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Hauptverfasser: Ding, Wen-Yi, Fang, Xiao
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2401.01467
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author Ding, Wen-Yi
Fang, Xiao
author_facet Ding, Wen-Yi
Fang, Xiao
contents Exponential random graph models (ERGMs) are flexible probability models allowing edge dependency. However, it is known that, to a first-order approximation, many ERGMs behave like Erdös-Rényi random graphs, where edges are independent. In this paper, to distinguish ERGMs from Erdös-Rényi random graphs, we consider second-order approximations of ERGMs using two-stars and triangles. We prove that the second-order approximation indeed achieves second-order accuracy in the triangle-free case. The new approximation is formally obtained by Hoeffding decomposition and rigorously justified using Stein's method.
format Preprint
id arxiv_https___arxiv_org_abs_2401_01467
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Second-order Approximation of Exponential Random Graph Models
Ding, Wen-Yi
Fang, Xiao
Probability
Exponential random graph models (ERGMs) are flexible probability models allowing edge dependency. However, it is known that, to a first-order approximation, many ERGMs behave like Erdös-Rényi random graphs, where edges are independent. In this paper, to distinguish ERGMs from Erdös-Rényi random graphs, we consider second-order approximations of ERGMs using two-stars and triangles. We prove that the second-order approximation indeed achieves second-order accuracy in the triangle-free case. The new approximation is formally obtained by Hoeffding decomposition and rigorously justified using Stein's method.
title Second-order Approximation of Exponential Random Graph Models
topic Probability
url https://arxiv.org/abs/2401.01467