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Quantile Regression for Partially Linear Models with Missing Responses at Random

机译:分位数回归用于随机缺失响应的部分线性模型

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In this paper, we propose a weighted quantile regression method for partially linear models with missing response at random. The proposed estimation method can give an efficient estimator for parametric components, and can attenuate the effect of missing responses. Some simulations are carried out to assess the performance of the proposed estimation method, and simulation results indicate that the proposed method is workable.
机译:在本文中,我们提出了一种加权分位数回归方法,用于随机缺失响应的部分线性模型。所提出的估计方法可以为参数分量提供有效的估计器,并且可以衰减缺失响应的效果。进行了一些模拟以评估所提出的估计方法的性能,仿真结果表明该方法是可行的。

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