A solution to a linear integral equation with an application to statistics of infinitely divisible moving averages

preprint2020arXivOpen access

Abstract

For a stationary moving average random field, a non-parametric low frequency estimator of the Lévy density of its infinitely divisible independently scattered integrator measure is given. The plug-in estimate is based on the solution ww of the linear integral equation v(x)=∫Rdg(s)w(h(s)x)dsv(x) = \int_{\mathbb{R}^d} g(s) w(h(s)x)ds, where g,h:Rd→Rg,h:\mathbb{R}^d \rightarrow \mathbb{R} are given measurable functions and vv is a (weighted) L2L^2-function on R\mathbb{R}. We investigate conditions for the existence and uniqueness of this solution and give L2L^2-error bounds for the resulting estimates. An application to pure jump moving averages and a simulation study round off the paper.

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