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Related papers: Optimal Bounds in Normal Approximation for Many In…

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Motivated by a theorem of Barbour, we revisit some of the classical limit theorems in probability from the viewpoint of the Stein method. We setup the framework to bound Wasserstein distances between some distributions on infinite…

Probability · Mathematics 2018-07-30 Laure Coutin , Laurent Decreusefond

Gradient flow in the 2-Wasserstein space is widely used to optimize functionals over probability distributions and is typically implemented using an interacting particle system with $n$ particles. Analyzing these algorithms requires showing…

Machine Learning · Computer Science 2026-03-27 Chandan Tankala , Dheeraj M. Nagaraj , Anant Raj

We provide explicit bounds on the Wasserstein distance between discrete time martingales and the standard normal distribution. The proofs are based on a combination of Lindeberg's and Stein's method.

Probability · Mathematics 2018-08-14 Adrian Röllin

We refine the classical Lindeberg-Feller central limit theorem by obtaining asymptotic bounds on the Kolmogorov distance, the Wasserstein distance, and the parametrized Prokhorov distances in terms of a Lindeberg index. We thus obtain more…

Probability · Mathematics 2016-12-26 Ben Berckmoes , Geert Molenberghs

In this paper, we study a mean-field spin model with three- and two-body interactions. In a recent paper by Contucci, Mingione and Osabutey, the equilibrium measure for large volumes was shown to have three pure states, two with opposite…

Probability · Mathematics 2024-04-12 Peter Eichelsbacher

We provide a general result for bounding the difference between point probabilities of integer supported distributions and the translated Poisson distribution, a convenient alternative to the discretized normal. We illustrate our theorem in…

Probability · Mathematics 2017-12-05 A. D. Barbour , Adrian Röllin , Nathan Ross

Recent progress has been made in establishing normal approximation bounds in terms of the Wasserstein-$p$ distance for i.i.d. and locally dependent random variables. However, for $p > 1$, no such results have been demonstrated for dependent…

Probability · Mathematics 2025-02-25 Tianle Liu , Morgane Austern

We obtain bounds to quantify the distributional approximation in the delta method for vector statistics (the sample mean of $n$ independent random vectors) for normal and non-normal limits, measured using smooth test functions. For normal…

Statistics Theory · Mathematics 2023-05-11 Robert E. Gaunt , Heather Sutcliffe

In \cite{n-p-noncentral}, Nourdin and Peccati established a neat characterization of Gamma approximation on a fixed Wiener chaos in terms of convergence of only the third and fourth cumulants. In this paper, we provide an optimal rate of…

Probability · Mathematics 2019-02-08 Ehsan Azmoodeh , Peter Eichelsbacher , Lukas Knichel

Applying an inductive technique for Stein and zero bias couplings yields Berry-Esseen theorems for normal approximation for two new examples. The conditions of the main results do not require that the couplings be bounded. Our two…

Probability · Mathematics 2020-05-12 Louis H. Y. Chen , Larry Goldstein , Adrian Röllin

We introduce a version of Stein's method of comparison of operators specifically tailored to the problem of bounding the Wasserstein-1 distance between continuous and discrete distributions on the real line. Our approach rests on a new…

Probability · Mathematics 2023-11-03 Gilles Germain , Yvik Swan

We propose a mean-field optimal control problem for the parameter identification of a given pattern. The cost functional is based on the Wasserstein distance between the probability measures of the modeled and the desired patterns. The…

Optimization and Control · Mathematics 2021-04-08 Martin Burger , Lisa Maria Kreusser , Claudia Totzeck

We consider distributional approximation by generalized Dickman distributions, which appear in number theory, perpetuities, logarithmic combinatorial structures and many other areas. We prove bounds in the Kolmogorov distance for the…

Probability · Mathematics 2022-11-21 Chinmoy Bhattacharjee , Matthias Schulte

By a delicate analysis for the Stein's equation associated to the $\alpha$-stable law approximation with $\alpha \in (0,2)$, we prove a quantitative stable central limit theorem in Wasserstein type distance, which generalizes the results in…

Probability · Mathematics 2023-01-26 Peng Chen , Ivan Nourdin , Lihu Xu , Xiaochuan Yang

One major obstacle in applications of Stein's method for compound Poisson approximation is the availability of so-called magic factors (bounds on the solution of the Stein equation) with favourable dependence on the parameters of the…

Probability · Mathematics 2017-06-30 Fraser Daly

We use Stein's method to prove a generalization of the Lindeberg-Feller CLT providing an upper and a lower bound for the superior limit of the Kolmogorov distance between a normally distributed random variable and the rowwise sums of a…

Probability · Mathematics 2011-12-30 Ben Berckmoes , Bob Lowen , Jan Van Casteren

We prove a new class of inequalities, yielding bounds for the normal approximation in the Wasserstein and the Kolmogorov distance of functionals of a general Poisson process (Poisson random measure). Our approach is based on an iteration of…

Probability · Mathematics 2014-01-30 Günter Last , Giovanni Peccati , Matthias Schulte

Motivated by several applications, including neuronal models, we consider the McKean-Vlasov limit for mean-field systems of interacting diffusions with simultaneous jumps. We prove propagation of chaos via a coupling technique that involves…

Probability · Mathematics 2017-04-05 Luisa Andreis , Paolo Dai Pra , Markus Fischer

We develop techniques for determining an explicit Berry-Esseen bound in the Kolmogorov distance for the normal approximation of a ratio of Gaussian functionals. We provide an upper bound in terms of the third and fourth cumulants, using…

Probability · Mathematics 2023-12-07 Khalifa Es-Sebaiy , Fares Alazemi

Since the introduction of Stein's method in the early 1970s, much research has been done in extending and strengthening it; however, there does not exist a version of Stein's original method of exchangeable pairs for multivariate normal…

Probability · Mathematics 2010-05-18 Sourav Chatterjee , Elizabeth Meckes