Nonparametric estimation of a shot-noise process

Abstract : We propose an efficient method to estimate in a nonpara-metric 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 γ-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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Communication dans un congrès
SSP 16 - Statistical Signal Processing Workshop, Jun 2016, Palma de Mallorca, Spain. 〈10.1109/SSP.2016.7551709〉
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Soumis le : lundi 19 décembre 2016 - 20:10:36
Dernière modification le : jeudi 10 mai 2018 - 02:05:33

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Paul Ilhe, François Roueff, Eric Moulines, Antoine Souloumiac. Nonparametric estimation of a shot-noise process. SSP 16 - Statistical Signal Processing Workshop, Jun 2016, Palma de Mallorca, Spain. 〈10.1109/SSP.2016.7551709〉. 〈hal-01418963〉

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