Reliability Inference for a Copula-Based Series System Life Test under Multiple Type-I Censoring

Tsung Ming Hsu, Takeshi Emura, Tsai Hung Fan

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

In this paper, we consider a multiple Type-I censored life test of series systems in which each component's lifetime belongs to the log-location-scale family of distributions with dependence. The dependence among lifetimes of components is generated by the Clayton copula with unknown copula parameter. We obtain the maximum likelihood estimates of the underlying parameters via EM algorithm under masked data and derive the Fisher information via missing information principle. The effect due to misspecification by independent models is investigated through the percentiles estimation of both the system's and components' failure time distributions by simulation study as well as a real data example.

Original languageEnglish
Article number7393618
Pages (from-to)1069-1080
Number of pages12
JournalIEEE Transactions on Reliability
Volume65
Issue number2
DOIs
StatePublished - Jun 2016

Keywords

  • Clayton copula
  • EM algorithm
  • Type-I censoring
  • log-location-scale family
  • masked data
  • missing information principle
  • series system

Fingerprint

Dive into the research topics of 'Reliability Inference for a Copula-Based Series System Life Test under Multiple Type-I Censoring'. Together they form a unique fingerprint.

Cite this