Phase Transitions in Edge-Weighted Exponential Random Graphs: Near-Degeneracy and Universality
Abstract
Conventionally used exponential random graphs cannot directly model weighted networks as the underlying probability space consists of simple graphs only. Since many substantively important networks are weighted, this limitation is especially problematic. We extend the existing exponential framework by proposing a generic common distribution for the edge weights. Minimal assumptions are placed on the distribution, that is, it is non-degenerate and supported on the unit interval. By doing so, we recognize the essential properties associated with near-degeneracy and universality in edge-weighted exponential random graphs.
Keywords
Cite
@article{arxiv.1706.02163,
title = {Phase Transitions in Edge-Weighted Exponential Random Graphs: Near-Degeneracy and Universality},
author = {Ryan DeMuse and Danielle Larcomb and Mei Yin},
journal= {arXiv preprint arXiv:1706.02163},
year = {2019}
}
Comments
15 pages, 4 figures. This article extends arXiv:1607.04084, which derives general formulas for the normalization constant and characterizes phase transitions in exponential random graphs with uniformly distributed edge weights. The present article places minimal assumptions on the edge-weight distribution, thereby recognizing essential properties associated with near-degeneracy and universality