Weighted Kernel regression
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- dc.contributor.author Delicado, Pedroca
- dc.contributor.author del Río, Manuelca
- dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
- dc.date.accessioned 2017-07-26T10:50:03Z
- dc.date.available 2017-07-26T10:50:03Z
- dc.date.issued 1996-03-01
- dc.date.modified 2017-07-23T02:02:31Z
- dc.description.abstract In the fixed design regression model, additional weights are considered for the Nadaraya--Watson and Gasser--M\"uller kernel estimators. We study their asymptotic behavior and the relationships between new and classical estimators. For a simple family of weights, and considering the IMSE as global loss criterion, we show some possible theoretical advantages. An empirical study illustrates the performance of the weighted estimators in finite samples.
- dc.format.mimetype application/pdfca
- dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=164
- dc.identifier.citation Communications in Statistics. Theory and methods, 26(12), 2983-2998, 1997
- dc.identifier.uri http://hdl.handle.net/10230/322
- dc.language.iso eng
- dc.relation.ispartofseries Economics and Business Working Papers Series; 164
- dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
- dc.subject.keyword asymptotic behavior
- dc.subject.keyword fixed design
- dc.subject.keyword nonparametric regression
- dc.subject.keyword smoothing
- dc.subject.keyword Statistics, Econometrics and Quantitative Methods
- dc.title Weighted Kernel regressionca
- dc.title.alternative Weighted nonparametric regression
- dc.type info:eu-repo/semantics/workingPaper