Non-crossing convex quantile regression

IF 2.1 4区经济学 Q2 ECONOMICS

Economics Letters Pub Date : 2023-10-13 DOI:10.1016/j.econlet.2023.111396

Sheng Dai , Timo Kuosmanen , Xun Zhou

引用次数: 7

Abstract

Quantile crossing is a common phenomenon in shape constrained nonparametric quantile regression. A direct approach to address this problem is to impose non-crossing constraints to convex quantile regression. However, the non-crossing constraints may violate an intrinsic quantile property. This paper proposes a penalized convex quantile regression approach that can circumvent quantile crossing while maintaining the quantile property. A Monte Carlo study demonstrates the superiority of the proposed penalized approach in addressing the quantile crossing problem.

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非交叉凸分位数回归

分位数交叉是形状约束非参数分位数回归中常见的现象。解决这个问题的直接方法是对凸分位数回归施加非交叉约束。然而，非交叉约束可能违反固有的分位数特性。本文提出了一种惩罚凸分位数回归方法，该方法可以在保持分位数性质的同时避免分位数交叉。蒙特卡罗研究证明了所提出的惩罚方法在解决分位数交叉问题方面的优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Economics Letters ECONOMICS-

CiteScore

3.20

自引率

5.00%

发文量

348

审稿时长

30 days

期刊介绍： Many economists today are concerned by the proliferation of journals and the concomitant labyrinth of research to be conquered in order to reach the specific information they require. To combat this tendency, Economics Letters has been conceived and designed outside the realm of the traditional economics journal. As a Letters Journal, it consists of concise communications (letters) that provide a means of rapid and efficient dissemination of new results, models and methods in all fields of economic research.