Optimal Credibility Estimation of Random Parameters in Hierarchical Random Effect Linear Model

作     者：WEN Limin FANG Jing MEI Guoping WU Xianyi 

作者机构：School of Mathematics and Information Science Jiangxi Normal University School of Information Management Jiangxi University of Finance and Economics Department of Statistics and Actuarial Science East China Normal University 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报(英文版))

年 卷 期：2015年第28卷第5期

页      面：1058-1069页

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 National Science Foundation of China under Grant Nos.71361015,71340010,71371074 the Jiangxi Provincial Natural Science Foundation under Grant No.20142BAB201013 China Postdoctoral Science Foundation under Grant No.2013M540534 China Postdoctoral Fund special Project under Grant No.2014T70615 Jiangxi Postdoctoral Science Foundation under Grant No.2013KY53 

主　　题：Bayes theory credibility estimator hierarchical linear model random effect 

摘      要：In the hierarchical random effect linear model, the Bayes estimator of random parameter are not only dependent on specific prior distribution but also it is difficult to calculate in most *** paper derives the distributed-free optimal linear estimator of random parameters in the model by means of the credibility theory method. The estimators the authors derive can be applied in more extensive practical scenarios since they are only dependent on the first two moments of prior parameter rather than on specific prior distribution. Finally, the results are compared with some classical models and a numerical example is given to show the effectiveness of the estimators.