Normal approximation for subgraph counts in age-dependent random connection models
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.
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Authors: Christian Hirsch, Raphaël Lachièze-Rey, Takashi Owada
Institutions: Université Paris Cité, Sorbonne Paris Cité, Aarhus University, Purdue University West Lafayette, Institut national de recherche en sciences et technologies du numérique, Département mathématiques, informatique, sciences de la donnée et technologies du numérique, Mathématiques Appliquées à Paris 5