Nonparametric model checking for k-out-of-n systems

E.A. Beutner*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

24 Citations (Web of Science)


It is an important problem in reliability analysis to decide whether for a given k-out-of-n system the static or the sequential k-out-of-n model is appropriate. Often components are redundantly added to a system to protect against failure of the system. If the failure of any component of the system induces a higher rate of failure of the remaining components due to increased load, the sequential k-out-of-n model is appropriate. The increase of the failure rate of the remaining components after a failure of some component implies that the effects of the component redundancy are diminished. On the other hand, if all the components have the same failure distribution and whenever a failure occurs, the remaining components are not affected, the static k-out-of-n model is adequate. In this paper. we consider nonparametric hypothesis tests to make a decision between these two models. We analyze test statistics based on the profile score process as well as test statistics based on a multivariate intensity ratio and derive their asymptotic distribution. Finally, we compare the different test statistics. 

Original languageEnglish
Pages (from-to)626-639
Number of pages14
JournalJournal of Statistical Planning and Inference
Issue number3
Publication statusPublished - Mar 2010


  • Hypothesis testing
  • Multivariate intensity ratio
  • k-out-of-n model
  • Profile score process
  • Sequential k-out-of-n model
  • Static k-out-of-n model

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