Combining least-squares and quantile regressions

doi:10.1016/j.jspi.2011.06.018

CSpace > 应用数学研究所

	Combining least-squares and quantile regressions
	Zhou, Yong2,3 ; Wan, Alan T. K.1; Yuan, Yuan 3
	2011-12-01
发表期刊	JOURNAL OF STATISTICAL PLANNING AND INFERENCE
ISSN	0378-3758
卷号	141 期号:12 页码:3814-3828
摘要	Least-squares and quantile regressions are method of moments techniques that are typically used in isolation. A leading example where efficiency may be gained by combining least-squares and quantile regressions is one where some information on the error quantiles is available but the error distribution cannot be fully specified. This estimation problem may be cast in terms of solving an over-determined estimating equation (EE) system for which the generalized method of moments (GMM) and empirical likelihood (EL) are approaches of recognized importance. The major difficulty with implementing these techniques here is that the EEs associated with the quantiles are non-differentiable. In this paper, we develop a kernel-based smoothing technique for non-smooth EEs, and derive the asymptotic properties of the GMM and maximum smoothed EL (MSEL) estimators based on the smoothed EEs. Via a simulation study, we investigate the finite sample properties of the GMM and MSEL estimators that combine least-squares and quantile moment relationships. Applications to real datasets are also considered. (C) 2011 Elsevier B.V. All rights reserved.
关键词	Empirical likelihood Estimating equations Generalized method of moments Kernel Smoothing
DOI	10.1016/j.jspi.2011.06.018
语种	英语
资助项目	National Natural Science Funds for Distinguished Young Scholar[70825004] ; National Natural Science Foundation of China (NSFC)[10628104] ; National Natural Science Foundation of China (NSFC)[10731010] ; National Basic Research Program[2007CB814902] ; Creative Research Groups of China[10721101] ; Hong Kong Research Grants Council[CityU-102709] ; City University of Hong Kong[CityU-7008126]
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000294149800015
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/11621
专题	应用数学研究所
通讯作者	Wan, Alan T. K.
作者单位	1.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China 3.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai 200433, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Yong,Wan, Alan T. K.,Yuan, Yuan. Combining least-squares and quantile regressions[J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE,2011,141(12):3814-3828.
APA	Zhou, Yong,Wan, Alan T. K.,&Yuan, Yuan.(2011).Combining least-squares and quantile regressions.JOURNAL OF STATISTICAL PLANNING AND INFERENCE,141(12),3814-3828.
MLA	Zhou, Yong,et al."Combining least-squares and quantile regressions".JOURNAL OF STATISTICAL PLANNING AND INFERENCE 141.12(2011):3814-3828.