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Related papers: Large sample behaviour of high dimensional autocov…

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This paper investigates the central limit theorem for linear spectral statistics of high dimensional sample covariance matrices of the form $\mathbf{B}_n=n^{-1}\sum_{j=1}^{n}\mathbf{Q}\mathbf{x}_j\mathbf{x}_j^{*}\mathbf{Q}^{*}$ where…

Probability · Mathematics 2017-08-15 Shurong Zheng , Zhidong Bai , Jianfeng Yao , Hongtu Zhu

We study the gaps between consecutive singular values of random rectangular matrices. Specifically, if $M$ is an $n \times p$ random matrix with independent and identically distributed entries and $\Sigma$ is a $n \times n$ deterministic…

Probability · Mathematics 2025-10-07 Nicholas Christoffersen , Kyle Luh , Sean O'Rourke , Calum Shearer

Consider the random matrix model $A^{1/2} UBU^* A^{1/2},$ where $A$ and $B$ are two $N \times N$ deterministic matrices and $U$ is either an $N \times N$ Haar unitary or orthogonal random matrix. It is well-known that on the macroscopic…

Probability · Mathematics 2022-07-07 Xiucai Ding , Hong Chang Ji

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals…

Probability · Mathematics 2021-03-18 Arup Bose , Koushik Saha , Arusharka Sen , Priyanka Sen

This paper is concerned with the limiting spectral behaviors of large dimensional Kendall's rank correlation matrices generated by samples with independent and continuous components. We do not require the components to be identically…

Statistics Theory · Mathematics 2019-12-16 Zeng Li , Qinwen Wang , Runze Li

Suppose that $\mathbf X_n=(x_{jk})$ is $N\times n$ whose elements are independent real variables with mean zero, variance 1 and the fourth moment equal to three. The separable sample covariance matrix is defined as $\mathbf{B}_n =…

Probability · Mathematics 2016-11-29 Bai Zhidong , Li Huiqin , Pan Guangming

Group equivariance can overly constrain models if the symmetries in the group differ from those observed in data. While common methods address this by determining the appropriate level of symmetry at the dataset level, they are limited to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Alonso Urbano , David W. Romero

Consider a $p$-dimensional population ${\mathbf x} \in\mathbb{R}^p$ with iid coordinates in the domain of attraction of a stable distribution with index $\alpha\in (0,2)$. Since the variance of ${\mathbf x}$ is infinite, the sample…

Probability · Mathematics 2022-09-20 Johannes Heiny , Jianfeng Yao

For symmetric random matrices with correlated entries, which are functions of independent random variables, we show that the asymptotic behavior of the empirical eigenvalue distribution can be obtained by analyzing a Gaussian matrix with…

Probability · Mathematics 2014-11-11 Florence Merlevede , Magda Peligrad , Marwa Banna

In this paper, we study the largest eigenvalues of sample covariance matrices with elliptically distributed data. We consider the sample covariance matrix $Q=YY^*,$ where the data matrix $Y \in \mathbb{R}^{p \times n}$ contains i.i.d.…

Probability · Mathematics 2023-04-24 Xiucai Ding , Jiahui Xie

We provide a simple, unified approach to describing the impact of super-sample covariance, or beat coupling, on power spectrum estimation in a finite-volume survey. For a wide range of survey volumes, the sample variance that arises from…

Cosmology and Nongalactic Astrophysics · Physics 2014-01-06 Masahiro Takada , Wayne Hu

We investigate the eigenvalue spectrum of the staggered Dirac matrix in SU(3) gauge theory and in full QCD as well as in quenched U(1) theory on various lattice sizes. As a measure of the fluctuation properties of the eigenvalues, we study…

High Energy Physics - Lattice · Physics 2007-05-23 Bernd A. Berg , Harald Markum , Rainer Pullirsch , Tilo Wettig

We derive the mean eigenvalue density for symmetric Gaussian random N x N matrices in the limit of large N, with a constraint implying that the row sum of matrix elements should vanish. The result is shown to be equivalent to a result found…

Disordered Systems and Neural Networks · Physics 2009-11-10 J. Staering , B. Mehlig , Yan V. Fyodorov , J. M. Luck

A central limit theorem (CLT) for the smoothed empirical spectral distribution of sample covariance matrices is established. Moreover, the CLTs for the smoothed quantiles of Marcenko and Pastur's law have been also developed.

Statistics Theory · Mathematics 2011-11-24 Guangming Pan , Qi-Man Shao , Wang Zhou

We study the fluctuations of the eigenvalues of real valued large centrosymmetric random matrices via its linear eigenvalue statistic. This is essentially a central limit theorem (CLT) for sums of dependent random variables. The dependence…

Probability · Mathematics 2025-10-01 Indrajit Jana , Sunita Rani

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

In this paper, we consider the addition of two matrices in generic position, namely A + U BU * , where U is drawn under the Haar measure on the unitary or the orthogonal group. We show that, under mild conditions on the empirical spectral…

Probability · Mathematics 2018-11-27 Alice Guionnet , Mylène Maïda

We investigate the asymptotic behavior of the eigenvalues of the sum A+U*BU, where A and B are deterministic N by N Hermitian matrices having respective limiting compactly supported distributions \mu, \nu, and U is a random N by N unitary…

Probability · Mathematics 2012-07-24 Serban Teodor Belinschi , Hari Bercovici , Mireille Capitaine , Maxime Février

We consider two $n\times n$ non-Hermitian random matrices such that the $ij$th entry of one matrix is correlated with the $ij$th entry of the other matrix. However, the entries of any particular matrix are i.i.d. random variables. We study…

Probability · Mathematics 2025-04-08 Indrajit Jana , Sunita Rani

Consider the sample covariance matrix $$\Sigma^{1/2}XX^T\Sigma^{1/2}$$ where $X$ is an $M\times N$ random matrix with independent entries and $\Sigma$ is an $M\times M$ diagonal matrix. It is known that if $\Sigma$ is deterministic, then…

Probability · Mathematics 2023-02-27 Ji Oon Lee , Yiting Li
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