Bayesian Estimation of Parameters in the Exponentiated Gumbel Distribution
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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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K. Fathi1∗, S.F. Bagheri2, M. Alizadeh3 ∗, M. Alizadeh4 Department of Statistics, North Branch, Islamic Azad University, Tehran, Iran 1 Department of Statistics, College of Basic Sciences, Yadegar-e-Imam Khomeini (RAH) Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran2 Branch of Mazandaran, Statistical Center of Iran3 Department of Mathematical since, University of Mazandaran, Mazandara...
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Journal title
volume 13 issue 2
pages 181- 195
publication date 2017-03
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