Empirical Bayes Risk Evaluation With Type II Censored Data

Research output: Contribution to journalArticle

Abstract

Empirical Bayes estimators for the scale parameter in a Weibull, Raleigh or an exponential distribution with type II censored data are developed. These estimators are derived by matching moment method, the maximum likelihood method and by modifying the geometric mean estimators developed by Dey and Kuo (1991). The empirical Bayes risks for these estimators and the Bayes rules are evaluated by extensive simulation. Often, the moment empirical Bayes estimator has the smallest empirical Bayes risk. The cases where the modified geometric mean estimator has the smallest empirical Bayes risk are also identified. We also obtain the empirical Bayes risk comparisons for various empirical Bayes estimators when one of the parameters in the hyperprior is known.

Original languageEnglish (US)
Pages (from-to)195-206
Number of pages12
JournalJournal of Statistical Computation and Simulation
Volume48
Issue number3-4
DOIs
StatePublished - Dec 1 1993
Externally publishedYes

Keywords

  • EB risk comparison
  • Geometric mean estimator
  • ML-II prior
  • Matching moment method
  • Parametric empirical Bayes estimation
  • Type II censored data

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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