一种对称损失函数下逆指数分布参数的刀切Bayes估计  

Bayes estimation of inverse exponential distribution parameters under a symmetric loss function

作　　者：关爽 徐宝[1] GUAN Shuang;XU Bao(School of Mathematics and Computer,Jilin Normal University,Siping,Jilin 136000,China)

机构地区：[1]吉林师范大学数学与计算机学院,吉林四平136000

出　　处：《内江师范学院学报》2025年第4期17-23,共7页Journal of Neijiang Normal University

基　　金：国家自然科学基金资助项目(11571138)。

摘　　要：在加权p,q对称熵损失函数下,研究逆指数分布参数的Bayes估计的形式及其性质.首先,研究逆指数分布参数Bayes估计的一般形式以及在先验分布为逆伽马分布下的精确形式,证明了所得Bayes估计具有可容许性和最小最大性.其次,研究了逆指数分布参数的刀切Bayes估计.最后,通过模拟研究了所得估计的精确性.结果表明,基于适当的加权p,q对称损失函数得出的Bayes估计精确性较高.Under the weighted p-q symmetric entropy loss function,the form and properties of Bayes estimation of inverse exponential distribution parameters are studied.Firstly,the general form of Bayes estimation of inverse exponential distribution parameters is studied,as well as the exact form under the prior distribution of inverse gamma distribution,And it was proved that the obtained Bayes estimation has tolerability and minimum maximum.Secondly,the knife cut Bayes estimation of the inverse exponential distribution parameters was studied.Finally,the accuracy of the obtained estimation was studied through simulation.The results showed that the Bayes estimation based on appropriate weighted p and q-symmetric loss functions had high accuracy.

关 键 词：逆指数分布 BAYES估计 损失函数 可容许性 最小最大性 

分 类 号：O212.8[理学—概率论与数理统计]