Extremal independence in discrete random systems

Fuente: arXiv
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Main Authors: Isaev, Mikhail, Rodionov, Igor, Zhang, Rui-Ray, Zhukovskii, Maksim
Format: Preprint
Published: 2021
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author Isaev, Mikhail
Rodionov, Igor
Zhang, Rui-Ray
Zhukovskii, Maksim
author_facet Isaev, Mikhail
Rodionov, Igor
Zhang, Rui-Ray
Zhukovskii, Maksim
contents Let $\mathbf{X}(n) \in \mathbb{R}^d$ be a sequence of random vectors, where $n\in\mathbb{N}$ and $d = d(n)$. Under certain weakly dependence conditions, we prove that the distribution of the maximal component of $\mathbf{X}$ and the distribution of the maximum of their independent copies are asymptotically equivalent. Our result on extremal independence relies on new lower and upper bounds for the probability that none of a given finite set of events occurs. As applications, we obtain the distribution of various extremal characteristics of random discrete structures such as maximum codegree in binomial random hypergraphs and the maximum number of cliques sharing a given vertex in binomial random graphs. We also generalise Berman-type conditions for a sequence of Gaussian random vectors to possess the extremal independence property.
format Preprint
id arxiv_https___arxiv_org_abs_2105_04917
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Extremal independence in discrete random systems
Isaev, Mikhail
Rodionov, Igor
Zhang, Rui-Ray
Zhukovskii, Maksim
Probability
Combinatorics
Let $\mathbf{X}(n) \in \mathbb{R}^d$ be a sequence of random vectors, where $n\in\mathbb{N}$ and $d = d(n)$. Under certain weakly dependence conditions, we prove that the distribution of the maximal component of $\mathbf{X}$ and the distribution of the maximum of their independent copies are asymptotically equivalent. Our result on extremal independence relies on new lower and upper bounds for the probability that none of a given finite set of events occurs. As applications, we obtain the distribution of various extremal characteristics of random discrete structures such as maximum codegree in binomial random hypergraphs and the maximum number of cliques sharing a given vertex in binomial random graphs. We also generalise Berman-type conditions for a sequence of Gaussian random vectors to possess the extremal independence property.
title Extremal independence in discrete random systems
topic Probability
Combinatorics
url https://arxiv.org/abs/2105.04917