信息先验条件下用贝叶斯分析估计形状已知的Frechet分布

Wajiha Nasir
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引用次数: 0

摘要

本研究采用贝叶斯分析对Frechet分布进行了研究。后验分布是用gamma和指数推导出来的。使用五种不同的损失函数推导了贝叶斯估计量及其后验风险。超参数的推导是通过使用先验预测分布完成的。对后验分布的行为进行了仿真研究。其中拟二次损失函数和指数先验较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On estimation of Frechet distribution with known shape using Bayesian analysis under informative priors
In this study, Frechet distribution has been studied by using Bayesian analysis. Posterior distribution has been derived by using gamma and exponential. Bayes estimators and their posterior risks has been derived using five different loss functions. Elicitation of hyperparameters has been done by using prior predictive distributions. Simulation study is carried out to study the behavior of posterior distribution. Quasi quadratic loss function and exponential prior are found better among all.
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