On confidence bands for multivariate nonparametric regression

dc.contributor.authorProksch, Katharina
dc.date.accessioned2014-01-14T08:48:34Z
dc.date.available2014-01-14T08:48:34Z
dc.date.issued2014-01-14
dc.description.abstractIn a multivariate nonparametric regression problem with fixed, deterministic design asymptotic, uniform confidence bands for the regression function are constructed. The construction of the bands is based on the asymptotic distribution of the maximal deviation between a suitable nonparametric estimator and the true regression function which is derived by multivariate strong approximation methods and a limit theorem for the supremum of a stationary Gaussian field over an increasing system of sets. The results are derived for a general class of estimators which includes local polynomial estimators as a special case. The finite sample properties of the proposed asymptotic bands are investigated by means of a small simulation study.en
dc.identifier.urihttp://hdl.handle.net/2003/31821
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-7369
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;01/2014
dc.subjectconfidence bandsen
dc.subjectuniform convergenceen
dc.subjectnonparametric regressionen
dc.subjectmultivariate regressionen
dc.subjectrates of convergenceen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleOn confidence bands for multivariate nonparametric regressionen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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