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We combine Malliavin calculus with Stein's method, in order to derive explicit bounds in the Gaussian and Gamma approximations of random variables in a fixed Wiener chaos of a general Gaussian process. We also prove results concerning…

Probability · Mathematics 2008-05-10 Ivan Nourdin , Giovanni Peccati

We combine the method of exchangeable pairs with Stein's method for functional approximation. As a result, we give a general linearity condition under which an abstract Gaussian approximation theorem for stochastic processes holds. We apply…

Probability · Mathematics 2020-10-22 Mikolaj J. Kasprzak

We derive Stein approximation bounds for functionals of uniform random variables, using chaos expansions and the Clark-Ocone representation formula combined with derivation and finite difference operators. This approach covers sums and…

Probability · Mathematics 2018-02-28 Nicolas Privault , Grzegorz Serafin

We combine Stein's method with Malliavin calculus in order to obtain explicit bounds in the multidimensional normal approximation (in the Wasserstein distance) of functionals of Gaussian fields. Our results generalize and refine the main…

Probability · Mathematics 2008-11-19 Ivan Nourdin , Giovanni Peccati , Anthony Réveillac

We develop a functional Stein-Malliavin method in a non-diffusive Poissonian setting, thus obtaining a) quantitative central limit theorems for approximation of arbitrary non-degenerate Gaussian random elements taking values in a separable…

Probability · Mathematics 2023-04-17 Solesne Bourguin , Simon Campese , Thanh Dang

New bounds on the total variation distance between the law of integer valued functionals of possibly non-symmetric and non-homogeneous infinite Rademacher sequences and the Poisson distribution are established. They are based on a…

Probability · Mathematics 2017-07-26 Kai Krokowski

In this PhD thesis, we apply a combination of Malliavin calculus and Stein's method in the framework of probability approximations. The specific problems we tackle with these methods are motivated by probabilistic models in cosmology (Part…

Probability · Mathematics 2024-06-26 Giacomo Giorgio

Berry-Esseen bounds for non-linear functionals of infinite Rademacher sequences are derived by means of the Malliavin-Stein method. Moreover, multivariate extensions for vectors of Rademacher functionals are shown. The results establish a…

Probability · Mathematics 2017-11-06 Kai Krokowski , Anselm Reichenbachs , Christoph Thaele

We propose a new functional analytic approach to Stein's method of exchangeable pairs that does not require the pair at hand to satisfy any approximate linear regression property. We make use of this theory in order to derive abstract…

Probability · Mathematics 2020-08-13 Christian Döbler

We show how to detect optimal Berry--Esseen bounds in the normal approximation of functionals of Gaussian fields. Our techniques are based on a combination of Malliavin calculus, Stein's method and the method of moments and cumulants, and…

Probability · Mathematics 2009-12-09 Ivan Nourdin , Giovanni Peccati

We investigate the multivariate central limit theorem for nonlinear statistics by means of Stein's method and Slepian's smart path interpolation method. Based on certain difference operators in theory of concentration inequalities, we…

Probability · Mathematics 2018-11-14 Nguyen Tien Dung

Stein's method is a method of probability approximation which hinges on the solution of a functional equation. For normal approximation the functional equation is a first order differential equation. Malliavin calculus is an…

Probability · Mathematics 2015-05-11 Louis H. Y. Chen

In this paper we use a Malliavin-Stein type method to investigate Poisson and normal approximations for the measurable functions of infinitely many independent random variables. We combine Stein's method with the difference operators in…

Probability · Mathematics 2018-08-13 Nguyen Tien Dung

In the first part of the paper we use a new Fourier technique to obtain a Stein characterizations for random variables in the second Wiener chaos. We provide the connection between this result and similar conclusions that can be derived…

Probability · Mathematics 2016-01-14 Benjamin Arras , Ehsan Azmoodeh , Guillaume Poly , Yvik Swan

In this paper we develop a framework for multivariate functional approximation by a suitable Gaussian process via an exchangeable pairs coupling that satisfies a suitable approximate linear regression property, thereby building on work by…

Probability · Mathematics 2021-03-25 Christian Döbler , Mikołaj J. Kasprzak

We combine Stein's method with a version of Malliavin calculus on the Poisson space. As a result, we obtain explicit Berry-Ess\'een bounds in Central Limit Theorems (CLTs) involving multiple Wiener-It\^o integrals with respect to a general…

Probability · Mathematics 2008-08-01 Giovanni Peccati , Josep Lluís Solé , Murad S. Taqqu , Frederic Utzet

Stein's method for Gaussian process approximation can be used to bound the differences between the expectations of smooth functionals $h$ of a c\`adl\`ag random process $X$ of interest and the expectations of the same functionals of a well…

Probability · Mathematics 2024-02-15 A. D. Barbour , Nathan Ross , Guangqu Zheng

Quantitative multivariate central limit theorems for general functionals of possibly non-symmetric and non-homogeneous infinite Rademacher sequences are proved by combining discrete Malliavin calculus with the smart path method for normal…

Probability · Mathematics 2017-11-06 Kai Krokowski , Christoph Thaele

In this work, we study the normal approximation and almost sure central limit theorems for some functionals of an independent sequence of Rademacher random variables. In particular, we provide a new chain rule that improves the one derived…

Probability · Mathematics 2018-10-16 Guangqu Zheng

We provide an overview of some recent techniques involving the Malliavin calculus of variations and the so-called ``Stein's method'' for the Gaussian approximations of probability distributions. Special attention is devoted to establishing…

Probability · Mathematics 2009-09-17 Ivan Nourdin , Giovanni Peccati
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