Asymptotic Properties of Maximum Quasi-Likelihood Estimators in Generalized Linear Models with Diverging Number of Covariates  

作　　者：GAO Qibing DU Xiuli ZHOU Xiuqing XIE Fengchang 

机构地区：[1]School of Mathematics Science, Nanjing Normal University

出　　处：《Journal of Systems Science & Complexity》2018年第5期1362-1376,共15页系统科学与复杂性学报（英文版）

基　　金：supported by Major Programm of Natural Science Foundation of China under Grant No.71690242;the Natural Science Foundation of China under Grant No.11471252;the National Social Science Fund of China under Grant No.18BTJ040

摘　　要：In this paper, for the generalized linear models （GLMs） with diverging number of covariates, the asymptotic properties of maximum quasi-likelihood estimators （MQLEs） under some regular conditions are developed. The existence, weak convergence and the rate of convergence and asymptotic normality of linear combination of MQLEs and asymptotic distribution of single linear hypothesis teststatistics are presented. The results are illustrated by Monte-Carlo simulations.

关 键 词：Asymptotic normality diverging dimension generalized linear models linear hypothesis maximum quasi-likelihood estimators. 

分 类 号：O212[理学—概率论与数理统计]