Testing for additivity in nonparametric quantile regression

Holger Dette (), Matthias Guhlich () and Natalie Neumeyer ()

Annals of the Institute of Statistical Mathematics, 2015, vol. 67, issue 3, 437-477

Abstract: 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. Copyright The Institute of Statistical Mathematics, Tokyo 2015

Keywords: Nonparametric regression; Quantile regression; Bootstrap; Additive estimation (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10463-014-0461-1

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