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Related papers: Donsker's theorem in {Wasserstein}-1 distance

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This paper provides estimates for the convergence rate of the total variation distance in the framework of the Breuer-Major theorem, assuming some smoothness properties of the underlying function. The results are proved by applying new…

Probability · Mathematics 2018-07-26 David Nualart , Hongjuan Zhou

We obtain the convergence in law of a sequence of excited (also called cookies) random walks toward an excited Brownian motion. This last process is a continuous semi-martingale whose drift is a function, say $\phi$, of its local time. It…

Probability · Mathematics 2011-08-22 Olivier Raimond , Bruno Schapira

Using a characterizing equation for the Beta distribution, Stein's method is applied to obtain bounds of the optimal order for the Wasserstein distance between the distribution of the scaled number of white balls drawn from a…

Probability · Mathematics 2013-01-03 Larry Goldstein , Gesine Reinert

For martingales with a wide range of integrability, we will quantify the rate of convergence of the central limit theorem via Wasserstein distances of order $r$, $1\le r\le 3$. Our bounds are in terms of Lyapunov's coefficients and the…

Probability · Mathematics 2024-07-25 Xiaoqin Guo

We present a study of the distance between a Brownian motion and a submanifold of a complete Riemannian manifold. We include a variety of results, including an inequality for the Laplacian of the distance function derived from a Jacobian…

Probability · Mathematics 2016-04-19 James Thompson

Continuous Time Markov Chains, Hawkes processes and many other interesting processes can be described as solution of stochastic differential equations driven by Poisson measures. Previous works, using the Stein's method, give the…

Probability · Mathematics 2026-04-02 Eustache Besançon , Laure Coutin , Laurent Decreusefond , Pascal Moyal

We consider the dispersive logarithmic Schr{\"o}dinger equation in a semi-classical scaling. We extend the results about the large time behaviour of the solution (dispersion faster than usual with an additional logarithmic factor,…

Analysis of PDEs · Mathematics 2021-03-24 Guillaume Ferriere

This article is dedicated to the estimation of Wasserstein distances and Wasserstein costs between two distinct continuous distributions $F$ and $G$ on $\mathbb R$. The estimator is based on the order statistics of (possibly dependent)…

Statistics Theory · Mathematics 2017-10-31 Philippe Berthet , Jean-Claude Fort , Thierry Klein

Owing to the Chapman-Kolmogorov equation for Markovian dynamics,any equilibrium trajectory of a Brownian particle in a solvent fluid can be viewed as the superposition of an uncountable number of non-equilibrium states. This property…

Statistical Mechanics · Physics 2026-05-18 Jason Boynewicz , Michael C. Thumann , Giuseppe Procopio , Massimiliano Giona

We develop Stein's method for the half-normal distribution and apply it to derive rates of convergence in distributional limit theorems for three statistics of the simple symmetric random walk: the maximum value, the number of returns to…

Probability · Mathematics 2015-11-24 Christian Döbler

In the first paper of this series, I investigated whether a wavefunction model of a heavy particle and a collection of light particles might generate "Brownian-Motion-Like" trajectories of the heavy particle. I concluded that it was…

Quantum Physics · Physics 2023-08-04 W. David Wick

We discuss the classical problem of measuring the regularity of distribution of sets of $N$ points in $\mathbb{T}^d$. A recent line of investigation is to study the cost ($=$ mass $\times$ distance) necessary to move Dirac measures placed…

Classical Analysis and ODEs · Mathematics 2020-09-29 Louis Brown , Stefan Steinerberger

We consider a one-dimensional Brownian motion of fixed duration $T$. Using a path-integral technique, we compute exactly the probability distribution of the difference $\tau=t_{\min}-t_{\max}$ between the time $t_{\min}$ of the global…

Statistical Mechanics · Physics 2020-05-13 Francesco Mori , Satya N. Majumdar , Gregory Schehr

In order to approximate the exit time of a one-dimensional diffusion process, we propose an algorithm based on a random walk. Such an algorithm was already introduced in both the Brownian context and in the Ornstein-Uhlenbeck context. Here…

Probability · Mathematics 2019-12-12 Samuel Herrmann , Nicolas Massin

The adapted Wasserstein distance is a metric for quantifying distributional uncertainty and assessing the sensitivity of stochastic optimization problems on time series data. A computationally efficient alternative to it, is provided by the…

Optimization and Control · Mathematics 2025-10-10 Beatrice Acciaio , Songyan Hou , Gudmund Pammer

The aim of this paper is to develop a sequence of discrete approximations to a one-dimensional It\^o diffusion that almost surely converges to a weak solution of the given stochastic differential equation. Under suitable conditions, the…

Probability · Mathematics 2014-03-27 John van der Hoek , Tamas Szabados

We obtain explicit Berry-Esseen bounds in the Kolmogorov distance for the normal approximation of non-linear functionals of vectors of independent random variables. Our results are based on the use of Stein's method and of random difference…

Probability · Mathematics 2015-05-19 Raphaël Lachièze-Rey , Giovanni Peccati

We derive a Benamou-Brenier type dynamical formulation for the Wasserstein metric $\mathsf W_p$ between stationary random measures recently introduced in [EHJM23]. A key step is a reformulation of the metric $\mathsf W_p$ using Palm…

Probability · Mathematics 2024-02-08 Martin Huesmann , Bastian Müller

We consider a $d$-dimensional stochastic differential equation (SDE) of the form $d U_t = b(U_t) dt + \sigma\,d Z_t$, let $X_t$ be the solution if the driving noise $Z_t$ is a $d$-dimensional rotationally symmetric $\alpha$-stable process…

Probability · Mathematics 2025-11-25 Changsong Deng , Xiang Li , Rene L. Schilling , Lihu Xu

We introduce a modified Benamou-Brenier type approach leading to a Wasserstein type distance that allows global invariance, specifically, isometries, and we show that the problem can be summarized to orthogonal transformations. This…

Machine Learning · Statistics 2025-03-24 Kevine Meugang Toukam
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