排序集抽样下定时截尾指数寿命数据的参数估计  

Parameter estimation of time censored exponential life data under ranked set sampling

作　　者：董晓芳[1] 高阳 张良勇[1] DONG Xiaofang;GAO Yang;ZHANG Liangyong(College of Mathematics and Statistics,Hebei University of Economics and Business,Shijiazhuang 050061,China)

机构地区：[1]河北经贸大学数学与统计学学院,河北石家庄050061

出　　处：《河北大学学报（自然科学版）》2022年第4期337-342,共6页Journal of Hebei University(Natural Science Edition)

基　　金：国家自然科学基金青年项目(11801134);河北省高等学校科学技术研究重点项目(ZD2022062);河北经贸大学重点项目(2021ZD05)。

摘　　要：针对定时截尾指数寿命数据的参数估计问题,采用排序集抽样方法,研究了指数分布参数的极大似然估计.针对排序集抽样下似然方程求不出解的问题,似然方程的部分项替换为期望,并给出修正极大似然估计.估计效率的比较结果说明:基于排序集抽样方法的修正估计量优于基于简单随机抽样方法的极大似然估计量.In order to solve the problem of parameter estimation for time censored exponential life data,the maximum likelihood estimation using ranked set sampling method is studied.For the problem that likelihood equation’s root under ranked set sampling is not found,some terms of likelihood equation are replaced with their expectations,and the modified maximum likelihood estimation is given.The comparison results of estimation efficiencies show that the proposed estimator using ranked set sampling method is better than maximum likelihood estimator using simple random sampling method.

关 键 词：定时截尾数据 排序集样本 参数估计 指数分布 

分 类 号：O212.1[理学—概率论与数理统计]