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We take a unified approach to central limit theorems for a class of irreducible urn models with constant replacement matrix. Depending on the eigenvalue, we consider appropriate linear combinations of the number of balls of different…

Probability · Mathematics 2008-05-29 Gopal K. Basak , Amites Dasgupta

We show how a central limit theorem for Poisson model random polygons implies a central limit theorem for uniform model random polygons. To prove this implication, it suffices to show that in the two models, the variables in question have…

Probability · Mathematics 2012-08-14 John Pardon

It is known that a random walk on $\Z^d$ among i.i.d. uniformly elliptic random bond conductances verifies a central limit theorem. It is also known that approximations of the covariance matrix can be obtained by considering periodic…

Probability · Mathematics 2007-05-23 Daniel Boivin

In Part I of this article (Banerjee and Kuchibhotla (2023)), we have introduced a new method to bound the difference in expectations of an average of independent random vector and the limiting Gaussian random vector using level sets. In the…

Probability · Mathematics 2023-06-27 Arun Kumar Kuchibhotla

In a spiked population model, the population covariance matrix has all its eigenvalues equal to units except for a few fixed eigenvalues (spikes). This model is proposed by Johnstone to cope with empirical findings on various data sets. The…

Probability · Mathematics 2008-12-18 Zhidong Bai , Jian-feng Yao

In this paper, we investigate a central limit theorem for weighted sums of independent random variables under sublinear expectations. It is turned out that our results are natural extensions of the results obtained by Peng and Li and Shi.

Probability · Mathematics 2011-05-05 Defei Zhang

Consider the product $X = X_{1}\cdots X_{m}$ of $m$ independent $n\times n$ iid random matrices. When $m$ is fixed and the dimension $n$ tends to infinity, we prove Gaussian limits for the centered linear spectral statistics of $X$ for…

Probability · Mathematics 2019-04-11 Natalie Coston , Sean O'Rourke

We extend our recent result [Cipolloni, Erd\H{o}s, Schr\"oder 2019] on the central limit theorem for the linear eigenvalue statistics of non-Hermitian matrices $X$ with independent, identically distributed complex entries to the real…

Probability · Mathematics 2024-02-02 Giorgio Cipolloni , László Erdős , Dominik Schröder

We prove a central limit theorem for random walks with finite variance on linear groups.

Probability · Mathematics 2016-05-25 Yves Benoist , Jean-François Quint

Some tools and ideas are interchanged between random matrix theory and multivariate statistics. In the context of the random matrix theory, classes of spherical and generalised Wishart random matrix ensemble, containing as particular cases…

Statistics Theory · Mathematics 2009-07-07 Jose A. Diaz-Garcia , Ramon Gutiérrez Jáimez

In this article, we will consider Wishart Matrices with correlated entries, but with a strictly log-concave law. It has been shown by A.Pajor and L.Pastur that the empirical measures of such matrices converges. We will show, under some…

Probability · Mathematics 2014-03-07 Kevin Richard , Alice Guionnet

This paper investigates the behavior of statistical ensembles under iteration map induced by discrete integrable Hamiltonian systems in deterministic case and stochastic case, addressing the problem from two perspectives: the Law of Large…

Probability · Mathematics 2025-09-26 Xinyu Liu , Xinze Zhang , Yong Li

We prove a central limit theorem for the components of the eigenvectors corresponding to the $d$ largest eigenvalues of the normalized Laplacian matrix of a finite dimensional random dot product graph. As a corollary, we show that for…

Machine Learning · Statistics 2016-07-29 Minh Tang , Carey E. Priebe

Consider random symmetric Toeplitz matrices $T_{n}=(a_{i-j})_{i,j=1}^{n}$ with matrix entries $a_{j}, j=0,1,2,...,$ being independent real random variables such that \be \mathbb{E}[a_{j}]=0, \ \ \mathbb{E}[|a_{j}|^{2}]=1 \ \ \textrm{for}\,\…

Probability · Mathematics 2010-11-09 Dang-Zheng Liu , Xin Sun , Zheng-Dong Wang

The central limit theorem is, with the strong law of large numbers, one of the two fundamental limit theorems in probability theory. Benjamin Jourdain and Alvin Tse have extended to non-linear functionals of the empirical measure of…

Probability · Mathematics 2022-04-14 Roberta Flenghi , Benjamin Jourdain

We consider the existence of the integrated density of states (IDS) of the Anderson model on the Hilbert space $\ell^2(\mathbb{Z}^d)$ as analogues to the law of large numbers (LLN). In this work, we prove the analogues central limit theorem…

Mathematical Physics · Physics 2024-12-04 Dhriti Ranjan Dolai

In this paper we consider the product of two independent random matrices $\mathbb X^{(1)}$ and $\mathbb X^{(2)}$. Assume that $X_{jk}^{(q)}, 1 \le j,k \le n, q = 1, 2,$ are i.i.d. random variables with $\mathbb E X_{jk}^{(q)} = 0, \mathbb E…

Probability · Mathematics 2015-11-24 Friedrich Götze , Alexey Naumov , Alexander Tikhomirov

We present some applications of central limit theorems on mesoscopic scales for random matrices. When combined with the recent theory of "homogenization" for Dyson Brownian Motion, this yields the universality of quantities which depend on…

Probability · Mathematics 2019-11-28 Benjamin Landon , Philippe Sosoe

We prove a central limit theorem for linear triangular arrays under weak dependence conditions. Our result is then applied to the study of dependent random variables sampled by a $\bbZ$-valued transient random walk. This extends the results…

Probability · Mathematics 2007-12-24 Nadine Guillotin-Plantard , Clémentine Prieur

The paper proves several limit theorems for linear eigenvalue statistics of overlapping Wigner and sample covariance matrices. It is shown that the covariance of the limiting multivariate Gaussian distribution is diagonalized by choosing…

Probability · Mathematics 2015-11-10 Vladislav Kargin