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Consider a $N\times n$ random matrix $Y_n=(Y_{ij}^{n})$ where the entries are given by $Y_{ij}^{n}=\frac{\sigma(i/N,j/n)}{\sqrt{n}} X_{ij}^{n}$, the $X_{ij}^{n}$ being centered i.i.d. and $\sigma:[0,1]^2 \to (0,\infty)$ being a continuous…

Probability · Mathematics 2007-06-13 W. Hachem , P. Loubaton , J. Najim

We consider measure-valued processes $X=(X_t)$ that solve the following martingale problem: for a given initial measure $X_0$, and for all smooth, compactly supported test functions $\varphi$, \begin{eqnarray*}X_t(\varphi…

Probability · Mathematics 2014-01-15 Steven P. Lalley , Edwin A. Perkins , Xinghua Zheng

We show that repulsive random variables can yield Monte Carlo methods with faster convergence rates than the typical $N^{-1/2}$, where $N$ is the number of integrand evaluations. More precisely, we propose stochastic numerical quadratures…

Probability · Mathematics 2019-06-18 Rémi Bardenet , Adrien Hardy

Let $X_N$ be a $N\times N$ matrix whose entries are i.i.d. complex random variables with mean zero and variance $\frac{1}{N}$. We study the asymptotic spectral distribution of the eigenvalues of the covariance matrix $X_N^*X_N$ for…

Mathematical Physics · Physics 2015-06-05 Claudio Cacciapuoti , Anna Maltsev , Benjamin Schlein

We study the asymptotic behaviour of a critical decomposable 3-type Galton-Watson process with immigration when its offspring mean matrix is triangular with diagonal entries 1. It is proved that, under second or fourth order moment…

Probability · Mathematics 2024-06-17 Matyas Barczy , Dániel Bezdány

The asymptotic normality of conditional least squares estimators for the offspring variance in critical branching processes with non-homogeneous immigration is established, under moment assumptions on both reproduction and immigration. The…

Statistics Theory · Mathematics 2012-05-07 Ibrahim Rahimov , George P. Yanev

A curious connection exists between the theory of optimal stopping for independent random variables, and branching processes. In particular, for the branching process $Z_n$ with offspring distribution $Y$, there exists a random variable $X$…

Probability · Mathematics 2007-05-23 David Assaf , Larry Goldstein , Ester Samuel-Cahn

Let $X^{(\delta)}$ be a Wishart process of dimension $\delta$, with values in the set of positive matrices of size $m$. We are interested in the large deviations for a family of matrix-valued processes $\{\delta^{-1} X_t^{(\delta)}, t \leq…

Probability · Mathematics 2007-05-23 Catherine Donati-Martin

Consider a branching process $\{Z_n\}_{n\ge 0}$ with immigration in varying environment. For $a\in\{0,1,2,...\},$ let $C=\{n\ge0:Z_n=a\}$ be the collection of times at which the population size of the process attains level $a.$ We give a…

Probability · Mathematics 2023-08-08 Hua-Ming Wang

Suppose that $X=\{X_t, t\ge 0; \mathbb{P}_{\mu}\}$ is a supercritical superprocess in a locally compact separable metric space $E$. Let $\phi_0$ be a positive eigenfunction corresponding to the first eigenvalue $\lambda_0$ of the generator…

Probability · Mathematics 2018-08-30 Yan-Xia Ren , Renming Song , Rui Zhang

We consider $n^2\times n^2$ real symmetric and hermitian matrices $M_n$, which are equal to sum of $m_n$ tensor products of vectors $X^\mu=B(Y^\mu\otimes Y^\mu)$, $\mu=1,\dots,m_n$, where $Y^\mu$ are i.i.d. random vectors from $\mathbb R^n…

Mathematical Physics · Physics 2020-03-11 Daria Tieplova

We provide some asymptotic theory for the largest eigenvalues of a sample covariance matrix of a p-dimensional time series where the dimension p = p_n converges to infinity when the sample size n increases. We give a short overview of the…

Statistics Theory · Mathematics 2016-04-27 Richard Davis , Johannes Heiny , Thomas Mikosch , Xiaolei Xie

We consider a supercritical branching process $Z_n$ in a stationary and ergodic random environment $\xi =(\xi_n)_{n\ge0}$. Due to the martingale convergence theorem, it is known that the normalized population size $W_n=Z_n/ (\mathbb E…

Probability · Mathematics 2018-06-14 Ewa Damek , Nina Gantert , Konrad Kolesko

We demonstrate the use of a variational method to determine a quantitative lower bound on the rate of convergence of Markov Chain Monte Carlo (MCMC) algorithms as a function of the target density and proposal density. The bound relies on…

Data Analysis, Statistics and Probability · Physics 2013-05-29 Fergal P. Casey , Joshua J. Waterfall , Ryan N. Gutenkunst , Christopher R. Myers , James P. Sethna

Suppose that $X=\{X_t, t\ge 0\}$ is a supercritical superprocess on a locally compact separable metric space $(E, m)$. Suppose that the spatial motion of $X$ is a Hunt process satisfying certain conditions and that the branching mechanism…

Probability · Mathematics 2015-02-10 Zhen-Qing Chen , Yan-Xia Ren , Renming Song , Rui Zhang

This paper studies the behaviour of the empirical eigenvalue distribution of large random matrices W_N W_N* where W_N is a ML x N matrix, whose M block lines of dimensions L x N are mutually independent Hankel matrices constructed from…

Probability · Mathematics 2017-04-25 Philippe Loubaton , Xavier Mestre

In this paper we study the joint distributional convergence of the largest eigenvalues of the sample covariance matrix of a $p$-dimensional time series with iid entries when $p$ converges to infinity together with the sample size $n$. We…

Probability · Mathematics 2016-08-26 Johannes Heiny , Thomas Mikosch

We consider an inhomogeneous Erd\H{o}s-R\'enyi random graph $G_N$ with vertex set $[N] = \{1,\dots,N\}$ for which the pair of vertices $i,j \in [N]$, $i\neq j$, is connected by an edge with probability $r_N(\tfrac{i}{N},\tfrac{j}{N})$,…

Probability · Mathematics 2025-01-08 Rajat Subhra Hazra , Frank den Hollander , Maarten Markering

We compute analytically the probability of large fluctuations to the left of the mean of the largest eigenvalue in the Wishart (Laguerre) ensemble of positive definite random matrices. We show that the probability that all the eigenvalues…

Statistical Mechanics · Physics 2009-11-13 Pierpaolo Vivo , Satya N. Majumdar , Oriol Bohigas

We consider a matrix branching random walk on the semi-group of nonnegative matrices, where we are able to derive, under general assumptions, an analogue of Biggins' martingale convergence theorem for the additive martingale $W_n$, a spinal…

Probability · Mathematics 2025-07-15 Ion Grama , Sebastian Mentemeier , Hui Xiao
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