Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7546104 | Journal of the Korean Statistical Society | 2018 | 13 Pages |
Abstract
In this paper, we propose a robust statistical inference approach for the varying coefficient partially nonlinear models based on quantile regression. A three-stage estimation procedure is developed to estimate the parameter and coefficient functions involved in the model. Under some mild regularity conditions, the asymptotic properties of the resulted estimators are established. Some simulation studies are conducted to evaluate the finite performance as well as the robustness of our proposed quantile regression method versus the well known profile least squares estimation procedure. Moreover, the Boston housing price data is given to further illustrate the application of the new method.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Jing Yang, Fang Lu, Hu Yang,