title: New Goodness-of-Fit Tests and their Application toNonparametric Confidence Sets
creator: Dümbgen, Lutz
subject: ddc-310
subject: 310 General statistics
subject: ddc-510
subject: 510 Mathematics
description: Suppose one observes a process V on the unit interval, wheredV(t) = f(t) + dW(t) with an unknown function f and standard Brownian motion W. We propose a particular test of one-point hypotheses about f which is based on suitably standardized increments of V.This test is shown to have desirable consistency properties if, for instance, fis restricted to various Hölder smoothness classes of functions. Thetest is mimicked in the context of nonparametric density estimation,nonparametric regression and interval censored data. Under shaperestrictions on the parameter f such as monotonicity or convexity, weobtain confidence sets for f adapting to its unknown smoothness.
publisher: IMS Business Office
date: 1998
type: Article
type: info:eu-repo/semantics/article
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/20896/1/beitrag.32.pdf
identifier: DOI:10.11588/heidok.00020896
identifier: urn:nbn:de:bsz:16-heidok-208967
identifier:   Dümbgen, Lutz  (1998) New Goodness-of-Fit Tests and their Application toNonparametric Confidence Sets.  The Annals of Statistics, 26 (1).  pp. 288-314.  ISSN 0090-5364     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/20896/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng