Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/17162
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dc.contributor.authorAristodemou, K-
dc.contributor.authorHe, J-
dc.contributor.authorYu, K-
dc.date.accessioned2018-11-27T15:43:33Z-
dc.date.available2018-02-08-
dc.date.available2018-11-27T15:43:33Z-
dc.date.issued2018-02-08-
dc.identifier.citationEconometric Reviews, 2019, 38(6): 679 - 694en_US
dc.identifier.issn0747-4938-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/17162-
dc.language.isoenen_US
dc.subjectadaptive lasso-
dc.subjectbinary regression-
dc.subjectiteratively reweighted least squares-
dc.subjectquantile regression-
dc.subjectsmoothed maximum score estimator-
dc.subjectvariable selection-
dc.subjectwork trip mode choice-
dc.titleBinary Quantile Regression and Variable Selection: A new Approachen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1080/07474938.2017.1417701-
dc.relation.isPartOfEconometric Reviews-
pubs.publication-statusPublished-
Appears in Collections:Dept of Mathematics Research Papers

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