Analysis shows Poisson point process convergence in edge crossings and a central limit theorem for stress.
We consider the number of edge crossings in a random graph drawing generated by projecting a random geometric graph on some compact convex set W⊂ Rᵈ , d≥ 3 , onto a plane. The positions of these crossings form the support of a point process. We show that if the expected number of crossings converges to a positive but finite value, this point process converges to a Poisson point process in the Kantorovich–Rubinstein distance. We further show a multivariate central limit theorem between the number of crossings and a second variable called the stress that holds when the expected vertex degree in the random geometric graph converges to a positive finite value.
No takes yet. Share an insight, caveat, or question.
Döring et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: