Normal approximation for subgraph counts in age-dependent random connection models
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866910943575801856 |
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| author | Hirsch, Christian Lachièze-Rey, Raphaël Owada, Takashi |
| author_facet | Hirsch, Christian Lachièze-Rey, Raphaël Owada, Takashi |
| contents | 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 $(2 + \varepsilon)$ 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_09318 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Normal approximation for subgraph counts in age-dependent random connection models Hirsch, Christian Lachièze-Rey, Raphaël Owada, Takashi Probability 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 $(2 + \varepsilon)$ 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. |
| title | Normal approximation for subgraph counts in age-dependent random connection models |
| topic | Probability |
| url | https://arxiv.org/abs/2505.09318 |