EconStor >
Humboldt-Universität zu Berlin >
Sonderforschungsbereich 649: Ökonomisches Risiko, Humboldt-Universität Berlin >
SFB 649 Discussion Papers, HU Berlin >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/56711
  

Full metadata record

DC FieldValueLanguage
dc.contributor.authorKappus, Johannaen_US
dc.date.accessioned2012-02-16en_US
dc.date.accessioned2012-04-05T16:19:47Z-
dc.date.available2012-04-05T16:19:47Z-
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/10419/56711-
dc.description.abstractFor a Lévy process X having finite variation on compact sets and finite first moments, u (dx) = xv (dx) is a finite signed measure which completely describes the jump dynamics. We construct kernel estimators for linear functionals of u and provide rates of convergence under regularity assumptions. Moreover, we consider adaptive estimation via model selection and propose a new strategy for the data driven choice of the smoothing parameter.en_US
dc.language.isoengen_US
dc.publisherSFB 649, Economic Risk Berlinen_US
dc.relation.ispartofseriesSFB 649 discussion paper 2012-016en_US
dc.subject.jelC14en_US
dc.subject.ddc330en_US
dc.subject.keywordstatistics of stochastic processesen_US
dc.subject.keywordlow frequency observed Lévy processesen_US
dc.subject.keywordnonparametric statisticsen_US
dc.subject.keywordadaptive estimationen_US
dc.subject.keywordmodel selection with unknown varianceen_US
dc.subject.stwStochastischer Prozessen_US
dc.subject.stwNichtparametrisches Verfahrenen_US
dc.subject.stwTheorieen_US
dc.titleNonparametric adaptive estimation of linear functionals for low frequency observed Lévy processesen_US
dc.typeWorking Paperen_US
dc.identifier.ppn68553586Xen_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:SFB 649 Discussion Papers, HU Berlin

Files in This Item:
File Description SizeFormat
68553586X.pdf435.11 kBAdobe PDF
No. of Downloads: Counter Stats
Show simple item record
Download bibliographical data as: BibTeX

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.