@techreport{Kappus2012Nonparametric,
abstract = {For a L\'{e}vy 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.},
address = {Berlin},
author = {Johanna Kappus},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C14; 330; statistics of stochastic processes; low frequency observed L\'{e}vy processes; nonparametric statistics; adaptive estimation; model selection with unknown variance; Stochastischer Prozess; Nichtparametrisches Verfahren; Theorie},
language = {eng},
number = {2012-016},
publisher = {SFB 649, Economic Risk},
title = {Nonparametric adaptive estimation of linear functionals for low frequency observed L\'{e}vy processes},
type = {SFB 649 discussion paper},
url = {http://hdl.handle.net/10419/56711},
year = {2012}
}
