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We give a new, self-contained proof of the multidimensional central limit theorem using the technique of ``doubling variables," which is traditionally used to prove uniqueness of solutions of partial differential equations (PDEs). Our…

Probability · Mathematics 2022-12-23 Louigi Addario-Berry , Gavin Barill , Erin Beckman , Jessica Lin

Using Stein's method techniques, we develop a framework which allows one to bound the error terms arising from approximation by the Laplace distribution and apply it to the study of random sums of mean zero random variables. As a corollary,…

Probability · Mathematics 2014-10-29 John Pike , Haining Ren

This work obtains sharp closed-form exponential concentration inequalities of Bernstein type for the ubiquitous beta distribution, improving upon sub-gaussian and sub-gamma bounds previously studied in this context. The proof leverages a…

Probability · Mathematics 2024-10-21 Maciej Skorski

Self-normalized processes arise naturally in many learning-related tasks. While self-normalized concentration has been extensively studied for scalar-valued processes, there are few results for multidimensional processes outside of the…

Probability · Mathematics 2025-05-02 Justin Whitehouse , Zhiwei Steven Wu , Aaditya Ramdas

In this paper we present a martingale related to the exit measures of super-Brownian motion. By changing measure with this martingale in the canonical way we have a new process associated with the conditioned exit measure. This measure is…

Probability · Mathematics 2016-11-01 Thomas S. Salisbury , John Verzani

The free central-limit theorem, a fundamental theorem in free probability, states that empirical averages of freely independent random variables are asymptotically semi-circular. We extend this theorem to general dynamical systems of…

Probability · Mathematics 2022-11-29 Morgane Austern

In this paper we prove exponential inequalities (also called Bernstein's inequality) for fractional martingales. As an immediate corollary, we will discuss weak law of large numbers for fractional martingales under divergence assumption on…

Probability · Mathematics 2012-04-20 Bruno Saussereau

We derive novel guaranteed lower bounds for eigenvalues of the Euler-Bernoulli beam with variable bending stiffness. While the standard finite element Rayleigh-Ritz method automatically yields upper bounds, we obtain lower bounds by…

Numerical Analysis · Mathematics 2026-05-08 Jana Burkotova , Jitka Machalova , Tomas Vejchodsky

Let {F_n} be a normalized sequence of random variables in some fixed Wiener chaos associated with a general Gaussian field, and assume that E[F_n^4] --> E[N^4]=3, where N is a standard Gaussian random variable. Our main result is the…

Probability · Mathematics 2011-09-08 Hermine Biermé , Aline Bonami , Ivan Nourdin , Giovanni Peccati

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

Let $Z:=\{Z_t,t\geq0\}$ be a stationary Gaussian process. We study two estimators of $\mathbb{E}[Z_0^2]$, namely $\widehat{f}_T(Z):= \frac{1}{T} \int_{0}^{T} Z_{t}^{2}dt$, and $\widetilde{f}_n(Z) :=\frac{1}{n} \sum_{i =1}^{n}…

Statistics Theory · Mathematics 2021-02-10 Soukaina Douissi , Khalifa Es-Sebaiy , George Kerchev , Ivan Nourdin

We propose an estimator for the singular vectors of high-dimensional low-rank matrices corrupted by additive subgaussian noise, where the noise matrix is allowed to have dependence within rows and heteroskedasticity between them. We prove…

Statistics Theory · Mathematics 2022-09-15 Joshua Agterberg , Zachary Lubberts , Carey Priebe

Known Bernstein-type upper bounds on the tail probabilities for sums of independent zero-mean sub-exponential random variables are improved in several ways at once. The new upper bounds have a certain optimality property.

Probability · Mathematics 2022-08-15 Iosif Pinelis

Testing network effects in weighted directed networks is a foundational problem in econometrics, sociology, and psychology. Yet, the prevalent edge dependency poses a significant methodological challenge. Most existing methods are…

Methodology · Statistics 2024-01-09 Wenqin Du , Yuan Zhang , Wen Zhou

It has been proved by Bovier & Hartung [Elect. J. Probab. 19 (2014)] that the maximum of a variable-speed branching Brownian motion (BBM) in the weak correlation regime converges to a randomly shifted Gumbel distribution. The random shift…

Probability · Mathematics 2017-12-13 Constantin Glenz , Nicola Kistler , Marius A. Schmidt

We use martingales to study Bayesian consistency. We derive sufficient conditions for both Hellinger and Kullback-Leibler consistency, which do not rely on the use of a sieve. Alternative sufficient conditions for Hellinger consistency are…

Statistics Theory · Mathematics 2007-06-13 Stephen Walker

This paper is a short exposition of Stein's method of normal approximation from my personal perspective. It focuses mainly on the characterization of the normal distribution and the construction of Stein identities. Through examples, it…

Probability · Mathematics 2021-04-20 Louis H. Y. Chen

We consider the random walk among random conductances on Z^d. We assume that the conductances are independent, identically distributed and uniformly bounded away from 0 and infinity. We obtain a quantitative version of the central limit…

Probability · Mathematics 2011-05-24 Jean-Christophe Mourrat

We propose a numerical procedure for computing the prices of European options, in which the underlying asset price is a Markovian strict local martingale. If the underlying process is a strict local martingale and the payoff is of linear…

Mathematical Finance · Quantitative Finance 2025-04-23 Yukihiro Tsuzuki

The Bruss-Robertson inequality gives a bound on the maximal number of elements of a random sample whose sum is less than a specified value, and the extension of that inequality which is given here neither requires the independence of the…

Probability · Mathematics 2015-10-06 J. Michael Steele
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