Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1154909 | Statistics & Probability Letters | 2012 | 11 Pages |
Abstract
This paper considers the weighted composite quantile (WCQ) regression for linear model with random censoring. The adaptive penalized procedure for variable selection in this model is proposed, and the consistency, asymptotic normality and oracle property of the resulting estimators are also derived. The simulation studies and the analysis of an acute myocardial infarction data set are conducted to illustrate the finite sample performance of the proposed method.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Linjun Tang, Zhangong Zhou, Changchun Wu,