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We study asymptotic behavior of the moments $M_k(\lambda)$ of the sum $X_1+\dots+X_{N_\lambda}$, where $N_\lambda$ follows the Poisson probability distribution with mean value $\lambda$ and $\{X_j\}$ is a family of i.i.d. random variables…

Probability · Mathematics 2024-11-08 O. Khorunzhiy

The first two terms in the large $N$ asymptotic expansion of the $\beta$ moment of the characteristic polynomial for the Gaussian and Laguerre $\beta$-ensembles are calculated. This is used to compute the asymptotic expansion of the…

Mathematical Physics · Physics 2015-06-16 Peter J. Forrester

For a centered, homogeneous R^d-valued Gaussian random field X(t), t in R^k, with covariance matrix function R(s,t) = E[X(s) X(t)^T], we investigate the exact asymptotics of kappa_u(x) = P( theta(u) * integral over [0,T]^k of 1{X(t) > u b}…

Probability · Mathematics 2025-10-09 Krzysztof Dębicki , Enkelejd Hashorva , Zbigniew Michna

This paper investigates the asymptotic behavior of the extremes of a sequence of generalized Oppenheim random variables. Particularly, we establish conditions under which some normalized extremes of sequences arising from Oppenheim…

Probability · Mathematics 2024-05-21 Milto Hadjikyriakou , Rita Giuliano

In this paper, we consider a two-dimensional sticky Brownian motion. Sticky Brownian motions can be viewed as time-changed semimartingale reflecting Brownian motions, which find applications in many areas including queueing theory and…

Probability · Mathematics 2018-06-13 Hongshuai Dai , Yiqiang Q. Zhao

We reconsider a classical, well-studied problem from applied probability. This is the max-sum equivalence of randomly weighted sums, and the originality is because we manage to include interdependence among the primary random variables, as…

We examine the rate of decay to the limit of the tail dependence coefficient of a bivariate skew t distribution which always displays asymptotic tail dependence. It contains as a special case the usual bivariate symmetric t distribution,…

Statistics Theory · Mathematics 2013-12-05 Thomas Fung , Eugene Seneta

Modeling and understanding multivariate extreme events is challenging, but of great importance in various applications - e.g. in biostatistics, climatology, and finance. The separating Hill estimator can be used in estimating the extreme…

Statistics Theory · Mathematics 2016-01-13 Matias Heikkilä , Yves Dominicy , Pauliina Ilmonen

For a stochastic difference equation $D_n=A_nD_{n-1}+B_n$ which stabilises upon time we study tail distribution asymptotics of $D_n$ under the assumption that the distribution of $\log(1+|A_1|+|B_1|)$ is heavy-tailed, that is, all its…

Probability · Mathematics 2020-07-28 Dmitry Korshunov

Let $X_{1},..,X_{n}$ denote an i.i.d. sample with light tail distribution and $S_{1}^{n}$ denote the sum of its terms; let $a_{n}$ be a real sequence\ going to infinity with $n.$\ In a previous paper (\cite{BoniaCao}) it is proved that as…

Statistics Theory · Mathematics 2013-05-16 Michel Broniatowski , Zhansheng Cao

Extreme events over large spatial domains may exhibit highly heterogeneous tail dependence characteristics, yet most existing spatial extremes models yield only one dependence class over the entire spatial domain. To accurately characterize…

Methodology · Statistics 2025-11-14 Muyang Shi , Likun Zhang , Mark D. Risser , Benjamin A. Shaby

We consider random rectangles in $\mathbb{R}^2$ that are distributed according to a Poisson random measure, i.e., independently and uniformly scattered in the plane. The distributions of the length and the width of the rectangles are…

Probability · Mathematics 2018-06-29 Frank Aurzada , Sebastian Schwinn

In this paper, we establish the first and the second-order asymptotics of distributions of normalized maxima of independent and non-identically distributed bivariate Gaussian triangular arrays, where each vector of the $n$th row follows…

Methodology · Statistics 2016-04-27 Xin Liao , Zuoxiang Peng

The problem of estimating the coefficient of bivariate tail dependence is considered here from the robustness point of view; it combines two apparently contradictory theories of robust statistics and extreme value statistics. The usual…

Applications · Statistics 2014-07-08 Abhik Ghosh

Models based on assumptions of multivariate regular variation and hidden regular variation provide ways to describe a broad range of extremal dependence structures when marginal distributions are heavy tailed. Multivariate regular variation…

Probability · Mathematics 2007-05-23 Janet E. Heffernan , Sidney I. Resnick

We study the large-time asymptotic of renewal-reward processes with a heavy-tailed waiting time distribution. It is known that the heavy tail of the distribution produces an extremely slow dynamics, resulting in a singular large deviation…

Mathematical Physics · Physics 2022-01-05 Hiroshi Horii , Raphael Lefevere , Takahiro Nemoto

Let $\{X_t, t \geq 1\}$ be a sequence of identically distributed and pairwise asymptotically independent random variables with regularly varying tails and $\{ \Theta_t, t\geq1 \}$ be a sequence of positive random variables independent of…

Probability · Mathematics 2017-09-05 Rajat Subhra Hazra , Krishanu Maulik

Given a sequence of real rooted polynomials $\{p_n\}_{n\geq 1}$ with a fixed asymptotic root distribution, we study the asymptotic root distribution of the repeated polar derivatives of this sequence. This limiting distribution can be seen…

Probability · Mathematics 2025-08-27 Daniel Perales , Zhiyuan Yang

We consider a multi-type branching random walk with displacements that have either regularly varying or semi-exponential tails. We investigate the asymptotic behavior of the rightmost particle in irreducible and reducible regimes and…

Probability · Mathematics 2025-09-19 Krzysztof Kowalski

We investigate the asymptotic behavior of the empirical eigenvalues distribution of the partial transpose of a random quantum state. The limiting distribution was previously investigated via Wishart random matrices indirectly (by…

Mathematical Physics · Physics 2013-07-16 Motohisa Fukuda , Piotr Śniady
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