Affiliation of Author(s):经济与管理学院
Journal:COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Key Words:Asymptotic normality Maximum likelihood estimation Spatial autoregressive models Semi-parametrics spatial autoregressive model
Abstract:Spatial data and non parametric methods arise frequently in studies of different areas and it is a common practice to analyze such data with semi-parametric spatial autoregressive (SPSAR) models. We propose the estimations of SPSAR models based on maximum likelihood estimation (MLE) and kernel estimation. The estimation of spatial regression coefficient was done by optimizing the concentrated log-likelihood function with respect to . Furthermore, under appropriate conditions, we derive the limiting distributions of our estimators for both the parametric and non parametric components in the model.
ISSN No.:0361-0926
Translation or Not:no
Date of Publication:2018-01-01
Co-author:Peng Xiaozhi,Ma Ling
Correspondence Author:Peng Xiaozhi,whc