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JSRI 2017, 13(2): 181-195 Back to browse issues page
Bayesian Estimation of Parameters in the Exponentiated Gumbel Distribution
Gholamhossein Gholami *
Abstract:   (354 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.

Keywords: Bayesian inference, exponentiated distributions, Gumbel distribution, Gibbs Sampler, Monte Carlo Markov Chain (MCMC) method, Metropolis-Hastings algorithm.
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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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DOI: 10.18869/acadpub.jsri.13.2.181

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Gholami G. Bayesian Estimation of Parameters in the Exponentiated Gumbel Distribution. JSRI. 2017; 13 (2) :181-195
URL: http://jsri.srtc.ac.ir/article-1-236-en.html
Volume 13, Number 2 (3-2017) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران (علمی - پژوهشی) Journal of Statistical Research of Iran JSRI
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