Quantifying structure in networks
Disordered Systems and Neural Networks
2016-04-08 v1
Abstract
We investigate exponential families of random graph distributions as a framework for systematic quantification of structure in networks. In this paper we restrict ourselves to undirected unlabeled graphs. For these graphs, the counts of subgraphs with no more than k links are a sufficient statistics for the exponential families of graphs with interactions between at most k links. In this framework we investigate the dependencies between several observables commonly used to quantify structure in networks, such as the degree distribution, cluster and assortativity coefficients.
Cite
@article{arxiv.0912.4450,
title = {Quantifying structure in networks},
author = {Eckehard Olbrich and Thomas Kahle and Nils Bertschinger and Nihat Ay and Juergen Jost},
journal= {arXiv preprint arXiv:0912.4450},
year = {2016}
}
Comments
17 pages, 3 figures