Statistics and Its Interface

Volume 17 (2024)

Number 4

A consistent specification test for functional linear quantile regression models

Pages: 649 – 667

DOI: https://dx.doi.org/10.4310/22-SII754

Authors

Lili Xia (Beijing University of Technology)

Zhongzhan Zhang (Beijing University of Technology)

Gongming Shi (Capital University of Economics and Business)

Abstract

This paper is focused on the specification test of functional linear quantile regression models. A nonparametric test statistic is proposed based on the orthogonality of residual and its conditional expectation. It is proved with mild assumptions that the proposed statistic follows asymptotically the standard normal distribution under the null hypothesis, but tends to infinity under alternative hypothesis. The asymptotic power of the test is also presented for some local alternative hypotheses. The test is easy to implement, and is shown by simulations powerful even for small sample sizes. A real data example with the Capital Bikeshare data is presented for illustration.

Keywords

functional data, quantile regression, consistent test, quadratic form, nonparametric test

2010 Mathematics Subject Classification

Primary 62G10. Secondary 62G20.

Received 26 January 2022

Accepted 21 August 2022

Published 19 July 2024