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In this paper we characterize the possible outliers in the spectrum of large deformed unitarily invariant additive and multiplicative models, as well as the eigenvectors corresponding to them. We allow both the non-deformed unitarily…

Probability · Mathematics 2015-03-23 Serban Teodor Belinschi , Hari Bercovici , Mireille Capitaine , Maxime Fevrier

Characterizing the asymptotic distributions of eigenvectors for large random matrices poses important challenges yet can provide useful insights into a range of statistical applications. To this end, in this paper we introduce a general…

Statistics Theory · Mathematics 2020-10-14 Jianqing Fan , Yingying Fan , Xiao Han , Jinchi Lv

Given a selfadjoint polynomial $P(X,Y)$ in two noncommuting selfadjoint indeterminates, we investigate the asymptotic eigenvalue behavior of the random matrix $P(A\_N,B\_N)$, where $A\_N$ and $B\_N$ are independent Hermitian random matrices…

Operator Algebras · Mathematics 2018-11-07 Serban Belinschi , Hari Bercovici , Mireille Capitaine

This is the second part of a study of the limiting distributions of the top eigenvalues of a Hermitian matrix model with spiked external source under a general external potential. The case when the external source is of rank one was…

Mathematical Physics · Physics 2012-05-30 Jinho Baik , Dong Wang

A Wishart matrix is said to be spiked when the underlying covariance matrix has a single eigenvalue $b$ different from unity. As $b$ increases through $b=2$, a gap forms from the largest eigenvalue to the rest of the spectrum, and with…

Mathematical Physics · Physics 2014-07-01 Peter J. Forrester

We consider a square random matrix of size N of the form A + Y where A is deterministic and Y has iid entries with variance 1/N. Under mild assumptions, as N grows, the empirical distribution of the eigenvalues of A+Y converges weakly to a…

Probability · Mathematics 2014-11-04 Charles Bordenave , Mireille Capitaine

Sample covariance matrices from multi-population typically exhibit several large spiked eigenvalues, which stem from differences between population means and are crucial for inference on the underlying data structure. This paper…

Statistics Theory · Mathematics 2024-09-16 Weiming Li , Zeng Li , Junpeng Zhu

A generalized Wigner matrix perturbed by a finite-rank deterministic matrix is considered. The fluctuations of the largest eigenvalues, which emerge outside the bulk of the spectrum, and the corresponding eigenvectors, are studied. Under…

Probability · Mathematics 2026-01-16 Bishakh Bhattacharya , Arijit Chakrabarty , Rajat Subhra Hazra

We study finite-rank normal deformations of rotationally invariant non-Hermitian random matrices. Extending the classical Baik-Ben Arous-P\'ech\'e (BBP) framework, we characterize the emergence and fluctuations of outlier eigenvalues in…

Disordered Systems and Neural Networks · Physics 2026-05-15 Pierre Bousseyroux , Marc Potters

Given a large, high-dimensional sample from a spiked population, the top sample covariance eigenvalue is known to exhibit a phase transition. We show that the largest eigenvalues have asymptotic distributions near the phase transition in…

Probability · Mathematics 2013-07-24 Alex Bloemendal , Bálint Virág

We investigate the asymptotic behavior of the eigenvalues of spiked perturbations of Wigner matrices when the dimension goes to infinity. The entries of the Hermitian Wigner matrix have a distribution which is symmetric and satisfies a…

Probability · Mathematics 2011-09-19 Mireille Capitaine , Catherine Donati-Martin , Delphine Féral , Maxime Février

Efficient schemes for sampling from the eigenvalues of the Wishart distribution have recently been described for both the uncorrelated central case (where the covariance matrix is $\mathbf{I}$) and the spiked Wishart with a single spike…

Computation · Statistics 2024-10-10 Thomas G. Brooks

The top eigenvalues of rank $r$ spiked real Wishart matrices and additively perturbed Gaussian orthogonal ensembles are known to exhibit a phase transition in the large size limit. We show that they have limiting distributions for…

Probability · Mathematics 2016-09-28 Alex Bloemendal , Bálint Virág

We consider general high-dimensional spiked sample covariance models and show that their leading sample spiked eigenvalues and their linear spectral statistics are asymptotically independent when the sample size and dimension are…

Statistics Theory · Mathematics 2020-09-25 Zhixiang Zhang , Shurong Zheng , Guangming Pan , Pingshou Zhong

We consider random matrices of the form $H = W + \lambda V$, $\lambda\in\mathbb{R}^+$, where $W$ is a real symmetric or complex Hermitian Wigner matrix of size $N$ and $V$ is a real bounded diagonal random matrix of size $N$ with i.i.d.\…

Probability · Mathematics 2014-01-15 Ji Oon Lee , Kevin Schnelli

We derive the joint asymptotic distribution of the outlier eigenvalues of an additively deformed Wigner matrix $H$. Our only assumptions on the deformation are that its rank be fixed and its norm bounded. Our results extend those of [The…

Probability · Mathematics 2014-09-04 Antti Knowles , Jun Yin

We consider the eigenvalues and eigenvectors of matrices of the form M + P, where M is an n by n Wigner random matrix and P is an arbitrary n by n deterministic matrix with low rank. In general, we show that none of the eigenvalues of M + P…

Probability · Mathematics 2016-04-21 Sean O'Rourke , Philip Matchett Wood

This text is about spiked models of non Hermitian random matrices. More specifically, we consider matrices of the type $A+P$, where the rank of $P$ stays bounded as the dimension goes to infinity and where the matrix $A$ is a non Hermitian…

Probability · Mathematics 2015-04-28 Florent Benaych-Georges , Jean Rochet

We consider large complex random sample covariance matrices obtained from "spiked populations", that is when the true covariance matrix is diagonal with all but finitely many eigenvalues equal to one. We investigate the limiting behavior of…

Mathematical Physics · Physics 2015-05-13 Delphine Féral , Sandrine Péché

Consider a real diagonal deterministic matrix $X_n$ of size $n$ with spectral measure converging to a compactly supported probability measure. We perturb this matrix by adding a random finite rank matrix, with delocalized eigenvectors. We…

Probability · Mathematics 2011-06-21 Florent Benaych-Georges , Alice Guionnet , Mylène Maïda