Department of Mathematics
Estimation of general semi-parametric quantile regression
Quantile regression introduced by Koenker and Bassett (1978) produces a comprehensive picture of a response variable on predictors. In this paper, we propose a general semi-parametric model of which part of predictors are presented with a single-index, to model the relationship of conditional quantiles of the response on predictors. Special cases are single-index models, partially linear single-index models and varying coefficient single-index models. We propose the qOPG, a quantile regression version of outer-product gradient estimation method (OPG, Xia et al., 2002) to estimate the single-index. Large-sample properties, simulation results and a real-data analysis are provided to examine the performance of the qOPG. © 2012 Elsevier B.V.
Eigenvector, Outer-product gradient estimation (OPG), QOPG, Quantile regression, Single-index model
Source Publication Title
Journal of Statistical Planning and Inference
Link to Publisher's Edition
Fan, Yan, and Lixing Zhu. "Estimation of general semi-parametric quantile regression." Journal of Statistical Planning and Inference 143.5 (2013): 896-910.