Please use this identifier to cite or link to this item:
https://hdl.handle.net/10419/56711
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kappus, Johanna | en |
dc.date.accessioned | 2012-02-16 | - |
dc.date.accessioned | 2012-04-05T16:19:47Z | - |
dc.date.available | 2012-04-05T16:19:47Z | - |
dc.date.issued | 2012 | - |
dc.identifier.uri | http://hdl.handle.net/10419/56711 | - |
dc.description.abstract | For 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 |
dc.language.iso | eng | en |
dc.publisher | |aHumboldt University of Berlin, Collaborative Research Center 649 - Economic Risk |cBerlin | en |
dc.relation.ispartofseries | |aSFB 649 Discussion Paper |x2012-016 | en |
dc.subject.jel | C14 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | statistics of stochastic processes | en |
dc.subject.keyword | low frequency observed Lévy processes | en |
dc.subject.keyword | nonparametric statistics | en |
dc.subject.keyword | adaptive estimation | en |
dc.subject.keyword | model selection with unknown variance | en |
dc.subject.stw | Stochastischer Prozess | en |
dc.subject.stw | Nichtparametrisches Verfahren | en |
dc.subject.stw | Theorie | en |
dc.title | Nonparametric adaptive estimation of linear functionals for low frequency observed Lévy processes | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 68553586X | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
Files in This Item:
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.