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This paper establishes new concentration inequalities for random matrices constructed from independent random variables. These results are analogous with the generalized Efron-Stein inequalities developed by Boucheron et al. The proofs rely…

Probability · Mathematics 2014-08-18 Daniel Paulin , Lester Mackey , Joel A. Tropp

The main purpose of this paper is to establish a noncommutative analogue of the Efron--Stein inequality, which bounds the variance of a general function of some independent random variables. Moreover, we state an operator version including…

Functional Analysis · Mathematics 2021-07-23 Ali Talebi , Mohammad Sal Moslehian

We show by a surprisingly simple argument that the exchangeability condition, which is key to the exchangeable pair approach in Stein's method for distributional approximation, can be omitted in many standard settings. This is achieved by…

Probability · Mathematics 2008-02-07 Adrian Röllin

We consider the variance of a function of $n$ independent random variables and provide new inequalities which, in particular, extend previous results obtained for symmetric functions in the i.i.d.~setting. For instance, we obtain various…

Statistics Theory · Mathematics 2020-01-01 Olivier Bousquet , Christian Houdré

This paper establishes a non-uniform Berry--Esseen bound in normal approximation for exchangeable pairs using Stein's method via a concentration inequality approach. The main theorem extends and improves several results in the literature,…

Probability · Mathematics 2025-02-18 Lê Vǎn Thành , Nguyen Ngoc Tu

We give a distribution-dependent concentration inequality for functions of independent variables. The result extends Bernstein's inequality from sums to more general functions, whose variation in any argument does not depend too much on the…

Probability · Mathematics 2017-05-12 Andreas Maurer

An exchangeable pair approach is commonly taken in the normal and non-normal approximation using Stein's method. It has been successfully used to identify the limiting distribution and provide an error of approximation. However, when the…

Probability · Mathematics 2021-04-28 Qi-Man Shao , Zhuo-Song Zhang

Stein's method of exchangeable pairs is examined through five examples in relation to Poisson and normal distribution approximation. In particular, in the case where the exchangeable pair is constructed from a reversible Markov chain, we…

Probability · Mathematics 2009-04-03 Nathan Ross

This note describes non-asymptotic variance and tail bounds for order statistics of samples of independent identically distributed random variables. Those bounds are checked to be asymptotically tight when the sampling distribution belongs…

Probability · Mathematics 2012-11-05 Stephane Boucheron , Maud Thomas

In this paper, we present a refined version of the (classical) Stein inequality for the Fourier transform, elevating it to a new level of accuracy. Furthermore, we establish extended analogues of a more precise version of the Stein…

Functional Analysis · Mathematics 2024-11-19 Erlan D. Nursultanov , Durvudkhan Suragan

We propose probabilistic representations for inverse Stein operators (i.e. solutions to Stein equations) under general conditions; in particular we deduce new simple expressions for the Stein kernel. These representations allow to deduce…

Probability · Mathematics 2019-06-21 Marie Ernst , Gesine Reinert , Yvik Swan

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

We derive explicit central moment inequalities for random variables that admit a Stein coupling, such as exchangeable pairs, size--bias couplings or local dependence, among others. The bounds are in terms of moments (not necessarily…

Probability · Mathematics 2020-07-07 A. D. Barbour , Nathan Ross , Yuting Wen

This is a substantially generalized version of the preprint arXiv:1105.4214 by Lifshits and Tyurin. We prove that for any pair of i.i.d. random vectors $X, Y$ in $R^n$ and any real-valued continuous negative definite function $g: R^n\to R$…

Probability · Mathematics 2015-02-24 M. Lifshits , R. L. Schilling , I. Tyurin

The extended de Finetti theorem characterizes exchangeable infinite random sequences as conditionally i.i.d. and shows that the apparently weaker distributional symmetry of spreadability is equivalent to exchangeability. Our main result is…

Operator Algebras · Mathematics 2008-06-24 Claus Köstler

For convex univalent functions we give instances where the sharp bound for various coefficient functionals are identical to those for the corresponding bound for the inverse function. We give instances where the sharp bounds differ and also…

Complex Variables · Mathematics 2022-12-12 Derek K. Thomas

We extend Stein's celebrated Wasserstein bound for normal approximation via exchangeable pairs to the multi-dimensional setting. As an intermediate step, we exploit the symmetry of exchangeable pairs to obtain an error bound for smooth test…

Probability · Mathematics 2020-09-22 Xiao Fang , Yuta Koike

We construct a continuous family of exchangeable pairs by perturbing the random variable through diffusion processes on manifold in order to apply Stein method to certain geometric settings. We compare our perturbation by diffusion method…

Probability · Mathematics 2020-07-07 Weitao Du

In Stein's method, the exchangeable pair approach is commonly used to estimate the approximation errors in normal approximation. In this paper, we establish a Cram\'er-type moderate deviation theorem of normal approximation for unbounded…

Probability · Mathematics 2022-09-26 Zhuo-Song Zhang

We consider Khintchine type inequalities on the $p$-th moments of vectors of $N$ pairwise independent Rademacher random variables. We establish that an analogue of Khintchine's inequality cannot hold in this setting with a constant that is…

Functional Analysis · Mathematics 2014-12-30 Brendan Pass , Susanna Spektor
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