Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/56711
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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.publisher|aSFB 649, Economic Risk |cBerlinen_US
dc.relation.ispartofseries|aSFB 649 discussion paper |x2012-016en_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

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