Asymptotic normality for a local composite quantile regression estimator of regression function with truncated data

作者：Wang, Jiang-Feng; Ma, Wei-Min^*; Zhang, Hui-Zeng; Wen, Li-Min

来源：Statistics & Probability Letters, 2013, 83(6): 1571-1579.

DOI：10.1016/j.spl.2013.02.022

• Composite quantile regression
• Local linear regression
• Truncated data
• Asymptotic normality

In this paper, we construct a local linear composite quantile regression (CQR) estimator of regression function for left-truncated data, which extends the CQR method to the left-truncated model. The asymptotic normality of the proposed estimator is also established. The estimator is much more efficient than the local linear regression estimator for commonly-used non-normal error distributions via simulations.

• 出版日期2013-6
• 单位江西师范大学; 杭州师范大学; 浙江工商大学; 同济大学