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Cumulant method for weighted random connection models (2311.00600v1)
Published 1 Nov 2023 in math.PR
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 $\alpha$-determinantal processes.
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