Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.spl.2011.09.003
Title: An empirical likelihood approach to quantile regression with auxiliary information
Authors: Tang, C.Y. 
Leng, C. 
Keywords: Auxiliary information
Empirical likelihood
Estimating equations
Quantile regression
Issue Date: Jan-2012
Citation: Tang, C.Y., Leng, C. (2012-01). An empirical likelihood approach to quantile regression with auxiliary information. Statistics and Probability Letters 82 (1) : 29-36. ScholarBank@NUS Repository. https://doi.org/10.1016/j.spl.2011.09.003
Abstract: We consider how to incorporate auxiliary information to improve quantile regression via empirical likelihood. We propose a novel framework and show that our approach yields more efficient estimates compared to those from the conventional quantile regression. The efficiency gain is quantified theoretically and demonstrated empirically via simulation studies. © 2011 Elsevier B.V.
Source Title: Statistics and Probability Letters
URI: http://scholarbank.nus.edu.sg/handle/10635/104995
ISSN: 01677152
DOI: 10.1016/j.spl.2011.09.003
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