数学杂志2025，Vol.45Issue(4)：337-348,12.
半参数变系数空间误差回归模型的惩罚经验似然
PENALIZED EMPIRICAL LIKELIHOOD FOR SEMIPARAMETRIC VARYING COEFFICIENT SPATIAL ERROR REGRESSION MODEL
摘要
Abstract
The article considers the problem of parameter estimation and variable selection in semi-parametric variable coefficient spatial error regression model.The local linear estimation method was used to estimate the variable coefficient function,then the maximum empirical log-likelihood ratio estimation of parametric and non-parametric components is constructed,and PEL was suggested to select the variables,and the square and sum method was used to estimate the variance of the spatial coefficient and error term.The estimated values of pa-rameters and non-parameters and the superiority of PEL method in selecting variables are obtained.Under suitable conditions,the Penalized empirical likelihood has oracle charac-teristics and obeys the asymptotic chi-square distribution under the null hypothesis.关键词
部分线性模型/惩罚经验似然/空间自回归/变量误差Key words
partially linear model/penalized empirical likelihood/SAR/Errors-in-variables分类
数理科学引用本文复制引用
王以恒,何帮强..半参数变系数空间误差回归模型的惩罚经验似然[J].数学杂志,2025,45(4):337-348,12.基金项目
"行政记录人口普查"的数据质量评估框架研究(21CTJ005) （21CTJ005）
金融资产泡沫的形成、识别及其价格有效性测度研究(72271003). （72271003）
