KMS Of Academy of mathematics and systems sciences, CAS
| Combining least-squares and quantile regressions | |
Zhou, Yong2,3 ; Wan, Alan T. K.1; Yuan, Yuan3
| |
| 2011-12-01 | |
| Source Publication | JOURNAL OF STATISTICAL PLANNING AND INFERENCE
 |
| ISSN | 0378-3758 |
| Volume | 141Issue:12Pages:3814-3828 |
| Abstract | 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. |
| Keyword | Empirical likelihood Estimating equations Generalized method of moments Kernel Smoothing |
| DOI | 10.1016/j.jspi.2011.06.018 |
| Language | 英语 |
| Funding Project | 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 Research Area | Mathematics |
| WOS Subject | Statistics & Probability |
| WOS ID | WOS:000294149800015 |
| Publisher | ELSEVIER SCIENCE BV |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/11621 |
| Collection | 应用数学研究所 |
| Corresponding Author | Wan, Alan T. K. |
| Affiliation | 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 |
| Recommended Citation 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. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment