dc.contributor.authorLian, Heng
dc.date.accessioned2013-07-22T03:06:00Z
dc.date.available2013-07-22T03:06:00Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationLian, H. (2012). A note on the consistency of Schwarz’s criterion in linear quantile regression with the SCAD penalty. Statistics & Probability Letters, 82(7), 1224-1228.en_US
dc.identifier.issn0167-7152en_US
dc.identifier.urihttp://hdl.handle.net/10220/11928
dc.description.abstractIn this short note, we demonstrate that Schwarz’s criterion, which has been used frequently in the literature on quantile regression, is consistent in variable selection. In particular, due to the recent interest in penalized likelihood for variable selection, we also show that Schwarz’s criterion consistently selects the true model combined with the SCAD-penalized estimator. Although similar results have been proved for linear regression, the results obtained here are new for quantile regression, which imposes extra technical difficulties compared to mean regression, since no closed-form solution exists.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesStatistics & probability lettersen_US
dc.rights© 2012 Elsevier B.V.en_US
dc.subjectDRNTU::Science::Mathematics
dc.titleA note on the consistency of Schwarz’s criterion in linear quantile regression with the SCAD penaltyen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.spl.2012.03.039


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