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This paper investigates the approximation of Gaussian random variables in Banach spaces, focusing on the high-probability bounds for the approximation of Gaussian random variables using finitely many observations. We derive non-asymptotic…

Statistics Theory · Mathematics 2025-08-28 Daniel Winkle , Ingo Steinwart , Bernard Haasdonk

The goal of this article is two-fold: in a first part, we prove Azuma-Hoeffding type concentration inequalities around the drift for the displacement of non-elementary random walks on hyperbolic spaces. For a proper hyperbolic space $M$, we…

Probability · Mathematics 2022-02-07 Richard Aoun , Cagri Sert

We establish inequalities for assessing the distance between the distribution of a (possibly multidimensional) functional of a Poisson random measure and that of a Gaussian element. Our bounds only involve add-one cost operators at the…

Probability · Mathematics 2020-10-27 Raphaël Lachièze-Rey , Giovanni Peccati , Xiaochuan Yang

This paper investigates the {\em nonasymptotic} properties of Bayes procedures for estimating an unknown distribution from $n$ i.i.d.\ observations. We assume that the prior is supported by a model $(\scr{S},h)$ (where $h$ denotes the…

Statistics Theory · Mathematics 2014-11-03 Lucien Birgé

Our main theorem is in the generality of the axioms of Hilbert space, and the theory of unbounded operators. Consider two Hilbert spaces such that their intersection contains a fixed vector space D. It is of interest to make a precise…

Functional Analysis · Mathematics 2017-01-19 Palle Jorgensen , Erin Pearse , Feng Tian

In this work, we investigate Gaussian Mixture Models ({\it abbrv} GMM) and the related problem of non parametric maximum likelihood estimation ({\it abbrv} NPMLE) from the perspective of statistical mechanics. In particular, we establish…

Statistics Theory · Mathematics 2026-03-25 Subhroshekhar Ghosh , Adityanand Guntuboyina , Satyaki Mukherjee , Hoang-Son Tran

In 2010, Shiffman and Zelditch proved a central limit theorem (CLT) for smooth statistics of Gaussian random zeros in codimension one over compact K\"ahler manifolds. They raised the question of whether this result admits a two-fold…

Complex Variables · Mathematics 2026-04-15 Bin Guo

In this paper, we study high-dimensional random projections of $\ell_p^n$-balls. More precisely, for any $n\in\mathbb N$ let $E_n$ be a random subspace of dimension $k_n\in\{1,\ldots,n\}$ and $X_n$ be a random point in the unit ball of…

Probability · Mathematics 2018-08-29 David Alonso-Gutierrez , Joscha Prochno , Christoph Thaele

Recent results in quantization theory show that the mean-squared expected distortion can reach a rate of convergence of $\mathcal{O}(1/n)$, where $n$ is the sample size [see, e.g., IEEE Trans. Inform. Theory 60 (2014) 7279-7292 or Electron.…

Statistics Theory · Mathematics 2015-04-02 Clément Levrard

We determine upper asymptotic estimates of Kolmogorov and linear $n$-widths of unit balls in Sobolev and Besov norms in $L_{p}$-spaces on smooth compact Riemannian manifolds. For compact homogeneous manifolds, we establish estimates which…

Functional Analysis · Mathematics 2015-02-13 Daryl Geller , Isaac Pesenson

We study two spinless bosons interacting via two-body Gaussian potential subjected to an externally impressed rotation about an axis confined in a harmonic trap in two-spatial dimensions. We obtain a transcendental equation for the relative…

Quantum Gases · Physics 2025-12-25 Md Hamid , M. A. H. Ahsan

This paper is concerned with volume-constrained minimization problems derived from Gamow's liquid drop model for the atomic nucleus, involving the competition of a perimeter term and repulsive nonlocal potentials. We consider a large class…

Analysis of PDEs · Mathematics 2021-05-04 Marc Pegon

Limit theorems are proved for quadratic forms of Gaussian random fields in presence of long memory. We obtain a non central limit theorem under a minimal integrability condition, which allows isotropic and anisotropic models. We apply our…

Statistics Theory · Mathematics 2010-01-08 Frédéric Lavancier , Anne Philippe

We consider the Grenander estimator that is the maximum likelihood estimator for non-increasing densities. We prove uniform central limit theorems for certain subclasses of bounded variation functions and for H\"older balls of smoothness…

Statistics Theory · Mathematics 2015-06-29 Jakob Söhl

We prove new concentration estimates for random variables that are functionals of a Poisson measure defined on a general measure space. Our results are specifically adapted to geometric applications, and are based on a pervasive use of a…

Probability · Mathematics 2015-04-14 Sascha Bachmann , Giovanni Peccati

This paper shows that large nonparametric classes of conditional multivariate densities can be approximated in the Kullback--Leibler distance by different specifications of finite mixtures of normal regressions in which normal means and…

Statistics Theory · Mathematics 2010-10-05 Andriy Norets

Under correlation-type conditions, we derive an upper bound of order $(\log n)/n$ for the average Kolmogorov distance between the distributions of weighted sums of dependent summands and the normal law. The result is based on improved…

Probability · Mathematics 2019-06-24 S. G. Bobkov , G. P. Chistyakov , F. Götze

This paper deals with a one--dimensional model for granular materials, which boils down to an inelastic version of the Kac kinetic equation, with inelasticity parameter $p>0$. In particular, the paper provides bounds for certain distances…

Mathematical Physics · Physics 2009-11-13 Federico Bassetti , Lucia Ladelli , Eugenio Regazzini

In this paper, we derive some upper and lower bounds and inequalities for the total variation distance (TVD) and the Kullback-Leibler divergence (KLD), also known as the relative entropy, between two probability measures $\mu$ and $\nu$…

Probability · Mathematics 2025-01-07 Ievlev Pavel , Timofei Shashkov

This paper derives central limit and bootstrap theorems for probabilities that sums of centered high-dimensional random vectors hit hyperrectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for…

Statistics Theory · Mathematics 2016-03-09 Victor Chernozhukov , Denis Chetverikov , Kengo Kato
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