Normal approximation of Functionals of Point Processes: Application to Hawkes Processes

Fuente: arXiv
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Autores principales: Coutin, Laure, Massat, Benjamin, Réveillac, Anthony
Formato: Preprint
Publicado: 2024
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author Coutin, Laure
Massat, Benjamin
Réveillac, Anthony
author_facet Coutin, Laure
Massat, Benjamin
Réveillac, Anthony
contents In this paper, we derive an explicit upper bound for the Wasserstein distance between a functional of point processes and a Gaussian distribution. Using Stein's method in conjunction with Malliavin's calculus and the Poisson embedding representation, our result applies to a variety of point processes including discrete and continuous Hawkes processes. In particular, we establish an explicit convergence rate for stable continuous non-linear Hawkes processes and for discrete Hawkes processes. Finally, we obtain an upper bound in the context of nearly unstable Hawkes processes.
format Preprint
id arxiv_https___arxiv_org_abs_2407_19806
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Normal approximation of Functionals of Point Processes: Application to Hawkes Processes
Coutin, Laure
Massat, Benjamin
Réveillac, Anthony
Probability
In this paper, we derive an explicit upper bound for the Wasserstein distance between a functional of point processes and a Gaussian distribution. Using Stein's method in conjunction with Malliavin's calculus and the Poisson embedding representation, our result applies to a variety of point processes including discrete and continuous Hawkes processes. In particular, we establish an explicit convergence rate for stable continuous non-linear Hawkes processes and for discrete Hawkes processes. Finally, we obtain an upper bound in the context of nearly unstable Hawkes processes.
title Normal approximation of Functionals of Point Processes: Application to Hawkes Processes
topic Probability
url https://arxiv.org/abs/2407.19806