Nonparametric adaptive estimation of linear functionals for low frequency observed Lévy processes
dc.contributor.author | Kappus, Johanna | |
dc.date.accessioned | 2017-06-16T00:36:42Z | |
dc.date.available | 2017-06-16T00:36:42Z | |
dc.date.created | 2012-02-23 | |
dc.date.issued | 2012-02-15 | |
dc.date.submitted | 2012-02-15 | |
dc.identifier.issn | 1860-5664 | |
dc.identifier.uri | http://edoc.hu-berlin.de/18452/5043 | |
dc.description.abstract | For a Lévy process X having finite variation on compact sets and finite first moments, µ( dx) = xv( dx) is a finite signed measure which completely describes the jump dynamics. We construct kernel estimators for linear functionals of µ 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. | eng |
dc.language.iso | eng | |
dc.publisher | Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät | |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
dc.subject | Adaptive estimation | eng |
dc.subject | Statistics of stochastic processes | eng |
dc.subject | Low frequency observed Lévy processes | eng |
dc.subject | Nonparametric statistics | eng |
dc.subject | Model selection with unknown variance | eng |
dc.subject.ddc | 330 Wirtschaft | |
dc.title | Nonparametric adaptive estimation of linear functionals for low frequency observed Lévy processes | |
dc.type | workingPaper | |
dc.identifier.urn | urn:nbn:de:kobv:11-100199543 | |
dc.identifier.doi | http://dx.doi.org/10.18452/4391 | |
local.edoc.pages | 39 | |
local.edoc.type-name | Diskussionspapier | |
local.edoc.container-type | series | |
local.edoc.container-type-name | Schriftenreihe | |
local.edoc.container-year | 2012 | |
dc.identifier.zdb | 2195055-6 | |
bua.series.name | Sonderforschungsbereich 649: Ökonomisches Risiko | |
bua.series.issuenumber | 2012,16 |