分位数
估计员
数学
非参数统计
分位数函数
推论
计量经济学
单调函数
统计
计算机科学
累积分布函数
人工智能
概率密度函数
数学分析
作者
Zheng Fang,Qi Li,Karen X. Yan
出处
期刊:Econometric Theory
[Cambridge University Press]
日期:2021-12-13
卷期号:39 (2): 290-320
被引量:2
标识
DOI:10.1017/s0266466621000499
摘要
In this paper, we present a new nonparametric method for estimating a conditional quantile function and develop its weak convergence theory. The proposed estimator is computationally easy to implement and automatically ensures quantile monotonicity by construction. For inference, we propose to use a residual bootstrap method. Our Monte Carlo simulations show that this new estimator compares well with the check-function-based estimator in terms of estimation mean squared error. The bootstrap confidence bands yield adequate coverage probabilities. An empirical example uses a dataset of Canadian high school graduate earnings, illustrating the usefulness of the proposed method in applications.
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