| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1154284 | Statistics & Probability Letters | 2016 | 8 Pages |
Abstract
In robust nonparametric kernel regression context, we prescribe method to select trimming parameter and bandwidth. Through solving estimating equations, we control outlier effect through combining weighting and trimming. We show asymptotic consistency, establish bias, variance properties and derive asymptotics.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Ge Zhao, Yanyuan Ma,