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| 摘要: |
| 文章考虑半参数变系数空间误差回归模型下的参数估计和变量选择问题。首先利用局部多项式的方法对变系数函数进行估计,然后分别构造参数部分和非参数部分的最大经验对数似然比估计,并使用惩罚经验似然(PEL)进行选择变量,最后用平方再求和的方法估计空间系数及误差项的方差。在合适的条件下,证明所用的惩罚经验似然估计具有Oracle特征且在零假设下服从渐近卡方分布。 |
| 关键词: 部分线性模型 惩罚经验似然 空间自回归 变量误差 |
| DOI： |
| 分类号:O212.7 |
| 基金项目: |
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| Penalized empirical likelihood for semiparametric varying coefficient spatial error regression model |
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WANG Yiheng
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| Abstract: |
| The article considers the problem of parameter estimation and variable selection in semiparametric variable coefficient spatial error regression model. First, 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 then the square and sum method was used to estimate the variance of the spatial coefficient and error term. Under suitable conditions, the Penalized empirical likelihood has oracle characteristics and obeys the asymptotic chi-square distribution under the null hypothesis. |
| Key words: Partially linear model Penalized empirical likelihood SAR Errors-in- variables |
