Testing model assumptions in functional regression models

dc.contributor.author	Bücher, Axel	de
dc.contributor.author	Dette, Holger	de
dc.contributor.author	Wieczorek, Gabi	de
dc.date.accessioned	2009-10-29T10:26:47Z
dc.date.available	2009-10-29T10:26:47Z
dc.date.issued	2009-09-28	de
dc.description.abstract	In the functional regression model where the responses are curves new tests for the functional form of the regression and the variance function are proposed, which are based on a stochastic process estimating L^2-distances. Our approach avoids the explicit estimation of the functional regression and it is shown that normalized versions of the proposed test statistics converge weakly. The finite sample properties of the tests are illustrated by means of a small simulation study. It is also demonstrated that for small samples bootstrap versions of the tests improve the quality of the approximation of the nominal level.	en
dc.identifier.uri	http://hdl.handle.net/2003/26499
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-817
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823; 27/2009	de
dc.subject	functional data	en
dc.subject	goodness-of-fit tests	en
dc.subject	parametric bootstrap	en
dc.subject	tests for heteroscedasticity	en
dc.subject.ddc	310	de
dc.subject.ddc	330	de
dc.subject.ddc	620	de
dc.title	Testing model assumptions in functional regression models	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access

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