:: Volume 13, Issue 2 (3-2017) ::
JSRI 2017, 13(2): 181-195 Back to browse issues page
Bayesian Estimation of Parameters in the Exponentiated Gumbel Distribution
Gholamhossein Gholami *
Abstract:   (3195 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.
Full-Text [PDF 3396 kb]   (1430 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/04/28 | Accepted: 2017/04/8 | Published: 2017/06/11

XML   Persian Abstract   Print

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 13, Issue 2 (3-2017) Back to browse issues page