损失函数下逐步二型删失数据广义Pareto分布参数的Bayes估计  

Bayes Estimation of Generalized Pareto Distribution Parameters of Progressively Type II Censored Data Under Loss Functions

作　　者：苏燕青 金良琼 邹路燕 陶永 李琼忆 冉烨军 Su Yanqing;Jin Liangqiong;Zou Luyan;Tao Yong;Li Qiongyi;Ran Yejun(School of Data Science and Information Engineering,Guizhou Minzu University,Guiyang,China)

机构地区：[1]贵州民族大学数据科学与信息工程学院,贵州贵阳

出　　处：《科学技术创新》2024年第5期66-69,共4页Scientific and Technological Innovation

基　　金：贵州省科技计划基金项目(黔科合基础-ZK[2021]一般342)。

摘　　要：基于逐步二型删失数据,在几种不同的损失函数下,选择广义Pareto分布,讨论其形状参数的Bayes估计。当尺度参数给定时,为θ参数引入Gamma分布作为先验分布,得到了几种不同损失函数下参数θ的Bayes估计的数学表达式,通过数值模拟方法,比较了几种损失函数下所得到的Bayes估计的效果。结果表明:在Linex损失函数下,广义Pareto分布参数的Bayes估计效果最优。Based on progressively type II censored data,the Bayes estimation of shape parameters is discussed by generalized Pareto distribution under several different loss functions.When the scale parameter is given,the Gamma distribution is introduced as a prior distribution for the θ parameters,and the mathematical expressions of Bayes estimates under θ parameter for several different loss functions are obtained.The results show that the Bayes estimation of generalized Pareto distribution parameters is the best under Linex loss function.

关 键 词：逐步二型删失数据 广义PARETO分布 BAYES估计 损失函数 可容许性 

分 类 号：O213.2[理学—概率论与数理统计]