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Malliavin-Stein method for the multivariate compound Hawkes process

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arxiv 2109.07749 v1 pith:MR443GUW submitted 2021-09-16 math.PR

Mahmoud Khabou (IMT) This is my paper · ORCID
classification math.PR
keywords compoundhawkesmultivariateprocessupperboundboundscalculus
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In this paper, we provide upper bounds on the d2 distance between a large class of functionals of a multivariate compound Hawkes process and a given Gaussian vector. This is proven using Malliavin's calculus defined on an underlying Poisson embedding. The upper bound is then used to infer the speed of convergence of Central Limit Theorems for the multivariate compound Hawkes process with exponential kernels as the observation time T goes to infinity.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Spectral clustering for dependent community Hawkes process models of temporal networks

    stat.ML 2025-05 conditional novelty 6.0 of 10

    A non-asymptotic bound is proven for spectral clustering misclustering error in dependent community Hawkes models, and a fast GMM estimator for a restricted model is shown to be consistent.

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