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- W4379741417 abstract "We consider an infinite spatial inhomogeneous random graph model with an integrable connection kernel that interpolates nicely between existing spatial random graph models. Key examples are versions of the weight-dependent random connection model, the infinite geometric inhomogeneous random graph, and the age-based random connection model. These infinite models arise as the local limit of the corresponding finite models, see cite{LWC_SIRGs_2020}. For these models we identify the scaling of the emph{local clustering} as a function of the degree of the root in different regimes in a unified way. We show that the scaling exhibits phase transitions as the interpolation parameter moves across different regimes. In addition to the scaling we also identify the leading constants of the clustering function. This allows us to draw conclusions on the geometry of a emph{typical} triangle contributing to the clustering in the different regimes." @default.
- W4379741417 created "2023-06-08" @default.
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- W4379741417 date "2023-06-07" @default.
- W4379741417 modified "2023-09-27" @default.
- W4379741417 title "Scaling of the Clustering Function in Spatial Inhomogeneous Random Graphs" @default.
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- W4379741417 doi "https://doi.org/10.1007/s10955-023-03122-6" @default.
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