Journal of Statistical Theory and Applications

Volume 12, Issue 4, December 2013, Pages 356 - 377

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

Authors
M. Maswadah, Ali M. Seham, M. Ahsanullah
Corresponding Author
M. Maswadah
Available Online 1 December 2013.
DOI
https://doi.org/10.2991/jsta.2013.12.4.4How to use a DOI?
Keywords
Generalized gamma distribution; Generalized order statistics; Asymptotic maximum likelihood estimation; Bayesian inference
Abstract
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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Journal
Journal of Statistical Theory and Applications
Volume-Issue
12 - 4
Pages
356 - 377
Publication Date
2013/12
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
https://doi.org/10.2991/jsta.2013.12.4.4How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - M. Maswadah
AU  - Ali M. Seham
AU  - M. Ahsanullah
PY  - 2013
DA  - 2013/12
TI  - Bayesian Inference on the Generalized Gamma Distribution Based on Generalized Order Statistics
JO  - Journal of Statistical Theory and Applications
SP  - 356
EP  - 377
VL  - 12
IS  - 4
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2013.12.4.4
DO  - https://doi.org/10.2991/jsta.2013.12.4.4
ID  - Maswadah2013
ER  -