Testing the Equality of Nonparametric Regression Curves

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dc.contributor.author Delgado, Miguel A.
dc.date.accessioned 2009-11-05T09:30:06Z
dc.date.available 2009-11-05T09:30:06Z
dc.date.issued 1993
dc.identifier.bibliographicCitation Statistics and Probability Letters, 1993, vol.17, nº. 3, p. 199-204
dc.identifier.issn 0167-7152
dc.identifier.uri http://hdl.handle.net/10016/2389
dc.description.abstract This paper proposes a test for the equality of nonparametric regression curves that does not depend on the choice of a smoothing number. The test statistic resembles in spirit the Kolmogorov-Smirnov statistic and it is easy to compute. It is powerful under alternatives that converge to the null hypothesis at a rate n ^ (-1/2). The disturbance distributions are arbitrary and possibly unequal, and conditions on the regressors distribution are very mild. A Monte Carlo study illustrates the performance of the test in small and moderate samples. We also study extensions to multiple regression, and test the equality of several regression curves.
dc.format.mimetype application/pdf
dc.format.mimetype text/plain
dc.language.iso eng
dc.language.iso eng
dc.publisher Elsevier
dc.rights © Elsevier
dc.subject.other Nonparametric
dc.subject.other testing
dc.subject.other weighted emperical process
dc.subject.other Donsker's invariance principles
dc.title Testing the Equality of Nonparametric Regression Curves
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1016/0167-7152(93)90167-H
dc.subject.eciencia Economía
dc.identifier.doi 10.1016/0167-7152(93)90167-H
dc.rights.accessRights openAccess
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