Bayesian Estimation of Parameters in the Exponentiated Gumbel Distribution

Gholamhossein Gholami
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引用次数: 1

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.
指数Gumbel分布中参数的贝叶斯估计
幂次甘贝尔(EG)分布被提出用来捕捉甘贝尔分布无法指定的数据的某些方面。本文在贝叶斯框架下对EG的参数进行估计。我们考虑先验分布的2级层次结构。由于后验分布不承认封闭形式,我们使用Gibbs和Metropolis-Hastings算法进行近似推理。
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