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.
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