Consistency and asymptotic normality of the maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with random regressors

被引：5

作者：

Xia, Tian ^{[1
]}

Wang, Shun-fang ^{[2
]}

Wang, Xue-ren ^{[1
]}

机构：

[1] Yunnan Univ, Dept Biostat, Kunming 650091, Peoples R China

[2] Yunnan Univ, Sch Informat Sci & Engn, Kunming 650091, Peoples R China

来源：

ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2010年 / 26卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Asymptotic normality; consistency; maximum quasi-likelihood estimator; quasi-likelihood nonlinear models with random regressors; GENERALIZED LINEAR-MODELS;

D O I：

10.1007/s10255-009-7168-8

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper proposes some regularity conditions, which result in the existence, strong consistency and asymptotic normality of maximum quasi-likelihood estimator (MQLE) in quasi-likelihood nonlinear models (QLNM) with random regressors. The asymptotic results of generalized linear models (GLM) with random regressors are generalized to QLNM with random regressors.

引用

页码：241 / 250

页数：10

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