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Growing Science » International Journal of Industrial Engineering Computations » Generalized exponential distribution: A Bayesian approach using MCMC methods

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 6 Issue 1 pp. 1-14 , 2015

Generalized exponential distribution: A Bayesian approach using MCMC methods Pages 1-14 Right click to download the paper Download PDF

Authors: Jorge Alberto Achcar, Fernando Antonio Moala, Juliana Boleta

DOI: 10.5267/j.ijiec.2014.8.002

Keywords: Bayesian analysis, Generalized exponential distribution, MCMC methods, Non-informative priors

Abstract: The generalized exponential distribution could be a good option to analyse lifetime data, as an alternative for the use of standard existing lifetime distributions as exponential, Weibull or gamma distributions. Assuming different non-informative prior distributions for the parameters of the model, we introduce a Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. Some numerical illustrations considering simulated and real lifetime data are presented to illustrate the proposed methodology, especially the effects of different priors on the posterior summaries of interest.

How to cite this paper
Achcar, J., Moala, F & Boleta, J. (2015). Generalized exponential distribution: A Bayesian approach using MCMC methods.International Journal of Industrial Engineering Computations , 6(1), 1-14.

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Journal: International Journal of Industrial Engineering Computations | Year: 2015 | Volume: 6 | Issue: 1 | Views: 2714 | Reviews: 0

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