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Let $M_n^{(k)}$ denote the $k$th largest maximum of a sample $(X_1,X_2,...,X_n)$ from parent $X$ with continuous distribution. Assume there exist normalizing constants $a_n>0$, $b_n\in \mathbb{R}$ and a nondegenerate distribution $G$ such…

Statistics Theory · Mathematics 2008-10-06 Zuoxiang Peng , Jiaona Li , Saralees Nadarajah

We consider the eigenvalues of sample covariance matrices of the form $\mathcal{Q}=(\Sigma^{1/2}X)(\Sigma^{1/2}X)^*$. The sample $X$ is an $M\times N$ rectangular random matrix with real independent entries and the population covariance…

Probability · Mathematics 2020-09-16 Jinwoong Kwak , Ji Oon Lee , Jaewhi Park

In this paper, we address the problem of packing large trees in $G_{n,p}$. In particular, we prove the following result. Suppose that $T_1, \dotsc, T_N$ are $n$-vertex trees, each of which has maximum degree at most $(np)^{1/6} / (\log…

Combinatorics · Mathematics 2018-10-03 Asaf Ferber , Wojciech Samotij

We consider the branching random walk on the real line where the underlying motion is of a simple random walk and branching is at least binary and at most decaying exponentially in law. It is well known that the normalized empirical measure…

Probability · Mathematics 2012-07-11 Oren Louidor , Will Perkins

This paper can be thought of as a remark of \cite{llw}, where the authors studied the eigenvalue distribution $\mu_{X_N}$ of random block Toeplitz band matrices with given block order $m$. In this note we will give explicit density…

Probability · Mathematics 2011-08-16 Yi-Ting Li , Dang-Zheng Liu , Xin Sun , Zheng-Dong Wang

In this paper we study the diameter of the random graph $G(n,p)$, i.e., the the largest finite distance between two vertices, for a wide range of functions $p=p(n)$. For $p=\la/n$ with $\la>1$ constant, we give a simple proof of an…

Probability · Mathematics 2010-10-07 Oliver Riordan , Nicholas Wormald

This paper explores the problem of generative modeling, aiming to simulate diverse examples from an unknown distribution based on observed examples. While recent studies have focused on quantifying the statistical precision of popular…

Statistics Theory · Mathematics 2024-06-07 Elen Vardanyan , Sona Hunanyan , Tigran Galstyan , Arshak Minasyan , Arnak Dalalyan

In this paper, we consider approximating expansions for the distribution of integer valued random variables, in circumstances in which convergence in law cannot be expected. The setting is one in which the simplest approximation to the…

Probability · Mathematics 2009-12-11 A. D. Barbour , E. Kowalski , A. Nikeghbali

Rank 1 inhomogeneous random graphs are a natural generalization of Erd\H{o}s R\'enyi random graphs. In this generalization each node is given a weight. Then the probability that an edge is present depends on the product of the weights of…

Probability · Mathematics 2021-07-28 Othmane Safsafi

In this paper we study a random graph with $N$ nodes, where node $j$ has degree $D_j$ and $\{D_j\}_{j=1}^N$ are i.i.d. with $\prob(D_j\leq x)=F(x)$. We assume that $1-F(x)\leq c x^{-\tau+1}$ for some $\tau>3$ and some constant $c>0$. This…

Probability · Mathematics 2007-05-23 Remco van der Hofstad , Gerard Hooghiemstra , Piet Van Mieghem

We suggest approximating the distribution of the sum of independent and identically distributed random variables with a Pareto-like tail by combining extreme value approximations for the largest summands with a normal approximation for the…

Probability · Mathematics 2018-02-05 Ulrich K. Mueller

We study how the spectral gap and diameter of Cayley graphs depend strongly on the choice of generating set. We answer a question of Pyber and Szab\'o (2013) by exhibiting a sequence of finite groups $G_n$ with $|G_n| \to \infty$ admitting…

Group Theory · Mathematics 2026-02-17 Sean Eberhard , Luca Sabatini

The article studies the almost surely asymptotics of extreme values $\bar{\xi}_n = \max_{1\leq i \leq n} \xi_i$, where $ \xi , \xi_1 , \xi_2 , \ldots$ are discrete identically distributed random variables. One of the main results on this…

Probability · Mathematics 2025-03-27 Kateryna Akbash , Ivan Matsak

Let $\mathbf{W}$ be a correlated complex non-central Wishart matrix defined through $\mathbf{W}=\mathbf{X}^H\mathbf{X}$, where $\mathbf{X}$ is $n\times m \, (n\geq m)$ complex Gaussian with non-zero mean $\boldsymbol{\Upsilon}$ and…

Statistics Theory · Mathematics 2015-03-17 Prathapasinghe Dharmawansa , Matthew R. McKay

We establish a lower bound on the entropy of weighted sums of (possibly dependent) random variables $(X_1, X_2, \dots, X_n)$ possessing a symmetric joint distribution. Our lower bound is in terms of the joint entropy of $(X_1, X_2, \dots,…

Information Theory · Computer Science 2018-01-16 Jing Hao , Varun Jog

The paper is devoted to infinite Bernoulli convolutions generated by positive multigeometric series and to probability distributions of random variables whose digits in an even integer base-$s$ expansion with two redundant digits form a…

Probability · Mathematics 2026-03-13 Mykola Pratsiovytyi , Dmytro Karvatskyi , Oleg Makarchuk

We consider a discrete time random walk in one dimension. At each time step the walker jumps by a random distance, independent from step to step, drawn from an arbitrary symmetric density function. We show that the expected positive maximum…

Statistical Mechanics · Physics 2009-11-11 Alain Comtet , Satya N. Majumdar

The Generalized Pareto (GP) and Generalized extreme value (GEV) distributions play an important role in extreme value analyses, as models for threshold excesses and block maxima respectively. For each of these distributions we consider…

Methodology · Statistics 2016-06-02 Paul J. Northrop , Nicolas Attalides

We study the largest eigenvalue of a Gaussian random symmetric matrix $X_n$, with zero-mean, unit variance entries satisfying the condition $\sup_{(i, j) \ne (i', j')}|\mathbb{E}[X_{ij} X_{i'j'}]| = O(n^{-(1 + \varepsilon)})$, where…

Probability · Mathematics 2025-02-10 Debapratim Banerjee , Soumendu Sundar Mukherjee , Dipranjan Pal

In this paper, we consider a data matrix $X_N\in\mathbb{R}^{N\times p}$ where all the rows are i.i.d. samples in $\mathbb{R}^p$ of mean zero and covariance matrix $\Sigma\in\mathbb{R}^{p\times p}$. Here the population matrix $\Sigma$ is of…

Probability · Mathematics 2013-05-06 Dai Shi