A kernel type nonparametric density estimator for decompounding

dc.creatorvan Es, Bert
dc.creatorGugushvili, Shota
dc.creatorSpreij, Peter
dc.date2005-05-17
dc.date2007-09-05
dc.date.accessioned2026-07-07T08:29:13Z
dc.date.available2026-07-07T08:29:13Z
dc.descriptionGiven a sample from a discretely observed compound Poisson process, we consider estimation of the density of the jump sizes. We propose a kernel type nonparametric density estimator and study its asymptotic properties. An order bound for the bias and an asymptotic expansion of the variance of the estimator are given. Pointwise weak consistency and asymptotic normality are established. The results show that, asymptotically, the estimator behaves very much like an ordinary kernel estimator.
dc.descriptionPublished at http://dx.doi.org/10.3150/07-BEJ6091 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)
dc.identifierhttps://arxiv.org/abs/math/0505355
dc.identifierhttp://arxiv.org/abs/math/0505355
dc.identifierBernoulli 2007, Vol. 13, No. 3, 672-694
dc.identifierdoi:10.3150/07-BEJ6091
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/137892
dc.subjectStatistics Theory
dc.titleA kernel type nonparametric density estimator for decompounding
dc.typetext

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