Yu-nan Su 1,Mao-zai Tian 2 Center for Applied Statistics,School of Statistics,Remin University of China,Beijing,100872,China
Abstract:
In this paper we propose a new method of local linear adaptive smoothing for nonparametric conditional quantile regression. Some theoretical properties of the procedure are investigated. Then we demonstrate the performance of the method on a simulated example and compare it with other methods. The simulation results demonstrate a reasonable performance of our method proposed especially in situations when the underlying image is piecewise linear or can be approximated by such images. Generally speaking, our ...