Document Type
Journal Article
Department/Unit
Department of Mathematics
Title
Estimation of general semi-parametric quantile regression
Language
English
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. © 2012 Elsevier B.V.
Keywords
Eigenvector, Outer-product gradient estimation (OPG), QOPG, Quantile regression, Single-index model
Publication Date
2013
Source Publication Title
Journal of Statistical Planning and Inference
Volume
143
Issue
5
Start Page
896
End Page
910
Publisher
Elsevier
DOI
10.1016/j.jspi.2012.11.005
Link to Publisher's Edition
http://dx.doi.org/10.1016/j.jspi.2012.11.005
ISSN (print)
03783758
APA Citation
Fan, Y., & Zhu, L. (2013). Estimation of general semi-parametric quantile regression. Journal of Statistical Planning and Inference, 143 (5), 896-910. https://doi.org/10.1016/j.jspi.2012.11.005