两种先验下两参数逆Kum分布参数的Bayes分析OA
Bayesian analysis of parameters of the two-parameter inverse Kumaraswamy distribution under two different priors
在加权p、q对称熵损失函数下,利用Bayes估计方法,得到了该参数Bayes估计的一般形式和精确形式,证明了所得Bayes估计的可容许性以及最小最大性.然后给出了该参数的多层Bayes估计、E-Bayes估计和刀切Bayes估计.最后运用R程序结合所得估计进行了数值模拟,结果表明:在Jeffreys先验下的Bayes估计比共轭先验分布下的Bayes估计精度更高;E-Bayes估计能降低超参数对模拟的影响.
Under the weighted p and q symmetric entropy loss functions,the general and exact form of Bayesian estimation for this parameter are obtained by using the Bayesian estimation method,which proves the acceptability and minimaxity of the obtained Bayesian estimation.Finally,the numerical simulation is carried out by the R program combined with the obtained estimates,and the results show that the Bayes estimation under the Jeffreys prior is more accurate than the Bayesian estimation under the conjugate prior distribution.E-Bayes estimation can reduce the influence of hyperparameters on the simulation.
张学成;徐宝
吉林师范大学数学与计算机学院,吉林,四平 136000吉林师范大学数学与计算机学院,吉林,四平 136000
数理科学
逆Kum分布损失函数Bayes估计可容许性MCMC算法
inverse Kumaraswamy distributionloss functionBayesian estimationadmissibilityMCMC algorithm
《井冈山大学学报（自然科学版）》 2026 (2)
9-17,9
国家自然科学基金项目(11571138)吉林省科技发展计划项目(YDZJ202201ZYTS622)
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