Stein's method for max-stable random vectors

Fuente: arXiv
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Autori principali: Costacèque, Bruno, Decreusefond, Laurent
Natura: Preprint
Pubblicazione: 2025
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author Costacèque, Bruno
Decreusefond, Laurent
author_facet Costacèque, Bruno
Decreusefond, Laurent
contents Motivated by the omnipresence of extreme value distributions in limit theorems involving extremes of random processes, we adapt Stein's method to include these laws as possible target distributions. We do so by using the generator approach of Stein's method, which is possible thanks to a recently introduced family of semi-groups. We study the corresponding Stein solution and its properties when the working distance is either the smooth Wasserstein distance or the Kolmogorov distance. We make use of those results to bound the distance between two max-stable random vectors, as well as to get a rate of convergence for the de Haan-LePage series in smooth Wasserstein distance.
format Preprint
id arxiv_https___arxiv_org_abs_2507_00463
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stein's method for max-stable random vectors
Costacèque, Bruno
Decreusefond, Laurent
Probability
Motivated by the omnipresence of extreme value distributions in limit theorems involving extremes of random processes, we adapt Stein's method to include these laws as possible target distributions. We do so by using the generator approach of Stein's method, which is possible thanks to a recently introduced family of semi-groups. We study the corresponding Stein solution and its properties when the working distance is either the smooth Wasserstein distance or the Kolmogorov distance. We make use of those results to bound the distance between two max-stable random vectors, as well as to get a rate of convergence for the de Haan-LePage series in smooth Wasserstein distance.
title Stein's method for max-stable random vectors
topic Probability
url https://arxiv.org/abs/2507.00463