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Related papers: On Stein's method for multivariate normal approxim…

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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

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 establish new Strichartz estimates for orthonormal systems on compact Riemannian manifolds in the case of wave, Klein-Gordon and fractional Schr\"odinger equations. Our results generalize the classical (single-function) Strichartz…

Analysis of PDEs · Mathematics 2025-09-03 Xing Wang , An Zhang , Cheng Zhang

We propose a new minimum-distance estimator for linear random coefficient models. This estimator integrates the recently advanced sliced Wasserstein distance with the nearest neighbor methods, both of which enhance computational efficiency.…

Statistics Theory · Mathematics 2025-04-25 Keunwoo Lim , Ting Ye , Fang Han

We propose extensions and improvements of the statistical analysis of distributed multipoles (SADM) algorithm put forth by Chipot et al. in [6] for the derivation of distributed atomic multipoles from the quantum-mechanical electrostatic…

Numerical Analysis · Mathematics 2010-07-28 Nicolas Champagnat , Christophe Chipot , Erwan Faou

We build upon recent advances on the distributional aspect of Stein's method to propose a novel and flexible technique for computing Stein operators for random variables that can be written as products of independent random variables. We…

Probability · Mathematics 2018-09-28 Robert E. Gaunt , Guillaume Mijoule , Yvik Swan

We investigate the convergence of a nonlinear approximation method introduced by Ammar et al. (J. Non-Newtonian Fluid Mech. 139:153-176, 2006) for the numerical solution of high-dimensional Fokker-Planck equations featuring in…

Numerical Analysis · Mathematics 2012-09-25 Leonardo E. Figueroa , Endre Süli

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 paper we propose a new, simple and explicit mechanism allowing to derive Stein operators for random variables whose characteristic function satisfies a simple ODE. We apply this to study random variables which can be represented as…

Probability · Mathematics 2023-07-06 Benjamin Arras , Ehsan Azmoodeh , Guillaume Poly , Yvik Swan

In this paper use the Stein method to characterize the $M$-Wright distribution $M_{\frac{1}{3}}$ and its symmetrization. The Stein operator is associated with the general Airy equation and the corresponding Stein equation is nothing but a…

Probability · Mathematics 2020-08-11 José Luís da Silva , Mohamed Erraoui

In this paper we present a general framework for Stein's method for multivariate continuous distributions. The approach gives a collection of Stein characterisations, among which we highlight score-Stein operators and kernel Stein…

Probability · Mathematics 2019-11-14 Guillaume Mijoule , Gesine Reinert , Yvik Swan

We combine Malliavin calculus with Stein's method to derive bounds for the Variance-Gamma approximation of functionals of isonormal Gaussian processes, in particular of random variables living inside a fixed Wiener chaos induced by such a…

Probability · Mathematics 2014-09-22 Peter Eichelsbacher , Christoph Thäle

We use Stein's method to provide non asymptotic $L^1$ bounds to the normal for functionals of associated point processes. As for supporting tools, we use the connection between association and $\alpha$-mixing properties that was recently…

Probability · Mathematics 2020-04-03 Nathakhun Wiroonsri

We establish a new perturbation theory for orthogonal polynomials using a Riemann--Hilbert approach and consider applications in numerical linear algebra and random matrix theory. This new approach shows that the orthogonal polynomials with…

Probability · Mathematics 2022-09-23 Xiucai Ding , Thomas Trogdon

Let $\boldsymbol{\xi}=(\xi_1,\ldots,\xi_m)$ be a negatively associated mean zero random vector with components that obey the bound $|\xi_i| \le B, i=1,\ldots,m$, and whose sum $W = \sum_{i=1}^m \xi_i$ has variance 1, the bound \[…

Probability · Mathematics 2018-09-11 Nathakhun Wiroonsri

We study the dispersive properties of the wave equation associated with the shifted Laplace-Beltrami operator on Damek-Ricci spaces, and deduce Strichartz estimates for a large family of admissible pairs. As an application, we obtain global…

Analysis of PDEs · Mathematics 2010-12-06 Jean-Philippe Anker , Vittoria Pierfelice , Maria Vallarino

Non-overlapping Schwarz methods with generalized Robin transmission conditions were originally introduced by B. Despr\'es for time-harmonic wave propagation problems and have largely developed over the past thirty years. The aim of the…

Numerical Analysis · Mathematics 2022-04-08 Clemens Pechstein

The aim of the present article is to extend the Stone--Weierstrass theorem to functions ranging in a lattice normed space and order rather than topological approximation. We proceed with the machinery of Boolean valued transfer from lattice…

Functional Analysis · Mathematics 2024-06-07 A. G. Kusraev , S. S. Kutateladze

This paper gives the Kolmogorov and Wasserstein bounds in normal approximation for the squared-length of total spin in the mean field classical $N$-vector models. The Kolmogorov bound is new while the Wasserstein bound improves a result…

Probability · Mathematics 2019-03-27 Lê Vǎn Thành , Nguyen Ngoc Tu

Random-effects meta-analyses are very commonly used in medical statistics. Recent methodological developments include multivariate (multiple outcomes) and network (multiple treatments) meta-analysis. Here we provide a new model and…

Methodology · Statistics 2017-08-16 Dan Jackson , Sylwia Bujkiewicz , Martin Law , Richard D Riley , Ian White