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Bayesian Estimation of Parameters in the Exponentiated Gumbel Distribution
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Gholamhossein Gholami   |
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Abstract: (3792 Views) |
Abstract: The Exponentiated Gumbel (EG) distribution has been proposed to capture some aspects of the data that the Gumbel distribution fails to specify. In this paper, we estimate the EG's parameters in the Bayesian framework. We consider a 2-level hierarchical structure for prior distribution. As the posterior distributions do not admit a closed form, we do an approximated inference by using Gibbs and Metropolis-Hastings algorithm.
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| Keywords: Bayesian inference, exponentiated distributions, Gumbel distribution, Gibbs Sampler, Monte Carlo Markov Chain (MCMC) method, Metropolis-Hastings algorithm. |
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Full-Text [PDF 3396 kb]
(2524 Downloads)
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Type of Study: Research |
Subject:
General
Received: 2016/04/28 | Accepted: 2017/04/8 | Published: 2017/06/11
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