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Wishart correlation matrices are the standard model for the statistical analysis of time series. The ensemble averaged eigenvalue density is of considerable practical and theoretical interest. For complex time series and correlation…

Mathematical Physics · Physics 2011-01-28 Christian Recher , Mario Kieburg , Thomas Guhr

The sum of independent Wishart matrices, taken from distributions with unequal covariance matrices, plays a crucial role in multivariate statistics, and has applications in the fields of quantitative finance and telecommunication. However,…

Mathematical Physics · Physics 2014-09-23 Santosh Kumar

Data sets collected at different times and different observing points can possess correlations at different times $and$ at different positions. The doubly correlated Wishart model takes both into account. We calculate the eigenvalue density…

Mathematical Physics · Physics 2015-05-06 Daniel Waltner , Tim Wirtz , Thomas Guhr

Using a character expansion method, we calculate exactly the eigenvalue density of random matrices of the form M^\dagger M where M is a complex matrix drawn from a normalized distribution P(M) ~ exp(-\Tr(A M B M^\dagger) with A and B…

Mathematical Physics · Physics 2009-11-10 Steven H. Simon , Aris L. Moustakas

We consider four nontrivial ensembles involving Gaussian Wigner and Wishart matrices. These are relevant to problems ranging from multiantenna communication to random supergravity. We derive the matrix probability density, as well as the…

Mathematical Physics · Physics 2015-09-16 Santosh Kumar

Random matrices formed from i.i.d. standard real Gaussian entries have the feature that the expected number of real eigenvalues is non-zero. This property persists for products of such matrices, independently chosen, and moreover it is…

Mathematical Physics · Physics 2016-08-16 P. J. Forrester , J. R. Ipsen

We consider the product of n complex non-Hermitian, independent random matrices, each of size NxN with independent identically distributed Gaussian entries (Ginibre matrices). The joint probability distribution of the complex eigenvalues of…

Mathematical Physics · Physics 2015-06-11 G. Akemann , Z. Burda

The eigenvalue density for members of the Gaussian orthogonal and unitary ensembles follows the Wigner semi-circle law. If the Gaussian entries are all shifted by a constant amount c/Sqrt(2N), where N is the size of the matrix, in the large…

Mathematical Physics · Physics 2009-04-21 Kevin E. Bassler , Peter J. Forrester , Norman E. Frankel

In this work, we consider the weighted difference of two independent complex Wishart matrices and derive the joint probability density function of the corresponding eigenvalues in a finite-dimension scenario using two distinct approaches.…

Mathematical Physics · Physics 2020-11-17 Santosh Kumar , S. Sai Charan

Using the replica method, we compute the statistics of the top eigenpair of diluted covariance matrices of the form $\mathbf{J} = \mathbf{X}^T \mathbf{X}$, where $\mathbf{X}$ is a $N\times M$ sparse data matrix, in the limit of large $N,M$…

Statistical Mechanics · Physics 2025-08-01 Barak Budnick , Preben Forer , Pierpaolo Vivo , Sabrina Aufiero , Silvia Bartolucci , Fabio Caccioli

Consider the product of $M$ quadratic random matrices with complex elements and no further symmetry, where all matrix elements of each factor have a Gaussian distribution. This generalises the classical Wishart-Laguerre Gaussian Unitary…

Mathematical Physics · Physics 2013-06-28 Gernot Akemann , Mario Kieburg , Lu Wei

The eigenvalue densities of two random matrix ensembles, the Wigner Gaussian matrices and the Wishart covariant matrices, are decomposed in the contributions of each individual eigenvalue distribution. It is shown that the fluctuations of…

Mathematical Physics · Physics 2010-08-16 O. Bohigas , M. P. Pato

We compute the spectral statistics of the sum H of two independent complex Wishart matrices, each of which is correlated with a different covariance matrix. Random matrix theory enjoys many applications including sums and products of random…

Mathematical Physics · Physics 2016-07-05 Gernot Akemann , Tomasz Checinski , Mario Kieburg

We consider the singular value statistics of products of independent random matrices. In particular we compute the corresponding averages of products of characteristic polynomials. To this aim we apply the projection formula recently…

Mathematical Physics · Physics 2017-01-31 Mario Kieburg

In this study, we derive the exact distributions of eigenvalues of a singular Wishart matrix under an elliptical model. We define generalized heterogeneous hypergeometric functions with two matrix arguments and provide convergence…

Statistics Theory · Mathematics 2021-04-27 Aya Shinozaki , Koki Shimizu , Hiroki Hashiguchi

It has been recently shown that if $X$ is an $n\times N$ matrix whose entries are i.i.d. standard complex Gaussian and $l_1$ is the largest eigenvalue of $X^*X$, there exist sequences $m_{n,N}$ and $s_{n,N}$ such that…

Probability · Mathematics 2007-06-13 Noureddine El Karoui

The paper "An efficient sampling scheme for the eigenvalues of dual Wishart matrices", by I.~Santamar\'ia and V.~Elvira, [\emph{IEEE Signal Processing Letters}, vol.~28, pp.~2177--2181, 2021] \cite{SE21}, poses the question of efficient…

Statistics Theory · Mathematics 2024-01-24 Peter J. Forrester

This paper is the second chapter of three of the author's undergraduate thesis. In this paper, we consider the random matrix ensemble given by $(d_b, d_w)$-regular graphs on $M$ black vertices and $N$ white vertices, where $d_b \in…

Probability · Mathematics 2018-01-18 Kevin Yang

We consider an $N$ by $N$ real or complex generalized Wigner matrix $H_N$, whose entries are independent centered random variables with uniformly bounded moments. We assume that the variance profile, $s_{ij}:=\mathbb{E} |H_{ij}|^2$,…

Probability · Mathematics 2020-08-20 Yiting Li , Yuanyuan Xu

We study the eigenvalue behaviour of large complex correlated Wishart matrices near an interior point of the limiting spectrum where the density vanishes (cusp point), and refine the existing results at the hard edge as well. More…

Probability · Mathematics 2016-03-08 Walid Hachem , Adrien Hardy , Jamal Najim
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