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

Chansoo Kim, Young Han Bae, Woosuk Kim

Research output: Contribution to journalArticle

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

Fingerprint

Generalized Order Statistics
Bayes
Exponential distribution
Parameter estimation
Maximum likelihood
Parameter Estimation
Extremes
Statistics
Squared Error Loss Function
Bayes Estimate
Variance-covariance Matrix
Asymptotic Variance
Covariance matrix
Maximum Likelihood Estimate
Maximum Likelihood Estimator
Maximum Likelihood
Data analysis
Monte Carlo Simulation
Approximation

All Science Journal Classification (ASJC) codes

  • Applied Mathematics

Cite this

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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.",
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Parameter estimations of geometric extreme exponential distribution based on dual generalized order statistics. / Kim, Chansoo; Bae, Young Han; Kim, Woosuk.

In: Applied Mathematical Sciences, Vol. 10, No. 61-64, 01.01.2016, p. 3173-3185.

Research output: Contribution to journalArticle

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