An oracle inequality for penalised projection estimation of Lévy densities from high-frequency observations
Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Ueltzhöfer, F., Klüppelberg, C.
Abstract:
We consider a multivariate Lévy process given by the sum of a Brownian motion
with drift and an independent time-homogeneous pure jump process governed
by a Lévy density. We assume that observation of a sample path takes place on
an equidistant discrete time grid. Following Grenander’s method of sieves, we
construct families of non-parametric projection estimators for the restriction of
a Lévy density to bounded sets away from the origin. Moreover, we introduce a
data-driven penalisation criterion to select an estimator within a given family,
where we measure the estimation error in an L2-norm. We furthermore give
sufficient conditions on the penalty such that an oracle inequality holds. As
an application we prove adaptiveness for sufficiently smooth Lévy densities in
some Sobolev space and explicitly derive the rate of convergence.
This is a preprint of an article whose final and definitive form has been published in the Journal
of Nonparametric Statistics (2011)
c Taylor & Francis; The Journal of Nonparametric Statistics is
available online at: http://www.informaworld.com/smpp/ — The final form of this article is available
online as of 30 June 2011: http://www.tandfonline.com/doi/abs/10.1080/10485252.2011.581375