常家齐, 徐宝. 一种对称损失下艾拉姆咖分布参数的Bayes分析J. 内江师范学院学报, 2026, 41(2): 22-31. DOI: 10.13603/j.cnki.51-1621/z.2026.02.004
    引用本文: 常家齐, 徐宝. 一种对称损失下艾拉姆咖分布参数的Bayes分析J. 内江师范学院学报, 2026, 41(2): 22-31. DOI: 10.13603/j.cnki.51-1621/z.2026.02.004
    CHANG Jiaqi, XU Bao. Bayesian analysises of parameter of ЭРланга distribution under a symmetric lossJ. Journal of Neijiang Normal University, 2026, 41(2): 22-31. DOI: 10.13603/j.cnki.51-1621/z.2026.02.004
    Citation: CHANG Jiaqi, XU Bao. Bayesian analysises of parameter of ЭРланга distribution under a symmetric lossJ. Journal of Neijiang Normal University, 2026, 41(2): 22-31. DOI: 10.13603/j.cnki.51-1621/z.2026.02.004

    一种对称损失下艾拉姆咖分布参数的Bayes分析

    Bayesian analysises of parameter of ЭРланга distribution under a symmetric loss

    • 摘要: 在加权p,q对称熵损失函数下,使用统计决策与Bayes分析方法研究了艾拉姆咖分布参数的Bayes估计问题,得到了不同先验下艾拉姆咖分布参数的Bayes估计的精确形式,在Bayes估计的基础上得到了艾拉姆咖分布参数的经验Bayes估计与刀切Bayes估计的精确形式,证明了艾拉姆咖分布参数的Bayes估计具有可容许性和最小最大性.运用MCMC算法对所研究参数的Bayes估计、经验Bayes估计和刀切Bayes估计进行了数值模拟;在逆Gamma先验下,对不同损失函数下艾拉姆咖分布参数的Bayes估计进行比较,结果表明加权p,q对称熵损失函数下的Bayes估计具有较高的精度.

       

      Abstract: The problems of Bayesian estimation for the parameter of the ЭРланга distribution are studied using statistical decision theory and Bayesian analysis methods under the weighted p,q symmetric entropy loss function; The precise forms of Bayesian estimation for the parameter of the ЭРланга distribution under different priors are obtained; The precise forms of the empirical Bayesian estimation and the Jackknife Bayesian estimation for the parameters of the ЭРланга distribution are derived on the basis of the Bayesian estimation that obtained; The admissiblility and minimaxity of the Bayesian estimation of the parameter of ЭРланга distribution are proved; Finally, some numerically simulations are conducted to evaluate the performance of the Bayesian estimation, empirical Bayesian estimation, and Jackknife Bayesian estimation of the studied parameter using the MCMC algorithm; The Bayesian estimations of the parameter of ЭРланга distribution with the same inverse Gamma prior under different loss functions are compared; The results indicate that the Bayesian estimation under the weighted p,q symmetric entropy loss function has higher accuracy.

       

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