Normal approximation for subgraph counts in age-dependent random connection models

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Authors: Christian Hirsch, Raphaël Lachièze-Rey, Takashi Owada
Cited by: 0

Abstract

Abstract We study normal approximation of subgraph counts in a model of spatial scale-free random networks known as the age-dependent random connection model . In the light-tailed regime where only moments of order left parenthesis 2 plus epsilon right parenthesis ( 2 + ε ) $(2+\varepsilon)$ are finite, we study the asymptotic normality of both clique and subtree counts. For clique counts, we establish a multivariate quantitative normal approximation result through the Malliavin–Stein method. In the more delicate case of subtree counts, we obtain distributional convergence based on a central limit theorem for sequences of associated random variables.

Fields of Study & Subjects

Graph Theory and Algorithms Markov Chains and Monte Carlo Methods

Publication details

Journal / source
Advances in Applied Probability
Pages
1–36
Publication date
8 September 2026
Language
EN