Two-Sided Empirical Bayes Test for the Exponential Family with Contaminated Data

作     者：CHEN Jiaqing JIN Qianyu CHEN Zhiqiang LIU Cihua 

作者机构：College of Science Wuhan University of Technology College of Mathematics and Statistics Huazhong University of Science and Technology 

出 版 物：《Wuhan University Journal of Natural Sciences》 (武汉大学学报（自然科学英文版）)

年 卷 期：2013年第18卷第6期

页      面：466-470页

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 Fundamental Research Funds for the Central Universities of China(2013-Ia-040) 

主　　题：empirical Bayes test asymptotic optimal conver-gence rate contaminated data 

摘      要：In this study, the two-sided Empirical Bayes test （EBT） rules for the parameter of continuous one-parameter exponential family with contaminated data （errors in variables） are constructed by a deconvolution kernel method. The asymptotically optimal uniformly over a class of prior distributions and uniform rates of convergence, which depends on two types of the error distribu- tions for the proposed EBT rules, are obtained under suitable con- ditions. Finally, an example about the main results of this paper is given.