Consistency results and confidence intervals for adaptive l1-penalized estimators of the high-dimensional sparse precision matrix

dc.bibliographicCitation.seriesTitleWIAS Preprintseng
dc.bibliographicCitation.volume2229
dc.contributor.authorAvanesov, Valeriy
dc.contributor.authorPolzehl, Jörg
dc.contributor.authorTabelow, Karsten
dc.date.accessioned2016-12-13T10:46:58Z
dc.date.available2019-06-28T08:01:57Z
dc.date.issued2016
dc.description.abstractIn this paper we consider the adaptive '1-penalized estimators for the precision matrix in a finite-sample setting. We show consistency results and construct confidence intervals for the elements of the true precision matrix. Additionally, we analyze the bias of these confidence intervals. We apply the estimator to the estimation of functional connectivity networks in functional Magnetic Resonance data and elaborate the theoretical results in extensive simulation experiments.eng
dc.description.versionpublishedVersioneng
dc.formatapplication/pdf
dc.identifier.issn2198-5855
dc.identifier.urihttps://doi.org/10.34657/2143
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/1645
dc.language.isoengeng
dc.publisherBerlin : Weierstraß-Institut für Angewandte Analysis und Stochastikeng
dc.relation.issn0946-8633eng
dc.rights.licenseThis document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.eng
dc.rights.licenseDieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.ger
dc.subject.ddc510eng
dc.subject.otherAdaptive l1 penaltyeng
dc.subject.otherprecision matrixeng
dc.subject.otherhigh-dimensional statisticseng
dc.subject.othersparsityeng
dc.subject.otherconfidence intervalseng
dc.subject.otherfunctional connectivityeng
dc.titleConsistency results and confidence intervals for adaptive l1-penalized estimators of the high-dimensional sparse precision matrixeng
dc.typeReporteng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorWIASeng
wgl.subjectMathematikeng
wgl.typeReport / Forschungsbericht / Arbeitspapiereng
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
86965795X.pdf
Size:
522.8 KB
Format:
Adobe Portable Document Format
Description: