Statistical Models for Degree Distributions of Networks
Statistics Theory
2014-11-17 v1 Machine Learning
Statistics Theory
Abstract
We define and study the statistical models in exponential family form whose sufficient statistics are the degree distributions and the bi-degree distributions of undirected labelled simple graphs. Graphs that are constrained by the joint degree distributions are called -graphs in the computer science literature and this paper attempts to provide the first statistically grounded analysis of this type of models. In addition to formalizing these models, we provide some preliminary results for the parameter estimation and the asymptotic behaviour of the model for degree distribution, and discuss the parameter estimation for the model for bi-degree distribution.
Keywords
Cite
@article{arxiv.1411.3825,
title = {Statistical Models for Degree Distributions of Networks},
author = {Kayvan Sadeghi and Alessandro Rinaldo},
journal= {arXiv preprint arXiv:1411.3825},
year = {2014}
}
Comments
13 pages. 4 figures, a shorter version to be presented at NIPS workshop 2014