Conditional central limit theorems for exponential random graphs

Fuente: arXiv
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Autori principali: Fang, Xiao, Liu, Song-Hao, Su, Zhonggen, Wang, Xiaolin
Natura: Preprint
Pubblicazione: 2025
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_version_ 1866916799046483968
author Fang, Xiao
Liu, Song-Hao
Su, Zhonggen
Wang, Xiaolin
author_facet Fang, Xiao
Liu, Song-Hao
Su, Zhonggen
Wang, Xiaolin
contents In this paper, we study the Exponential Random Graph Models (ERGMs) conditioning on the number of edges. In subcritical region of model parameters, we prove a conditional Central Limit Theorem (CLT) with explicit mean and variance for the number of two stars. This generalizes the corresponding result in the literature for the Erdős--Rényi random graph. To prove our main result, we develop a new conditional CLT via exchangeable pairs based on the ideas of Dey and Terlov. Our key technical contributions in the application to ERGMs include establishing a linearity condition for an exchangeable pair involving two star counts, a local CLT for edge counts, as well as new higher-order concentration inequalities. Our approach also works for general subgraph counts, and we give a conjectured form of their conditional CLT.
format Preprint
id arxiv_https___arxiv_org_abs_2506_15159
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Conditional central limit theorems for exponential random graphs
Fang, Xiao
Liu, Song-Hao
Su, Zhonggen
Wang, Xiaolin
Probability
60F05, 05C80
In this paper, we study the Exponential Random Graph Models (ERGMs) conditioning on the number of edges. In subcritical region of model parameters, we prove a conditional Central Limit Theorem (CLT) with explicit mean and variance for the number of two stars. This generalizes the corresponding result in the literature for the Erdős--Rényi random graph. To prove our main result, we develop a new conditional CLT via exchangeable pairs based on the ideas of Dey and Terlov. Our key technical contributions in the application to ERGMs include establishing a linearity condition for an exchangeable pair involving two star counts, a local CLT for edge counts, as well as new higher-order concentration inequalities. Our approach also works for general subgraph counts, and we give a conjectured form of their conditional CLT.
title Conditional central limit theorems for exponential random graphs
topic Probability
60F05, 05C80
url https://arxiv.org/abs/2506.15159