Graph connectivity with fixed endpoints in the random-connection model
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arXiv
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| Format: | Preprint |
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2023
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| _version_ | 1866912459016634368 |
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| author | Liu, Qingwei Privault, Nicolas |
| author_facet | Liu, Qingwei Privault, Nicolas |
| contents | We consider the count of subgraphs with an arbitrary configuration of endpoints in the random-connection model based on a Poisson point process on ${\Bbb R}^d$. We present combinatorial expressions for the computation of the cumulants and moments of all orders of such subgraph counts, which allow us to estimate the growth of cumulants as the intensity of the underlying Poisson point process goes to infinity. As a consequence, we obtain a central limit theorem with explicit convergence rates under the Kolmogorov distance, and connectivity bounds. Numerical examples are presented using a computer code in SageMath for the closed-form computation of cumulants of any order, for any type of connected subgraph and for any configuration of endpoints in any dimension $d\geq 1$. In particular, graph connectivity estimates, Gram-Charlier expansions for density estimation, and correlation estimates for joint subgraph counting are obtained. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_12745 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Graph connectivity with fixed endpoints in the random-connection model Liu, Qingwei Privault, Nicolas Probability Combinatorics 60D05, 05C80, 60G55, 60F05 We consider the count of subgraphs with an arbitrary configuration of endpoints in the random-connection model based on a Poisson point process on ${\Bbb R}^d$. We present combinatorial expressions for the computation of the cumulants and moments of all orders of such subgraph counts, which allow us to estimate the growth of cumulants as the intensity of the underlying Poisson point process goes to infinity. As a consequence, we obtain a central limit theorem with explicit convergence rates under the Kolmogorov distance, and connectivity bounds. Numerical examples are presented using a computer code in SageMath for the closed-form computation of cumulants of any order, for any type of connected subgraph and for any configuration of endpoints in any dimension $d\geq 1$. In particular, graph connectivity estimates, Gram-Charlier expansions for density estimation, and correlation estimates for joint subgraph counting are obtained. |
| title | Graph connectivity with fixed endpoints in the random-connection model |
| topic | Probability Combinatorics 60D05, 05C80, 60G55, 60F05 |
| url | https://arxiv.org/abs/2312.12745 |