Bayesian estimation of gumbel type-ii distribution

Kamran Abbas, Jiayu Fu, Yincai Tang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this paper we consider the Bayesian estimators for the unknown parameters of Gumbel type-II distribution. The Bayesian estimators cannot be obtained in closed forms. Approximate Bayesian estimators are computed using the idea of Lindley's approximation under different loss functions. The approximate Bayes estimates obtained under the assumption of non-informative priors are compared with their maximum likelihood counterparts using Monte Carlo simulation. A real data set is analyzed for illustrative purpose.

Original languageEnglish
Pages (from-to)33-46
Number of pages14
JournalData Science Journal
Volume12
DOIs
StatePublished - 10 Aug 2013

Keywords

  • Bayesian estimator
  • Gumbel type-II distribution
  • Lindley's approximation
  • Maximum likelihood estimator
  • Monte Carlo simulation

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