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dc.contributor.authorPatschkowski, Tim-
dc.contributor.authorRohde, Angelika-
dc.date.accessioned2016-11-03T13:34:14Z-
dc.date.available2016-11-03T13:34:14Z-
dc.date.issued2016-
dc.identifier.urihttp://hdl.handle.net/2003/35308-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-17351-
dc.description.abstractWe develop honest and locally adaptive confidence bands for probability densities. They provide substantially improved confidence statements in case of inhomogeneous smoothness, and are easily implemented and visualized. The article contributes conceptual work on locally adaptive inference as a straightforward modification of the global setting imposes severe obstacles for statistical purposes. Among others, we introduce a statistical notion of local Hölder regularity and prove a correspondingly strong version of local adaptivity. We substantially relax the straightforward localization of the self-similarity condition in order not to rule out prototypical densities. The set of densities permanently excluded from the consideration is shown to be pathological in a mathematically rigorous sense. On a technical level, the crucial component for the verification of honesty is the identification of an asymptotically least favorable stationary case by means of Slepian's comparison inequality.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;60, 2016en
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleLocally adaptive confidence bandsen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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