Désempilement non-paramétrique de la densité d'un processus shot-noise

Abstract : In this paper, we propose an efficient method to estimate in a nonparametric fashion the marks' density of a shot-noise process in presence of pileup from a sample of low-frequency observations. Based on a functional equation linking the marks' density to the characteristic function of the observations and its derivative, we propose a new time-efficient method using B-splines to estimate the density of the underlying gamma-ray spectrum, which is able to handle large datasets used in nuclear physics. A discussion on the numerical computation of the algorithm and its performances on simulated data are provided to support our findings.
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Paul Ilhe, François Roueff, Eric Moulines, Antoine Souloumiac. Désempilement non-paramétrique de la densité d'un processus shot-noise. 48èmes Journées de Statistique de la SFdS, Société Française de Statistique, May 2016, Montpellier, France. ⟨hal-02287434⟩

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