Cumulant method for weighted random connection models
Probability
2023-11-02 v1
Abstract
In this paper, we derive cumulant bounds for subgraph counts and power-weighted edge length in a class of spatial random networks known as weighted random connection models. This involves dealing with long-range spatial correlations induced by the profile function and the weight distribution. We start by deriving the bounds for the classical case of a Poisson vertex set, and then provide extensions to -determinantal processes.
Cite
@article{arxiv.2311.00600,
title = {Cumulant method for weighted random connection models},
author = {Nils Heerten and Christian Hirsch and Moritz Otto},
journal= {arXiv preprint arXiv:2311.00600},
year = {2023}
}