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Analysis of generalized progressive hybrid censored competing risks data
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 Title & Authors
Analysis of generalized progressive hybrid censored competing risks data
Lee, Kyeong-Jun; Lee, Jae-Ik; Park, Chan-Keun;
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 Abstract
In reliability analysis, it is quite common for the failure of any individual or item to be attributable to more than one cause. Moreover, observed data are often censored. Recently, progressive hybrid censoring schemes have become quite popular in life-testing problems and reliability analysis. However, a limitation of the progressive hybrid censoring scheme is that it cannot be applied when few failures occur before time T. Therefore, generalized progressive hybrid censoring schemes have been introduced. In this article, we derive the likelihood inference of the unknown parameters under the assumptions that the lifetime distributions of different causes are independent and exponentially distributed. We obtain the maximum likelihood estimators of the unknown parameters in exact forms. Asymptotic confidence intervals are also proposed. Bayes estimates and credible intervals of the unknown parameters are obtained under the assumption of gamma priors on the unknown parameters. Different methods are compared using Monte Carlo simulations. One real data set is analyzed for illustrative purposes.
 Keywords
Bayes estimate;Competing risk;Exponential distribution;Generalized progressive hybrid censoring;Maximum likelihood estimator;
 Language
English
 Cited by
 References
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