On Non-parametric Estimation of the Survival Function with Competing Risks |
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Authors: | Paul H. Kvam,& Harshinder Singh |
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Affiliation: | Georgia Institute of Technology,;Panjab University, Chandigarh |
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Abstract: | The non-parametric maximum likelihood estimators (MLEs) are derived for survival functions associated with individual risks or system components in a reliability framework. Lifetimes are observed for systems that contain one or more of those components. Analogous to a competing risks model, the system is assumed to fail upon the first instance of any component failure; i.e. the system is configured in series. For any given risk or component type, the asymptotic distribution is shown to depend explicitly on the unknown survival function of the other risks, as well as the censoring distribution. Survival functions with increasing failure rate are investigated as a special case. The order restricted MLE is shown to be consistent under mild assumptions of the underlying component lifetime distributions. |
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Keywords: | censoring Gaussian process increasing failure rate isotonic regression series system |
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