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This article is concerned with the spectral behavior of $p$-dimensional linear processes in the moderately high-dimensional case when both dimensionality $p$ and sample size $n$ tend to infinity so that $p/n\to0$. It is shown that, under an…

Statistics Theory · Mathematics 2015-04-27 Lili Wang , Alexander Aue , Debashis Paul

We consider the modulation of data given by random vectors $X_n \in \mathbb{R}^{d_n}$, $n \in \mathbb{N}$. For each $X_n$, one chooses an independent modulating random vector $\Xi_n \in \mathbb{R}^{d_n}$ and forms the projection $Y_n =…

Statistics Theory · Mathematics 2025-10-16 Armine Bagyan , Donald Richards

For a sample of $n$ independent identically distributed $p$-dimensional centered random vectors with covariance matrix $\mathbf{\Sigma}_n$ let $\tilde{\mathbf{S}}_n$ denote the usual sample covariance (centered by the mean) and…

Statistics Theory · Mathematics 2015-09-22 Taras Bodnar , Holger Dette , Nestor Parolya

The first focus of this paper is the characterization of the spectrum and the singular values of the coefficient matrix stemming from the discretization with space-time grid for a parabolic diffusion problem and from the approximation of…

Numerical Analysis · Mathematics 2023-02-17 Matthias Bolten , Sven-Erik Ekström , Isabella Furci , Stefano Serra-Capizzano

Spatial-sign covariance matrix (SSCM) is an important substitute of sample covariance matrix (SCM) in robust statistics. This paper investigates the SSCM on its asymptotic spectral behaviors under high-dimensional elliptical populations,…

Statistics Theory · Mathematics 2017-05-19 Weiming Li , Wang Zhou

The behavior of the leading singular values and vectors of noisy low-rank matrices is fundamental to many statistical and scientific problems. Theoretical understanding currently derives from asymptotic analysis under one of two regimes:…

Statistics Theory · Mathematics 2023-08-03 Michael J. Feldman

In random matrix theory, the spectral distribution of the covariance matrix has been well studied under the large dimensional asymptotic regime when the dimensionality and the sample size tend to infinity at the same rate. However, most…

Statistics Theory · Mathematics 2026-03-17 Qiang Liu , Yiming Liu , Zhi Liu , Wang Zhou

This paper studies the asymptotic spectral properties of a renormalized sample correlation matrix, including the limiting spectral distribution, the properties of largest eigenvalues, and the central limit theorem for linear spectral…

Statistics Theory · Mathematics 2025-05-14 Qianqian Jiang , Junpeng Zhu , Zeng Li

Suppose $X$ and $Y$ are $p\times n$ matrices each with mean $0$, variance $1$ and where all moments of any order are uniformly bounded as $p,n \to \infty$. Moreover, the entries $(X_{ij}, Y_{ij})$ are independent across $i,j$ with a common…

Probability · Mathematics 2021-03-23 Monika Bhattacharjee , Arup Bose , Apratim Dey

Consider a $N\times n$ random matrix $Y_n=(Y_{ij}^{n})$ where the entries are given by $$ Y_{ij}^{n}=\frac{\sigma_{ij}(n)}{\sqrt{n}} X_{ij}^{n} $$ the $X_{ij}^{n}$ being centered, independent and identically distributed random variables…

Probability · Mathematics 2007-06-04 Walid Hachem , Philippe Loubaton , Jamal Najim

The spectral symbols are useful tools to analyse the eigenvalue distribution when dealing with high dimensional linear systems. Given a matrix sequence with an asymptotic symbol, the last one depends only on the spectra of the individual…

Numerical Analysis · Mathematics 2017-10-03 Giovanni Barbarino

We investigate the universality of singular value and eigenvalue distributions of matrix valued functions of independent random matrices and apply these general results in several examples. In particular we determine the limit distribution…

Probability · Mathematics 2014-08-19 F. Götze , H. Kösters , A. Tikhomirov

We study the universal properties of distributions of eigenvalues of random matrices in the large $N$ limit. The distributions fall in universality classes characterized entirely by the support of the spectral density.

Condensed Matter · Physics 2009-10-28 J. Ambjorn , G. Akemann

For two large matrices ${\mathbf X}$ and ${\mathbf Y}$ with Gaussian i.i.d.\ entries and dimensions $T\times N_X$ and $T\times N_Y$, respectively, we derive the probability distribution of the singular values of $\mathbf{X}^T \mathbf{Y}$ in…

Statistics Theory · Mathematics 2025-08-29 Arabind Swain , Sean Alexander Ridout , Ilya Nemenman

The distribution of singular values of the propagation operator in a random medium is investigated, in a backscattering configuration. Experiments are carried out with pulsed ultrasonic waves around 3 MHz, using an array of 64 programmable…

Classical Physics · Physics 2010-07-20 Alexandre Aubry , Arnaud Derode

It is established that the linear spectral statistics (LSS) of the smoothed periodogram estimate of the spectral coherence matrix of a complex Gaussian high-dimensional times series (yn) n$\in$Z with independent components satisfy at each…

Statistics Theory · Mathematics 2025-11-19 Philippe Loubaton , Alexis Rosuel , Pascal Vallet

We consider the moment space $\mathcal{M}_n$ corresponding to $p \times p$ real or complex matrix measures defined on the interval $[0,1]$. The asymptotic properties of the first $k$ components of a uniformly distributed vector $(S_{1,n},…

Probability · Mathematics 2011-05-18 Jan Nagel , Holger Dette

We propose a novel estimation procedure for certain spectral distributions associated with a class of high dimensional linear time series. The processes under consideration are of the form $X_t = \sum_{\ell=0}^\infty \mathbf{A}_\ell…

Statistics Theory · Mathematics 2025-04-15 Jamshid Namdari , Alexander Aue , Debashis Paul

In this paper we present the asymptotic theory for spectral distributions of high dimensional covariation matrices of Brownian diffusions. More specifically, we consider $N$-dimensional Ito integrals with time varying matrix-valued…

Probability · Mathematics 2014-10-27 Claudio Heinrich , Mark Podolskij

Let $\mathbf{B}_n=\mathbf {S}_n(\mathbf {S}_n+\alpha_n\mathbf {T}_N)^{-1}$, where $\mathbf {S}_n$ and $\mathbf {T}_N$ are two independent sample covariance matrices with dimension $p$ and sample sizes $n$ and $N$, respectively. This is the…

Probability · Mathematics 2015-07-30 Zhidong Bai , Jiang Hu , Guangming Pan , Wang Zhou