Testing symmetry of a nonparametric bivariate regression function

dc.contributor.author	Birke, Melanie	de
dc.contributor.author	Dette, Holger	de
dc.contributor.author	Stahljans, Kristin	de
dc.date.accessioned	2009-10-29T10:07:00Z
dc.date.available	2009-10-29T10:07:00Z
dc.date.issued	2009-07-10	de
dc.description.abstract	We propose a test for symmetry of a regression function with a bivariate predictor based on the L_2 distance between the original function and its reflection. This distance is estimated by kernel methods and it is shown that under the null hypothesis as well as under the alternative the test statistic is asymptotically normally distributed. The finite sample properties of a bootstrap version of this test are investigated by means of a simulation study and a possible application in detecting asymmetries in gray-scale images is discussed.	en
dc.identifier.uri	http://hdl.handle.net/2003/26480
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-12674
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823; 5/2009	de
dc.subject.ddc	310	de
dc.subject.ddc	330	de
dc.subject.ddc	620	de
dc.title	Testing symmetry of a nonparametric bivariate regression function	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access
eldorado.dnb.deposit	true

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