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We derive normal approximation bounds in the Kolmogorov distance for sums of discrete multiple integrals and $U$-statistics made of independent Bernoulli random variables. Such bounds are applied to normal approximation for the renormalized…

Probability · Mathematics 2018-06-15 Nicolas Privault , Grzegorz Serafin

Under Poincar\'e-type conditions, upper bounds are explored for the Kolmogorov distance between the distributions of weighted sums of dependent summands and the normal law. Based on improved concentration inequalities on high-dimensional…

Probability · Mathematics 2020-11-19 S. G. Bobkov , G. P. Chistyakov , F. Götze

We use Stein's method to establish the rates of normal approximation in terms of the total variation distance for a large class of sums of score functions of marked Poisson point processes on $\mathbb{R}^d$. As in the study under the weaker…

Probability · Mathematics 2020-11-17 Tianshu Cong , Aihua Xia

We provide a bound on a natural distance between finitely and infinitely supported elements of the unit sphere of $\ell^2(\mathbb{N}^*)$, the space of real valued sequences with finite $\ell^2$ norm. We use this bound to estimate the…

Probability · Mathematics 2019-08-20 Benjamin Arras , Ehsan Azmoodeh , Guillaume Poly , Yvik Swan

On any denumerable product of probability spaces, we construct a Malliavin gradient and then a divergence and a number operator. This yields a Dirichlet structure which can be shown to approach the usual structures for Poisson and Brownian…

Probability · Mathematics 2018-07-30 Laurent Decreusefond , Hélène Halconruy

We provide a generalisation of Pinelis' Rademacher-Gaussian tail comparison to complex coefficients. We also establish uniform bounds on the probability that the magnitude of weighted sums of independent random vectors uniform on Euclidean…

Probability · Mathematics 2022-03-15 Giorgos Chasapis , Ruoyuan Liu , Tomasz Tkocz

Linear statistics of eigenvalues in many familiar classes of random matrices are known to obey gaussian central limit theorems. The proofs of such results are usually rather difficult, involving hard computations specific to the model in…

Probability · Mathematics 2007-11-25 Sourav Chatterjee

We introduce a carr\'e du champ operator for Banach-valued random elements, taking values in the projective tensor product, and use it to control the bounded Lipschitz distance between a Malliavin-smooth random element satisfying mild…

Probability · Mathematics 2026-04-03 Solesne Bourguin , Simon Campese

This paper establishes an upper bound for the Kolmogorov distance between the maximum of a high-dimensional vector of smooth Wiener functionals and the maximum of a Gaussian random vector. As a special case, we show that the maximum of…

Statistics Theory · Mathematics 2019-02-07 Yuta Koike

We establish a general inequality on the Poisson space, yielding an upper bound for the distance in total variation between the law of a regular random variable with values in the integers and a Poisson distribution. Several applications…

Probability · Mathematics 2012-04-18 Giovanni Peccati

This article compares the distributions of integer-valued random variables and Poisson random variables. It considers the total variation and the Wasserstein distance and provides, in particular, explicit bounds on the pointwise difference…

Probability · Mathematics 2021-04-07 Federico Pianoforte , Matthias Schulte

This paper deals with bilateral-gamma (BG) approximation to functionals of an isonormal Gaussian process. We use Malliavin-Stein method to obtain the error bounds for the smooth Wasserstein distance. As by-products, the error bounds for…

Probability · Mathematics 2024-10-01 Kalyan Barman , Tomoyuki Ichiba , Palaniappan Vellaisamy

We derive explicit distance bounds for Stratonovich iterated integrals along two Gaussian processes (also known as signatures of Gaussian rough paths) based on the regularity assumption of their covariance functions. Similar estimates have…

Probability · Mathematics 2012-08-03 Sebastian Riedel , Weijun Xu

We prove the chain rule in the more general framework of the Wiener-Poisson space, allowing us to obtain the so-called Nourdin-Peccati bound. From this bound we obtain a second-order Poincare-type inequality that is useful in terms of…

Probability · Mathematics 2017-12-13 Juan Jose Viquez R

In this paper we provide a new explicit bound on the total variation distance between a standardized partial sum of random variables belonging to a finite sum of Wiener chaoses and a standard normal random variable. We apply our result to…

Probability · Mathematics 2025-06-17 Khalifa Es-Sebaiy

The paper is devoted to a comprehensive second-order study of a remarkable class of convex extended-real-valued functions that is highly important in many aspects of nonlinear and variational analysis, specifically those related to…

Optimization and Control · Mathematics 2015-07-21 Boris S. Mordukhovich , M. Ebrahim Sarabi

We consider square-integrable functionals of Poisson point processes for which the variance upper bound provided by the classical Poincar\'{e} inequality is suboptimal, a phenomenon known as superconcentration. In this paper, we establish a…

Probability · Mathematics 2026-03-26 Chinmoy Bhattacharjee , Rowan O'Clarey

An upper bound for the Wasserstein distance is provided in the general framework of the Wiener-Poisson space. Is obtained from this bound a second order Poincar\'e-type inequality which is useful in terms of computations. For completeness…

Probability · Mathematics 2012-04-27 Juan Víquez

We prove concentration inequalities for general functions of weakly dependent random variables satisfying the Dobrushin condition. In particular, we show Talagrand's convex distance inequality for this type of dependence. We apply our…

Probability · Mathematics 2014-09-02 Daniel Paulin

In [NP09a], 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 investigate the rate of convergence in…

Probability · Mathematics 2018-10-24 Ehsan Azmoodeh , Peter Eichelsbacher , Lukas Knichel