Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.spl.2011.09.003
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dc.titleAn empirical likelihood approach to quantile regression with auxiliary information
dc.contributor.authorTang, C.Y.
dc.contributor.authorLeng, C.
dc.date.accessioned2014-10-28T05:09:59Z
dc.date.available2014-10-28T05:09:59Z
dc.date.issued2012-01
dc.identifier.citationTang, 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
dc.identifier.issn01677152
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104995
dc.description.abstractWe 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.spl.2011.09.003
dc.sourceScopus
dc.subjectAuxiliary information
dc.subjectEmpirical likelihood
dc.subjectEstimating equations
dc.subjectQuantile regression
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1016/j.spl.2011.09.003
dc.description.sourcetitleStatistics and Probability Letters
dc.description.volume82
dc.description.issue1
dc.description.page29-36
dc.description.codenSPLTD
dc.identifier.isiut000298204800005
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