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Journal of Systems Science and Complexity

, Volume 31, Issue 5, pp 1362–1376 | Cite as

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

  • Qibing Gao
  • Xiuli Du
  • Xiuqing Zhou
  • Fengchang Xie
Article
  • 56 Downloads

Abstract

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 test statistics are presented. The results are illustrated by Monte-Carlo simulations.

Keywords

Asymptotic normality diverging dimension generalized linear models linear hypothesis maximum quasi-likelihood estimators 

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Copyright information

© Institute of Systems Science, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Qibing Gao
    • 1
  • Xiuli Du
    • 1
  • Xiuqing Zhou
    • 1
  • Fengchang Xie
    • 1
  1. 1.School of Mathematics ScienceNanjing Normal UniversityNanjingChina

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