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Main Authors: Tudor, Ciprian A., Zurcher, Jérémy
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2605.27742
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author Tudor, Ciprian A.
Zurcher, Jérémy
author_facet Tudor, Ciprian A.
Zurcher, Jérémy
contents We derive a multidimensional Stein's method for asymptotic independence in the case of a general target $μ$ with a density, being invariant measure of a diffusion process. It allows us to give a general bound in Wasserstein distance between the law of a couple $(X, Y)$, where $X$ is a random variable, and $Y$ a random vector and $μ\otimes \mathrm{Law}(Y)$. We focus in particular in the case where $X$ and $Y$ are differentiable in the Malliavin sense, by being function of a finite number of stochastic Wiener integrals.
format Preprint
id arxiv_https___arxiv_org_abs_2605_27742
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Multidimensional Stein's method for asymptotic independence with invariant measures of diffusion
Tudor, Ciprian A.
Zurcher, Jérémy
Probability
We derive a multidimensional Stein's method for asymptotic independence in the case of a general target $μ$ with a density, being invariant measure of a diffusion process. It allows us to give a general bound in Wasserstein distance between the law of a couple $(X, Y)$, where $X$ is a random variable, and $Y$ a random vector and $μ\otimes \mathrm{Law}(Y)$. We focus in particular in the case where $X$ and $Y$ are differentiable in the Malliavin sense, by being function of a finite number of stochastic Wiener integrals.
title Multidimensional Stein's method for asymptotic independence with invariant measures of diffusion
topic Probability
url https://arxiv.org/abs/2605.27742