possesses wide applicability to the systems and processes where the Cox PH model fits the reliability data well. Copyright © 2010 John Wiley & Sons, Ltd.