三种不同损失函数下Pareto分布可靠性函数的Bayes估计

IF 0.9 Q3 STATISTICS & PROBABILITY
Gaurav Shukla, U. Chandra, Vinod Kumar
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引用次数: 0

摘要

本文给出了Pareto分布形状参数的Bayes估计量以及SELF、QLF和APLF损失函数下的可靠性函数。为了更好地理解贝叶斯方法,我们将杰弗里先验视为非信息先验,将指数先验和伽马先验视为信息先验。将该估计量与极大似然估计量(MLE)和一致最小方差无偏估计量(UMVUE)进行了比较。此外,本文还推导了这三种损失函数下的风险函数表达式。用实际和模拟数据集对所得结果进行了说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayes Estimation of the Reliability Function of Pareto Distribution Under Three Different Loss Functions
In this paper, we have proposed Bayes estimators of shape parameter of Pareto distribution as well as reliability function under SELF, QLF and APLF loss functions. For better understanding of Bayesian approach, we consider Jeffrey’s prior as non-informative prior, exponential and gamma priors as informative priors. The proposed estimators have been compared with Maximum likelihood estimator (MLE) and the uniformly minimum variance unbiased estimator (UMVUE). Moreover, the current study also derives the expressions for risk function under these three loss functions. The results obtained have been illustrated with the real as well as simulated data set.
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来源期刊
CiteScore
1.60
自引率
12.50%
发文量
24
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