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dc.contributor.authorBücher, Axelde
dc.contributor.authorDette, Holgerde
dc.contributor.authorWieczorek, Gabide
dc.date.accessioned2009-10-29T10:26:47Z-
dc.date.available2009-10-29T10:26:47Z-
dc.date.issued2009-09-28de
dc.identifier.urihttp://hdl.handle.net/2003/26499-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-817-
dc.description.abstractIn 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.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823; 27/2009de
dc.subjectfunctional dataen
dc.subjectgoodness-of-fit testsen
dc.subjectparametric bootstrapen
dc.subjecttests for heteroscedasticityen
dc.subject.ddc310de
dc.subject.ddc330de
dc.subject.ddc620de
dc.titleTesting model assumptions in functional regression modelsen
dc.typeTextde
dc.type.publicationtypereportde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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