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Main Authors: Sturm, Anja, Wemheuer, Moritz
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2404.12740
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author Sturm, Anja
Wemheuer, Moritz
author_facet Sturm, Anja
Wemheuer, Moritz
contents We prove a central limit theorem for a certain class of functions on sparse rank-one inhomogeneous random graphs endowed with additional i.i.d. edge and vertex weights. Our proof of the central limit theorem uses a perturbative form of Stein's method and relies on a careful analysis of the local structure of the underlying sparse inhomogeneous random graphs (as the number of vertices in the graph tends to infinity), which may be of independent interest, as well as a local approximation property of the function, which is satisfied for a number of combinatorial optimisation problems. These results extend recent work by Cao (2021) for Erdős-Rényi random graphs and additional i.i.d. weights only on the edges.
format Preprint
id arxiv_https___arxiv_org_abs_2404_12740
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Central Limit Theorem for Functions on Weighted Sparse Inhomogeneous Random Graphs
Sturm, Anja
Wemheuer, Moritz
Probability
We prove a central limit theorem for a certain class of functions on sparse rank-one inhomogeneous random graphs endowed with additional i.i.d. edge and vertex weights. Our proof of the central limit theorem uses a perturbative form of Stein's method and relies on a careful analysis of the local structure of the underlying sparse inhomogeneous random graphs (as the number of vertices in the graph tends to infinity), which may be of independent interest, as well as a local approximation property of the function, which is satisfied for a number of combinatorial optimisation problems. These results extend recent work by Cao (2021) for Erdős-Rényi random graphs and additional i.i.d. weights only on the edges.
title A Central Limit Theorem for Functions on Weighted Sparse Inhomogeneous Random Graphs
topic Probability
url https://arxiv.org/abs/2404.12740