Estimation in a Random Censoring Model with Incomplete Information: Exponential Lifetime Distribution

T. Elperin, I. Gertsbakh

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Analysis of methods and simulation results for estimating the exponential mean lifetime in a random censoring model with incomplete information are presented. The instant of an item#x2019;s failure is observed if it occurs before a randomly chosen inspection time and the failure was signalled. Otherwise, the experiment is terminated at the instant of inspection during which the true state of the item is discovered. The maximum likelihood method (MLM) is used to obtain point and interval estimates for item mean lifetime, for the exponential model. It is demonstrated, using Monte Carlo simulation, that MLM provides positively biased estimates for the mean lifetime and that the large sample approximation to the log-likelihood ratio produces rather accurate confidence intervals. The quality of the estimates is very little influenced by the value of the probability of failure-to-signal. Properties of the Fisher information in the censored sample are investigated theoretically and numerically.

Original languageEnglish
Pages (from-to)223-229
Number of pages7
JournalIEEE Transactions on Reliability
Volume37
Issue number2
DOIs
StatePublished - 1 Jan 1988

Keywords

  • Exponential distribution
  • Interval estimation
  • Maximum likelihood method
  • Point estimation
  • Random censoring

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Electrical and Electronic Engineering

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