Common Drivers in Sparsely Interacting Hawkes Processes
Statistics Theory
2025-04-08 v1 Statistics Theory
Abstract
We study a multivariate Hawkes process as a model for time-continuous relational event networks. The model does not assume the network to be known, it includes covariates, and it allows for both common drivers, parameters common to all the actors in the network, and also local parameters specific for each actor. We derive rates of convergence for all of the model parameters when both the number of actors and the time horizon tends to infinity. To prevent an exploding network, sparseness is assumed. We also discuss numerical aspects.
Keywords
Cite
@article{arxiv.2504.03916,
title = {Common Drivers in Sparsely Interacting Hawkes Processes},
author = {Alexander Kreiss and Enno Mammen and Wolfgang Polonik},
journal= {arXiv preprint arXiv:2504.03916},
year = {2025}
}