Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10524905 | Journal of Statistical Planning and Inference | 2013 | 15 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Yan Fan, Lixing Zhu,