Probability inequalities for sums of NSD random variables and applications

作     者：Cai, Ting Hu, Hong Chang 

作者机构：Hubei Normal Univ Sch Math & Stat Huangshi Hubei Peoples R China 

出 版 物：《COMMUNICATIONS IN STATISTICS-THEORY AND METHODS》 (统计学通讯：理论与方法)

年 卷 期：2020年第49卷第2期

页      面：281-306页

核心收录：

学科分类：0202[经济学-应用经济学] 02[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）] 

基　　金：National Natural Science Foundation of China, NSFC, (11471105) National Natural Science Foundation of China, NSFC 

主　　题：NSD random variable generalized linear models M-estimates weak convergence 

摘      要：In this paper, we obtain the exponential-type inequalities for maximal partial sums of negatively superadditive dependent (NSD) random variables, which extends the corresponding results for independent and negatively associated (NA) random variables. Using these inequalities, we further investigate the weak convergence of the M-estimators in the generalized linear model with NSD errors, which generalize and improve the corresponding results of the independent random errors to that of NSD random errors.