Identification and estimation in quantile varying-coefficient models with unknown link function

被引：0
作者：
Lili Yue
Gaorong Li
Heng Lian
机构：
[1] Beijing University of Technology,Beijing Institute for Scientific and Engineering Computing
[2] City University of Hong Kong,Department of Mathematics
来源：
TEST | 2019年 / 28卷
关键词：
Asymptotic property; B-splines; Check loss minimization; Single-index models; Quantile regression; 62G08; 62G20; 62G35;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we consider the estimation problem of quantile varying-coefficient models when the link function is unspecified, which significantly expands the existing works on varying-coefficient models with unspecified link function focusing only on mean regression. We provide new identification conditions which are weaker than existing ones. Under these identification conditions, we use polynomial splines to estimate both the varying coefficients and the link functions and establish the convergence rate of the estimator. Our simulation studies and a real data application illustrate the finite sample performance of the estimators.
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页码：1251 / 1275
页数：24
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