论文标题
基于凸编程解决方案的基于分位数的概要估计器，响应缺失和高维协变量
A Convex Programming Solution Based Debiased Estimator for Quantile with Missing Response and High-dimensional Covariables
论文作者
论文摘要
本文与响应随机丢失时有关响应分位数的估计问题的估计问题。一些现有方法为响应分位数定义了root-n一致的估计器。但是，这些方法需要正确的规格，即给定协变量的响应的条件分布和选择概率函数。在本文中，通过求解凸面编程提出了一种依据的方法。给定条件分布函数的正确指定的参数模型，通过提出方法获得的估计器在无需指定和估算选择概率函数的情况下均非正常。此外，提出的估计器在渐近上比现有估计器更有效。该方法通过模拟研究评估，并通过真实数据示例进行了说明。
This paper is concerned with the estimating problem of response quantile with high dimensional covariates when response is missing at random. Some existing methods define root-n consistent estimators for the response quantile. But these methods require correct specifications of both the conditional distribution of response given covariates and the selection probability function. In this paper, a debiased method is proposed by solving a convex programming. The estimator obtained by the proposed method is asymptotically normal given a correctly specified parametric model for the condition distribution function, without the requirement to specify and estimate the selection probability function. Moreover, the proposed estimator is asymptotically more efficient than the existing estimators. The proposed method is evaluated by a simulation study and is illustrated by a real data example.
