[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: 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:   (1686 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]   (551 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/04/28 | Accepted: 2017/04/8 | Published: 2017/06/11
Add your comments about this article
Your username or Email:


XML   Persian Abstract   Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

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, Issue 2 (3-2017) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران (علمی - پژوهشی) Journal of Statistical Research of Iran JSRI
Persian site map - English site map - Created in 0.05 seconds with 32 queries by YEKTAWEB 3903