Parameter estimations of geometric extreme exponential distribution based on dual generalized order statistics

Chansoo Kim, Young Han Bae, Woosuk Kim

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, we consider the maximum likelihood and Bayes esti-mation of the parameters of geometric extreme exponential distribution based on dual generalized order statistics. However, the Bayes esti-mator does not exist in an explicit form for the parameters. We usedan approximation based on Lindley method for obtaining Bayes esti-mates under squared error loss function. We also discuss the asymptotic variance-covariance matrix of maximum likelihood estimators of two pa-rameters. Through Monte Carlo simulation, we compare the maximum likelihood and Bayes estimates of the parameters. And we include one real data analysis.

Original languageEnglish (US)
Pages (from-to)3173-3185
Number of pages13
JournalApplied Mathematical Sciences
Volume10
Issue number61-64
DOIs
StatePublished - Jan 1 2016

All Science Journal Classification (ASJC) codes

  • Applied Mathematics

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