Abstract
We define a class of growing networks in which new nodes are given a spatial position and are connected to existing nodes with a probability mechanism favoring short distances and high degrees. The competition of preferential attachment and spatial clustering gives this model a range of interesting properties. Empirical degree distributions converge to a limit law, which can be a power law with any exponent
Citation
Emmanuel Jacob. Peter Mörters. "Spatial preferential attachment networks: Power laws and clustering coefficients." Ann. Appl. Probab. 25 (2) 632 - 662, April 2015. https://doi.org/10.1214/14-AAP1006
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