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In this note we develop an extension of the Mar\v{c}enko-Pastur theorem to time series model with temporal correlations. The limiting spectral distribution (LSD) of the sample covariance matrix is characterised by an explicit equation for…

Statistics Theory · Mathematics 2012-06-06 Jianfeng Yao

We consider the random geometric graph on $n$ vertices drawn uniformly from a $d$--dimensional sphere. We focus on the sparse regime, when the expected degree is constant independent of $d$ and $n$. We show that, when $d$ is larger than $n$…

Probability · Mathematics 2021-10-22 Elliot Paquette , Andrew Vander Werf

Using Beck and Cohen's superstatistics, we introduce in a systematic way a family of generalised Wishart-Laguerre ensembles of random matrices with Dyson index $\beta$ = 1,2, and 4. The entries of the data matrix are Gaussian random…

Mathematical Physics · Physics 2009-04-07 A. Y. Abul-Magd , G. Akemann , P. Vivo

We derive the probability that all eigenvalues of a random matrix $\bf M$ lie within an arbitrary interval $[a,b]$, $\psi(a,b)\triangleq\Pr\{a\leq\lambda_{\min}({\bf M}), \lambda_{\max}({\bf M})\leq b\}$, when $\bf M$ is a real or complex…

Statistics Theory · Mathematics 2017-04-25 Marco Chiani

We obtain the limiting spectral distribution for large sample covariance matrices associated with random vectors having graph-dependent entries under the assumption that the interdependence among the entries grows with the sample size n.…

Probability · Mathematics 2021-05-21 Pavel Yaskov

This paper is the first chapter of three of the author's undergraduate thesis. We study the random matrix ensemble of covariance matrices arising from random $(d_b, d_w)$-regular bipartite graphs on a set of $M$ black vertices and $N$ white…

Probability · Mathematics 2017-04-28 Kevin Yang

Random matrix theory is used to assess the significance of weak correlations and is well established for Gaussian statistics. However, many complex systems, with stock markets as a prominent example, exhibit statistics with power-law tails,…

Statistical Mechanics · Physics 2013-03-19 Mauro Politi , Enrico Scalas , Daniel Fulger , Guido Germano

We derive the Marchenko-Pastur (MP) law for sample covariance matrices of the form $V_n=\frac{1}{n}XX^T$, where $X$ is a $p\times n$ data matrix and $p/n\to y\in(0,\infty)$ as $n,p \to \infty$. We assume the data in $X$ stems from a…

Probability · Mathematics 2022-03-09 Michael Fleermann , Johannes Heiny

For a class of symmetric random matrices whose entries are martingale differences adapted to an increasing filtration, we prove that under a Lindeberg-like condition, the empirical spectral distribution behaves asymptotically similarly to a…

Probability · Mathematics 2014-02-27 Florence Merlevède , Costel Peligrad , Magda Peligrad

We study various methods to generate ensembles of random density matrices of a fixed size N, obtained by partial trace of pure states on composite systems. Structured ensembles of random pure states, invariant with respect to local unitary…

Quantum Physics · Physics 2019-02-27 Karol Zyczkowski , Karol A. Penson , Ion Nechita , Benoit Collins

We develop a theoretical approach to compute the conditioned spectral density of $N \times N$ non-invariant random matrices in the limit $N \rightarrow \infty$. This large deviation observable, defined as the eigenvalue distribution…

Disordered Systems and Neural Networks · Physics 2018-08-15 Isaac Pérez Castillo , Fernando L. Metz

Let $\mathbf X=(X_{jk})$ denote a $n\times p$ random matrix with entries $X_{jk}$, which are independent for $1\le j\le n, 1\le k\le p$. Let $n,p$ tend to infinity such that $\frac np=y+O(n^{-1})\in(0,1]$. For those values of $n,p$ we…

Probability · Mathematics 2014-12-22 F. Götze , A. N. Tikhomirov

In this paper, we study the convergence rates of empirical spectral distribution of large dimensional quaternion sample covariance matrix. Assume that the entries of $\mathbf X_n$ ($p\times n$) are independent quaternion random variables…

Probability · Mathematics 2013-12-30 Huiqin LI , Zhidong Bai

We study the limiting spectral distribution of sample covariance matrices $XX^T$, where $X$ are $p\times n$ random matrices with correlated entries, for the cases $p/n\to y\in [0,\infty)$. If $y>0$, we obtain the Mar\v{c}enko-Pastur…

Probability · Mathematics 2019-10-29 Michael Fleermann , Johannes Heiny

We consider the limiting spectral distribution of matrices of the form $\frac{1}{2b_{n}+1} (R + X)(R + X)^{*}$, where $X$ is an $n\times n$ band matrix of bandwidth $b_{n}$ and $R$ is a non random band matrix of bandwidth $b_{n}$. We show…

Probability · Mathematics 2017-08-02 Indrajit Jana , Alexander Soshnikov

It is well known the sample covariance has a consistent bias in the spectrum, for example spectrum of Wishart matrix follows the Marchenko-Pastur law. We in this work introduce an iterative algorithm 'Concent' that actively eliminate this…

Machine Learning · Statistics 2022-01-04 Juntao Duan , Ionel Popescu , Heinrich Matzinger

Let $X_N$ be a $N \times N$ real Wishart random matrix with aspect ratio $M/N$. The limit eigenvalue distribution of $X_N$ is the Marchenko-Pastur law with parameter $c = \lim_N M/N$. The limit moments $\{m_n\}_n$ are given by $m_n =…

Probability · Mathematics 2025-07-30 James A. Mingo , Josue Vazquez-Becerra

We consider the problem of determining the limiting spectral distribution for random matrices whose row distributions are permitted to have limited dependence. We assume mild moment conditions and give an extension of the…

Probability · Mathematics 2018-01-16 Chris Connell , Pawan Patel

We study a $q$-deformed random unitary ensemble associated with the little-$q$ Laguerre weight, which provides a discrete analogue of the classical Laguerre unitary ensemble. In the double scaling regime $q=e^{-\lambda/N}$, where $N$ is the…

Probability · Mathematics 2026-01-15 Sung-Soo Byun , Yeong-Gwang Jung , Guido Mazzuca

We develop a theoretical framework based on the cavity and replica methods to analyze the spectral properties of sparse asymmetric correlation matrices of the form $\boldsymbol{F} = (\boldsymbol{X}\boldsymbol{Y}^\top + \omega…

Disordered Systems and Neural Networks · Physics 2025-10-21 Edgar Guzmán-González , Isaac Pérez Castillo