Estimation and Testing of Varying Coefficients in Quantile Regression

• 成果类型: Article
• 署名作者: Feng, Xingdong; Zhu, Liping
• 署名单位: Shanghai University of Finance & Economics; Renmin University of China
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2014.1001068
• 发表日期: 2016
• 页码: 266-274
• 关键词: Rank; inference; matrices

摘要

In this article, we establish a novel connection between the null hypothesis H-0 on the coefficients and a rank-reducible form of the varying coefficient model in quantile regression. We use B-splines to approximate the varying coefficients in the rank-reducible model, and make use of the fact that the null hypothesis H-0 implies a unidimensional structure of a transformed coefficient matrix for the B-spline basis functions. By evaluating the unidimensional structure, we alleviate the difficulty of testing such hypotheses commonly considered in varying coefficient quantile models. We demonstrate through numerical studies that the proposed method can be much more powerful than the rank score test which is widely used in the quantile regression literature. Supplementary materials for this article are available online.