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Testing for parametric component of partially linear models with missing covariates

机译:用缺失的协变量进行部分线性模型的参数分量测试

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摘要

This paper considers the testing problem of partially linear models with missing covariates. The inverse probability weighted restricted estimator for the parametric component under linear constraint is derived and proven to share asymptotically normal distribution. To test the linear constraint, we construct two test statistics based on the the Lagrange multiplier and the empirical likelihood methods. The limiting distributions of the resulting test statistics are both standard chi-squared distributions under the null hypothesis. Simulation studies and a real data analysis are conducted to illustrate relevant performances.
机译:本文考虑了缺少协变量的部分线性模型的测试问题。 导出和证明在线性约束下的参数分量的反概率加权限制估计器以共享渐近正常分布。 为了测试线性约束,我们根据拉格朗日乘数和经验似然方法构建两个测试统计信息。 所得测试统计的限制分布是零假设下的标准Chi平方分布。 进行仿真研究和实际数据分析以说明相关性能。

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