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

Lawrence M. Leemis ()
Additional contact information
Lawrence M. Leemis: The College of William and Mary

Chapter 15 in Computational Probability Applications, 2017, pp 217-237 from Springer

Abstract: 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.

Keywords: Beta distribution; Binomial confidence interval; Coherent system; Computer algebra system (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-43317-2_15

Ordering information: This item can be ordered from
http://www.springer.com/9783319433172

DOI: 10.1007/978-3-319-43317-2_15

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().