Empirical likelihood for spatial cross-sectional data models with matrix exponential spatial specification

In this paper, we study spatial cross-sectional data models in the form of matrix exponential spatial specification (MESS), where MESS appears in both dependent and error terms. The empirical likelihood (EL) ratio statistics are established for the parameters of the MESS model. It is shown that the...

Full description

Saved in:
Bibliographic Details
Published inApplied Mathematics-A Journal of Chinese Universities Vol. 39; no. 1; pp. 125 - 139
Main Authors Liu, Yan, Rong, Jian-rong, Qin, Yong-song
Format Journal Article
LanguageEnglish
Published Singapore Springer Nature Singapore 01.03.2024
Springer Nature B.V
Subjects
Applications of Mathematics
Chi-square test
Mathematical models
Mathematics
Mathematics and Statistics
Parameters
Spatial data
Specifications
62G05
empirical likelihood
confidence region
MESS
62E20
Online AccessGet full text

Cover

More Information
Summary:In this paper, we study spatial cross-sectional data models in the form of matrix exponential spatial specification (MESS), where MESS appears in both dependent and error terms. The empirical likelihood (EL) ratio statistics are established for the parameters of the MESS model. It is shown that the limiting distributions of EL ratio statistics follow chi-square distributions, which are used to construct the confidence regions of model parameters. Simulation experiments are conducted to compare the performances of confidence regions based on EL method and normal approximation method.
ISSN:1005-1031
1993-0445
DOI:10.1007/s11766-024-4446-4