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Article: A lack-of-fit test for quantile regression
Title | A lack-of-fit test for quantile regression |
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Authors | |
Keywords | Consistency Cusum process Empirical process Goodness-of-fit Linear regression |
Issue Date | 2003 |
Publisher | American Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main |
Citation | Journal of the American Statistical Association, 2003, v. 98 n. 464, p. 1013-1022 How to Cite? |
Abstract | We propose a new lack-of-fit test for quantile regression models that is suitable even with high-dimensional covariates. The test is based on the cumulative sum of residuals with respect to unidimensional linear projections of the covariates. The test adapts concepts proposed by Escanciano (Econometric Theory, 22, 2006) to cope with many covariates to the test proposed by He and Zhu (Journal of the American Statistical Association, 98, 2003). To approximate the critical values of the test, a wild bootstrap mechanism is used, similar to that proposed by Feng et al. (Biometrika, 98, 2011). An extensive simulation study was undertaken that shows the good performance of the new test, particularly when the dimension of the covariate is high. The test can also be applied and performs well under heteroscedastic regression models. The test is illustrated with real data about the economic growth of 161 countries. |
Persistent Identifier | http://hdl.handle.net/10722/224198 |
ISSN | 2023 Impact Factor: 3.0 2023 SCImago Journal Rankings: 3.922 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | He, X | - |
dc.contributor.author | Zhu, LX | - |
dc.date.accessioned | 2016-03-29T07:11:51Z | - |
dc.date.available | 2016-03-29T07:11:51Z | - |
dc.date.issued | 2003 | - |
dc.identifier.citation | Journal of the American Statistical Association, 2003, v. 98 n. 464, p. 1013-1022 | - |
dc.identifier.issn | 0162-1459 | - |
dc.identifier.uri | http://hdl.handle.net/10722/224198 | - |
dc.description.abstract | We propose a new lack-of-fit test for quantile regression models that is suitable even with high-dimensional covariates. The test is based on the cumulative sum of residuals with respect to unidimensional linear projections of the covariates. The test adapts concepts proposed by Escanciano (Econometric Theory, 22, 2006) to cope with many covariates to the test proposed by He and Zhu (Journal of the American Statistical Association, 98, 2003). To approximate the critical values of the test, a wild bootstrap mechanism is used, similar to that proposed by Feng et al. (Biometrika, 98, 2011). An extensive simulation study was undertaken that shows the good performance of the new test, particularly when the dimension of the covariate is high. The test can also be applied and performs well under heteroscedastic regression models. The test is illustrated with real data about the economic growth of 161 countries. | - |
dc.language | eng | - |
dc.publisher | American Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main | - |
dc.relation.ispartof | Journal of the American Statistical Association | - |
dc.subject | Consistency | - |
dc.subject | Cusum process | - |
dc.subject | Empirical process | - |
dc.subject | Goodness-of-fit | - |
dc.subject | Linear regression | - |
dc.title | A lack-of-fit test for quantile regression | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1198/016214503000000963 | - |
dc.identifier.scopus | eid_2-s2.0-1142301687 | - |
dc.identifier.hkuros | 95420 | - |
dc.identifier.volume | 98 | - |
dc.identifier.issue | 464 | - |
dc.identifier.spage | 1013 | - |
dc.identifier.epage | 1022 | - |
dc.identifier.isi | WOS:000188318600026 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0162-1459 | - |