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On Non‐parametric Estimation of the Survival Function with Competing Risks

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  • Paul H. Kvam
  • Harshinder Singh

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.

Suggested Citation

  • Paul H. Kvam & Harshinder Singh, 2001. "On Non‐parametric Estimation of the Survival Function with Competing Risks," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(4), pages 715-724, December.
  • Handle: RePEc:bla:scjsta:v:28:y:2001:i:4:p:715-724
    DOI: 10.1111/1467-9469.00264
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    Cited by:

    1. Coolen-Maturi, Tahani, 2014. "Nonparametric predictive pairwise comparison with competing risks," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 146-153.

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