$\beta$ models for random hypergraphs with a given degree sequence
Statistics Theory
2014-07-04 v1 Social and Information Networks
Statistics Theory
Abstract
We introduce the beta model for random hypergraphs in order to represent the occurrence of multi-way interactions among agents in a social network. This model builds upon and generalizes the well-studied beta model for random graphs, which instead only considers pairwise interactions. We provide two algorithms for fitting the model parameters, IPS (iterative proportional scaling) and fixed point algorithm, prove that both algorithms converge if maximum likelihood estimator (MLE) exists, and provide algorithmic and geometric ways of dealing the issue of MLE existence.
Cite
@article{arxiv.1407.1004,
title = {$\beta$ models for random hypergraphs with a given degree sequence},
author = {Despina Stasi and Kayvan Sadeghi and Alessandro Rinaldo and Sonja Petrović and Stephen E. Fienberg},
journal= {arXiv preprint arXiv:1407.1004},
year = {2014}
}
Comments
9 pages, 2 figures, Proceedings of 21st International Conference on Computational Statistics (2014), to appear