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Related papers: High-dimensional CLT: Improvements, Non-uniform Ex…

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We establish a central limit theorem (CLT) for families of products of $\epsilon$-independent random variables. We utilize graphon limits to encode the evolution of independence and characterize the limiting distribution. Our framework…

Probability · Mathematics 2025-04-15 Guillaume Cébron , Patrick Oliveira Santos , Pierre Youssef

We prove quenched versions of (i) a large deviations principle (LDP), (ii) a central limit theorem (CLT), and (iii) a local central limit theorem (LCLT) for non-autonomous dynamical systems. A key advance is the extension of the spectral…

Dynamical Systems · Mathematics 2018-02-14 Davor Dragicevic , Gary Froyland , Cecilia Gonzalez-Tokman , Sandro Vaienti

Let $X_1, \ldots , X_n$ be i.i.d. random vectors in $\mathbb{R}^d$ with $\|X_1\| \le \beta$. Then, we show that $\frac{1}{\sqrt{n}}(X_1 + \ldots + X_n)$ converges to a Gaussian in quadratic transportation (also known as "Kantorovich" or…

Probability · Mathematics 2017-07-25 Alex Zhai

In the literature of high-dimensional central limit theorems, there is a gap between results for general limiting correlation matrix $\Sigma$ and the strongly non-degenerate case. For the general case where $\Sigma$ may be degenerate, under…

Probability · Mathematics 2023-05-30 Xiao Fang , Yuta Koike , Song-Hao Liu , Yi-Kun Zhao

We produce a series of Central Limit Theorems (CLTs) associated to compact metric measure spaces $(K,d,\eta)$, with $\eta$ a reasonable probability measure. For the first CLT, we can ignore $\eta$ by isometrically embedding $K$ into…

Probability · Mathematics 2020-01-14 Steven Rosenberg , Jie Xu

In this paper, we establish the central limit theorem (CLT) for linear spectral statistics (LSS) of large-dimensional sample covariance matrix when the population covariance matrices are not uniformly bounded, which is a nontrivial…

Statistics Theory · Mathematics 2022-05-17 Zhijun Liu , Jiang Hu , Zhidong Bai , Haiyan Song

When the underlying random variables are Gaussian, the classical Central Limit Theorem (CLT) is trivial, but the functional CLT is not. The objective of the paper is to investigate the functional CLT for stationary Gaussian processes in the…

Probability · Mathematics 2022-09-20 S. V. Lototsky

The question of whether the central limit theorem (CLT) holds for the total number of edges in exponential random graph models (ERGMs) in the subcritical region of parameters has remained an open problem. In this paper, we establish the…

Probability · Mathematics 2025-04-09 Xiao Fang , Song-Hao Liu , Qi-Man Shao , Yi-Kun Zhao

This paper deals with subspace estimation in the small sample size regime, where the number of samples is comparable in magnitude with the observation dimension. The traditional estimators, mostly based on the sample correlation matrix, are…

Methodology · Statistics 2015-06-19 Pascal Vallet , Xavier Mestre , Philippe Loubaton

The main result of the article is the rate of convergence to the Rosenblatt-type distributions in non-central limit theorems. Specifications of the main theorem are discussed for several scenarios. In particular, special attention is paid…

Probability · Mathematics 2016-06-16 Vo Anh , Nikolai Leonenko , Andriy Olenko

We consider the rates of convergence of the quenched central limit theorem for hitting times of one-dimensional random walks in a random environment. Previous results had identified polynomial upper bounds for the rates of decay which are…

Probability · Mathematics 2021-09-16 Sung Won Ahn , Jonathon Peterson

We obtain convergence rates (in the Levi-Prokhorove metric) in the functional central limit theorem (CLT) for partial sums $S_n=\sum_{j=1}^{n}\xi_{j,n}$ of triangular arrays $\{\xi_{1,n},\xi_{2,n},...,\xi_{n,n}\}$ satisfying some mixing and…

Probability · Mathematics 2022-06-23 Yeor Hafouta

In this paper we consider a branching particle system consisting of particles moving according to the Ornstein-Uhlenbeck process in $\Rd$ and undergoing a binary, supercritical branching with a constant rate $\lambda>0$. This system is…

Probability · Mathematics 2011-11-23 Radosław Adamczak , Piotr Miłoś

In this paper, we rigorously derive Central Limit Theorems (CLT) for Bayesian two-layerneural networks in the infinite-width limit and trained by variational inference on a regression task. The different networks are trained via different…

Machine Learning · Statistics 2024-06-14 Arnaud Descours , Tom Huix , Arnaud Guillin , Manon Michel , Éric Moulines , Boris Nectoux

We study the central limit theorem for sums of independent tensor powers, $\frac{1}{\sqrt{d}}\sum\limits_{i=1}^d X_i^{\otimes p}$. We focus on the high-dimensional regime where $X_i \in \mathbb{R}^n$ and $n$ may scale with $d$. Our main…

Probability · Mathematics 2020-11-05 Dan Mikulincer

We use martingale embeddings to prove a central limit theorem (CLT) for one-dimensional projections of high-dimensional random vectors in $\{-1,1\}^n$ satisfying a Poincar\'e inequality. We obtain a non-asymptotic error bound involving…

Probability · Mathematics 2026-04-29 Xiao Fang , Yang Xie , Yi-Kun Zhao

We analyze the fluctuations of incomplete $U$-statistics over a triangular array of independent random variables. We give criteria for a Central Limit Theorem (CLT, for short) to hold in the sense that we prove that an appropriately scaled…

Probability · Mathematics 2020-03-24 Matthias Löwe , Sara Terveer

In this paper, we prove a polynomial Central Limit Theorem for several integrable models, and for the $\beta$-ensembles at high-temperature with polynomial potential. Furthermore, we connect the mean values, the variances and the…

Probability · Mathematics 2023-12-19 Guido Mazzuca , Ronan Memin

We establish a central limit theorem for the fluctuations of the linear statistics in the $\beta$-ensemble of dimension $N$ at a temperature proportional to $N$ and with confining smooth potential. In this regime, the particles do not…

Probability · Mathematics 2024-11-12 Charlie Dworaczek Guera , Ronan Memin

Consider the set of all sequences of $n$ outcomes, each taking one of $m$ values, that satisfy a number of linear constraints. If $m$ is fixed while $n$ increases, most sequences that satisfy the constraints result in frequency vectors…

Information Theory · Computer Science 2016-11-18 Kostas N. Oikonomou , Peter D. Grunwald