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Statistical inference on accelerated life testing with dependent competing failure model under progressively type‐II censored data based on copula theory
Author(s) -
Wang Ying,
Yan Zaizai
Publication year - 2021
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.2803
Subject(s) - copula (linguistics) , bivariate analysis , censoring (clinical trials) , accelerated life testing , confidence interval , statistics , mathematics , inference , statistical inference , econometrics , bivariate data , likelihood function , maximum likelihood , computer science , weibull distribution , artificial intelligence
In this paper, we discuss the statistical analysis of a constant‐stress accelerated dependent competing failure model under progressively type‐II censoring based on a copula function. The dependence structure of lifetimes is constructed when the copula is a bivariate Clayton copula. The maximum likelihood estimations (MLEs) of the model parameters are derived. We also get the coverage probability of the 95% confidence intervals of the parameters based on MLEs and bootstrap confidence intervals. Finally, a real data set of some insulation system for electric motors was demonstrated for illustrative purpose.