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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 pile-up 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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Submitted on : Monday, January 13, 2020 - 11:09:28 PM
Last modification on : Friday, February 18, 2022 - 3:09:09 AM
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Paul Ilhe, François Roueff, Éric Moulines, Antoine Souloumiac. Nonparametric estimation of a shot-noise process. SSP 16 - Statistical Signal Processing Workshop, IEEE Signal Processing Society, Jun 2016, Palma de Mallorca, Spain. pp.7551709, ⟨10.1109/SSP.2016.7551709⟩. ⟨hal-01418963⟩



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