Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics

In this paper, the confidence intervals for the generalized gamma distribution parameters are derived based on the Bayesian approach using the informative and non-informative priors and the classical approach, via the Asymptotic Maximum likelihood estimation, based on the generalized order statistic...

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Main Authors: M. Maswadah, Ali M. Seham, M. Ahsanullah
Format: Article
Language:English
Published: Springer 2013-12-01
Series:Journal of Statistical Theory and Applications (JSTA)
Subjects:
Online Access:https://www.atlantis-press.com/article/11326.pdf
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author M. Maswadah
Ali M. Seham
M. Ahsanullah
author_facet M. Maswadah
Ali M. Seham
M. Ahsanullah
author_sort M. Maswadah
collection DOAJ
description In this paper, the confidence intervals for the generalized gamma distribution parameters are derived based on the Bayesian approach using the informative and non-informative priors and the classical approach, via the Asymptotic Maximum likelihood estimation, based on the generalized order statistics. For measuring the performance of the Bayesian approach comparing to the classical approach, the confidence intervals of the unknown parameters have been studied, via Monte Carlo simulations and some real data. The simulation results indicated that the confidence intervals based on the Bayesian approach compete and outperform those based on the classical approach.
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spelling doaj.art-c074c03c2da5442b87394a3c78becbad2022-12-22T02:26:14ZengSpringerJournal of Statistical Theory and Applications (JSTA)1538-78872013-12-0112410.2991/jsta.2013.12.4.4Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order StatisticsM. MaswadahAli M. SehamM. AhsanullahIn this paper, the confidence intervals for the generalized gamma distribution parameters are derived based on the Bayesian approach using the informative and non-informative priors and the classical approach, via the Asymptotic Maximum likelihood estimation, based on the generalized order statistics. For measuring the performance of the Bayesian approach comparing to the classical approach, the confidence intervals of the unknown parameters have been studied, via Monte Carlo simulations and some real data. The simulation results indicated that the confidence intervals based on the Bayesian approach compete and outperform those based on the classical approach.https://www.atlantis-press.com/article/11326.pdfGeneralized gamma distribution; Generalized order statistics; Asymptotic maximum likelihood estimation; Bayesian inference
spellingShingle M. Maswadah
Ali M. Seham
M. Ahsanullah
Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics
Journal of Statistical Theory and Applications (JSTA)
Generalized gamma distribution; Generalized order statistics; Asymptotic maximum likelihood estimation; Bayesian inference
title Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics
title_full Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics
title_fullStr Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics
title_full_unstemmed Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics
title_short Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics
title_sort bayesian inference on the generalized gamma distribution based on generalized order statistics
topic Generalized gamma distribution; Generalized order statistics; Asymptotic maximum likelihood estimation; Bayesian inference
url https://www.atlantis-press.com/article/11326.pdf
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AT alimseham bayesianinferenceonthegeneralizedgammadistributionbasedongeneralizedorderstatistics
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