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Lower Confidence Bounds for System Reliability from Binary Failure Data Using Bootstrapping

In: Computational Probability Applications

Author

Listed:
  • Lawrence M. Leemis

    (The College of William and Mary)

Abstract

Binary failure data are collected for each of the independent components in a coherent system. Bootstrapping is used to determine a (1 −α)100 % lower confidence bound on the system reliability. When a component with perfect test results is encountered, a beta prior distribution is used to avoid an overly optimistic lower bound.

Suggested Citation

  • Lawrence M. Leemis, 2017. "Lower Confidence Bounds for System Reliability from Binary Failure Data Using Bootstrapping," International Series in Operations Research & Management Science, in: Andrew G. Glen & Lawrence M. Leemis (ed.), Computational Probability Applications, chapter 15, pages 217-237, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-43317-2_15
    DOI: 10.1007/978-3-319-43317-2_15
    as

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