|Table of Contents|

Analysis of Empirical Likelihood Methods for Multivariate Generalized Linear Models(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2024年01期
Page:
7-13
Research Field:
数学
Publishing date:

Info

Title:
Analysis of Empirical Likelihood Methods for Multivariate Generalized Linear Models
Author(s):
Zhu Chunhua1; Shan Miaohui1; Gao Qibing2
(1.School of Statistics and Data Science,Nanjing Audit University,Nanjing,211815,China)
(2.School of Mathematical Sciences,Nanjing Normal University,Nanjing,210046,China)
Keywords:
multivariate generalized linear models; generalized estimating equations; empirical likelihood; confidence region
PACS:
O212.4
DOI:
10.3969/j.issn.1001-4616.2024.01.002
Abstract:
For the generalized linear models with multivariate responses,based on the estimating correlation matrix,the generalized estimating equations and empirical likelihood methods,this paper constructs the empirical likelihood ratio statistics which can overcome the mistakenly specification caused by the method of “working correlation matrix”. Under certain assumptions,this paper also obtains the asymptotic Wilks property of the empirical likelihood ratio statistics,which can be used to construct the confidence region of the unknown parameter. Last,the validity of the proposed method is verified through the numerical simulations.

References:

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Last Update: 2024-03-15