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In the present paper we obtain rates of convergence for the limit theorems of the density vector in the Curie-Weiss-Potts model via Stein's Method of exchangeable pairs. Our results include Kolmogorov bounds for multivariate normal…

Probability · Mathematics 2013-01-10 Peter Eichelsbacher , Bastian Martschink

We study an "inner-product kernel" random matrix model, whose empirical spectral distribution was shown by Xiuyuan Cheng and Amit Singer to converge to a deterministic measure in the large $n$ and $p$ limit. We provide an interpretation of…

Probability · Mathematics 2017-02-03 Zhou Fan , Andrea Montanari

This paper aims to examine the characteristics of the posterior distribution of covariance/precision matrices in a "large $p$, large $n$" scenario, where $p$ represents the number of variables and $n$ is the sample size. Our analysis…

Statistics Theory · Mathematics 2026-02-02 Partha Sarkar , Kshitij Khare , Malay Ghosh , Matt P. Wand

We derive the universality principle for empirical spectral distributions of sample covariance matrices and their Stieltjes transforms. This principle states the following. Suppose quadratic forms of random vectors $y_p$ in $R^p$ satisfy a…

Probability · Mathematics 2014-12-23 Pavel Yaskov

The eigenvector empirical spectral distribution (VESD) is a useful tool in studying the limiting behavior of eigenvalues and eigenvectors of covariance matrices. In this paper, we study the convergence rate of the VESD of sample covariance…

Probability · Mathematics 2020-08-19 Haokai Xi , Fan Yang , Jun Yin

In practice, observations are often contaminated by noise, making the resulting sample covariance matrix a signal-plus-noise sample covariance matrix. Aiming to make inferences about the spectral distribution of the population covariance…

Statistics Theory · Mathematics 2017-03-02 Ningning Xia , Xinghua Zheng

In this paper, we derive distributional convergence rates for the magnetization vector and the maximum pseudolikelihood estimator of the inverse temperature parameter in the tensor Curie-Weiss Potts model. Limit theorems for the…

Probability · Mathematics 2024-07-08 Sanchayan Bhowal , Somabha Mukherjee

We study the asymptotic behavior of the spectra of matrices of the form $S_n = \frac{1}{n}XX^*$ where $X =\sum_{r=1}^K X_r$, where $X_r = A_r^\frac{1}{2}Z_rB_r^\frac{1}{2}$, $K \in \mathbb{N}$ and $A_r,B_r$ are sequences of positive…

Statistics Theory · Mathematics 2026-02-03 Javed Hazarika , Debashis Paul

Hochst\"attler, Kirsch, and Warzel showed that the semicircle law holds for generalized Curie-Weiss matrix ensembles at or above the critical temperature. We extend their result to the case of subcritical temperatures for which the…

Mathematical Physics · Physics 2017-03-16 Werner Kirsch , Thomas Kriecherbauer

We study the thermodynamic properties of the generalized non-convex multispecies Curie-Weiss model, where interactions among different types of particles (forming the species) are encoded in a generic matrix. For spins with a generic prior…

Mathematical Physics · Physics 2025-02-28 Francesco Camilli , Emanuele Mingione , Godwin Osabutey

We consider a spherical spin system with pure 2-spin spherical Sherrington-Kirkpatrick Hamiltonian with ferromagnetic Curie-Weiss interaction. The system shows a two-dimensional phase transition with respect to the temperature and the…

Probability · Mathematics 2018-03-28 Jinho Baik , Ji Oon Lee

The random field Curie-Weiss model is derived from the classical Curie-Weiss model by replacing the deterministic global magnetic field by random local magnetic fields. This opens up a new and interestingly rich phase structure. In this…

Probability · Mathematics 2013-04-18 Matthias Löwe , Raphael Meiners

This paper discusses fluctuations of linear spectral statistics of high-dimensional sample covariance matrices when the underlying population follows an elliptical distribution. Such population often possesses high order correlations among…

Statistics Theory · Mathematics 2018-03-22 Jiang Hu , Weiming Li , Zhi Liu , Wang Zhou

We investigate increasing propagation of chaos for the mean-field Ising model of ferromagnetism (also known as the Curie-Weiss model) with $N$ spins at inverse temperature $\beta>0$ and subject to an external magnetic field of strength…

Probability · Mathematics 2023-07-12 Jonas Jalowy , Zakhar Kabluchko , Matthias Löwe , Alexander Marynych

We introduce a random matrix model for the stationary covariance of multivariate Ornstein-Uhlenbeck processes with heterogeneous temperatures, where the covariance is constrained by the Sylvester-Lyapunov equation. Using the replica method,…

Disordered Systems and Neural Networks · Physics 2025-01-30 Leonardo Ferreira , Fernando Metz , Paolo Barucca

In this paper, we derive limit laws for the empirical spectral distributions of random band and block matrices with correlated entries. In the first part of the paper, we study band matrices with approximately uncorrelated entries. We…

Probability · Mathematics 2022-02-11 Riccardo Catalano , Michael Fleermann , Werner Kirsch

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

We consider the $2$-spin spherical Sherrington--Kirkpatrick model whose disorder is given by a deformed Wigner matrix of the form $W+\lambda V$, where $W$ is a Wigner matrix and $V$ is a random diagonal matrix with i.i.d. entries. Assuming…

Probability · Mathematics 2022-10-13 Ji Oon Lee , Yiting Li

We study the spectral properties of a class of random matrices of the form $S_n^{-} = n^{-1}(X_1 X_2^* - X_2 X_1^*)$ where $X_k = \Sigma^{1/2}Z_k$, for $k=1,2$, $Z_k$'s are independent $p\times n$ complex-valued random matrices, and…

Statistics Theory · Mathematics 2024-11-27 Javed Hazarika , Debashis Paul

We compute the limiting distributions of the largest eigenvalue of a complex Gaussian sample covariance matrix when both the number of samples and the number of variables in each sample become large. When all but finitely many, say $r$,…

Probability · Mathematics 2007-05-23 Jinho Baik , Gerard Ben Arous , Sandrine Peche