Statistical Models for Degree Distributions of Networks

2014/11/14 by Kayvan Sadeghi, Alessandro Rinaldo, Sadeghi, Kayvan +1
Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Graph theory and applications #Limits and Structures in Graph Theory #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Topological and Geometric Data Analysis

paper · pdf · doi:10.48550/arxiv.1411.3825

openalex publication_date 2014/11/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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 dK-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.

Citations

• The Structure and Function of Complex Networks

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