Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1151664 | Statistics & Probability Letters | 2014 | 11 Pages |
Abstract
In this paper, we study the weighted composite quantile regression (WCQR) for general linear model with missing covariates. We propose the WCQR estimation and bootstrap test procedures for unknown parameters. Simulation studies and a real data analysis are conducted to examine the finite performance of our proposed methods.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Zijun Ning, Linjun Tang,