Exponential-Poisson Parameters Estimation in Moving Extremes Ranked Set Sampling Design

作     者：Meng CHEN Wang-xue CHEN Rui YANG Ya-wen ZHOU 

作者机构：Department of Mathematics and Statistics Jishou University 

出 版 物：《Acta Mathematicae Applicatae Sinica》 (应用数学学报(英文版))

年 卷 期：2024年

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by the This research was supported by National Science Foundation of China (Grant Nos.12261036 and 11901236) Scientific Research Fund of Hunan Provincial Education Department (Grant No.21A0328) Provincial Natural Science Foundation of Hunan (Grant No.2022JJ30469) Young Core Teacher Foundation of Hunan Province (Grant No.43) 

摘      要：In this article, the maximum likelihood estimators (MLEs) of the scale and shape parameters βandλfrom the Exponential-Poisson distribution will be considered in moving extremes ranked set sampling(MERSS). These MLEs will be compared in terms of asymptotic efficiencies. The numerical results show that these MLEs in MERSS can be real competitors against those in simple random sampling.