Testing for additivity in nonparametric quantile regression

被引：0
|
作者：
Dette, Holger [1 ]
Guhlich, Matthias [1 ]
Neumeyer, Natalie [2 ]
机构：
[1] Ruhr Univ Bochum, Fak Math, D-44780 Bochum, Germany
[2] Univ Hamburg, Fachbereich Math, D-20146 Hamburg, Germany
来源：
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 2015年 / 67卷 / 03期
关键词：
Nonparametric regression; Quantile regression; Bootstrap; Additive estimation; MODEL;
D O I：
10.1007/s10463-014-0461-1
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this article, we propose a new test for additivity in nonparametric quantile regression with a high-dimensional predictor. Asymptotic normality of the corresponding test statistic (after appropriate standardization) is established under the null hypothesis, local and fixed alternatives. We also propose a bootstrap procedure which can be used to improve the approximation of the nominal level for moderate sample sizes. The methodology is also illustrated by means of a small simulation study, and a data example is analyzed.
引用
收藏
页码：437 / 477
页数：41
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