Using Different Loss Function to Estimate the Parameters of Birnbaum-Saunders Distribution by Bayesian Method with Application

Hussain Bashar, Ahmed Salih
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Abstract

The Birnbaum-Saunders distribution is one of the most important distributions that explain fatigue time in general, as it has many engineering and industrial applications. In our Paper we introduce three estimation methods to estimate the parameters of Birnbaum-Saunders parameters, first is the Maximum Likelihood Estimator MLE and second, is Bayes estimation with quadratic loss function BQ and last is the Bayes estimator with weighted loss function BW. simulated data were used as well as real data used which represented by the fatigue time of a concrete block under pressure before its final collapse. It was concluded that the Bayes estimator with squared loss function BQ is the best.
用贝叶斯方法用不同损失函数估计Birnbaum-Saunders分布参数及其应用
Birnbaum-Saunders分布是解释疲劳时间的最重要的分布之一,因为它有许多工程和工业应用。本文介绍了三种估计Birnbaum-Saunders参数的方法,第一种是极大似然估计MLE,第二种是二次损失函数BQ的贝叶斯估计,最后一种是加权损失函数BW的贝叶斯估计。采用了模拟数据和实际数据,这些数据代表了混凝土块体在压力下最终坍塌前的疲劳时间。结果表明,具有平方损失函数BQ的贝叶斯估计是最好的估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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