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We find the exponential exact two-terms non-asymptotic expression for the maximum and minimum distribution of a non-Gaussian, in general case, random vector.

Probability · Mathematics 2022-06-09 M. R. Formica , E. Ostrovsky , L. Sirota

We study an asymptotic behaviour of parametric autoresonance for non-linear equation. Main result of this work is statement about asymptotic behaviour of measure for captured trajectories. To find this we obtain an asymptotic expansion for…

Dynamical Systems · Mathematics 2016-12-28 O. M. Kiselev

Using an intrinsic approach, we study some properties of random fields which appear as tail fields of regularly varying stationary random fields. The index set is allowed to be a general locally compact Hausdorff Abelian group $\mathbb{G}$.…

Probability · Mathematics 2023-01-11 Günter Last

The sub-Gaussian stable distribution is a heavy-tailed elliptically contoured law which has interesting applications in signal processing and financial mathematics. This work addresses the problem of feasible estimation of distributions. We…

Statistics Theory · Mathematics 2022-08-04 Taras Bodnar , Dmitry Otryakhin , Erik Thorsen

We determine the asymptotics of the joint eigenfunctions of the torus action on a toric Kahler variety. Such varieties are models of completely integrable systems in complex geometry. We first determine the pointwise asymptotics of the…

Complex Variables · Mathematics 2007-05-23 Bernard Shiffman , Tatsuya Tate , Steve Zelditch

We propose the notion of sub-Weibull distributions, which are characterised by tails lighter than (or equally light as) the right tail of a Weibull distribution. This novel class generalises the sub-Gaussian and sub-Exponential families to…

Statistics Theory · Mathematics 2020-12-04 Mariia Vladimirova , Stephane Girard , Hien Nguyen , Julyan Arbel

We investigate the tail asymptotics of the supremum of X(t)+Y(t)-ct, where X={X(t),t\geq 0} and Y={Y(t),t\geq 0} are two independent stochastic processes. We assume that the process Y has subexponential characteristics and that the process…

Probability · Mathematics 2007-05-23 Bert Zwart , Sem Borst , Krzystof Debicki

Symmetry is a cornerstone of much of mathematics, and many probability distributions possess symmetries characterized by their invariance to a collection of group actions. Thus, many mathematical and statistical methods rely on such…

Statistics Theory · Mathematics 2023-10-23 Adam B Kashlak

The asymptotic behavior of the tail probabilities for the first hitting times of the Bessel process with arbitrary index is shown without using the explicit expressions for the distribution function obtained in the authors' previous works.

Probability · Mathematics 2016-02-17 Yuji Hamana , Hiroyuki Matsumoto

We investigate Bayes posterior distributions in high-dimensional generalized linear models (GLMs) under the proportional asymptotics regime, where the number of features and samples diverge at a comparable rate. Specifically, we…

Statistics Theory · Mathematics 2026-01-05 Manuel Sáenz , Pragya Sur

In this paper, according to a certain criterion, we divide the exponential distribution class into three subclasses. One of them is closely related to the regular-variation-tailed distribution class, so it is called the…

Probability · Mathematics 2018-05-30 Zhaolei Cui , Edward Omey , Wenyuan Wang , Yuebao Wang

Tail Gini functional is a measure of tail risk variability for systemic risks, and has many applications in banking, finance and insurance. Meanwhile, there is growing attention on aymptotic independent pairs in quantitative risk…

Methodology · Statistics 2023-09-13 Zhaowen Wang , Liujun Chen , Deyuan Li

In this paper, we propose a kernel method for exact tail asymptotics of a random walk to neighborhoods in the quarter plane. This is a two-dimensional method, which does not require a determination of the unknown generating function(s).…

Probability · Mathematics 2015-05-19 Hui Li , Yiqiang Q. Zhao

This contribution establishes exact tail asymptotics of $\sup_{(s,t)\in\mathbf{E}}$ $X(s,t)$ for a large class of nonhomogeneous Gaussian random fields $X$ on a bounded convex set $\mathbf{E}\subset\mathbb{R}^2$, with variance function that…

Probability · Mathematics 2016-03-16 Krzysztof Dȩbicki , Enkelejd Hashorva , Lanpeng Ji

We consider a Markov chain on $R^+$ with asymptotically zero drift and finite second moments of jumps which is positive recurrent. A power-like asymptotic behaviour of the invariant tail distribution is proven; such a heavy-tailed invariant…

Probability · Mathematics 2012-08-16 Denis Denisov , Dmitry Korshunov , Vitali Wachtel

We investigate the asymptotic variance of Gaussian nodal excursions in the Euclidean space, focusing on the case where the spectral measure has incommensurable atoms. This study requires to establish fine recurrence properties in 0 for the…

Probability · Mathematics 2022-09-22 Raphaël Lachièze-Rey

Consider $n$ i.i.d. random elements on $C[0,1]$. We show that, under an appropriate strengthening of the domain of attraction condition, natural estimators of the extreme-value index, which is now a continuous function, and the normalizing…

Statistics Theory · Mathematics 2007-06-13 John H. J. Einmahl , Tao Lin

Let $Y=\sum_{k\ge 1} 1_{A_k}$ be an infinite sum of the indicators of independent events. We investigate a precise (as opposed to logarithmic) first-order asymptotic behavior of the tail probabilities $\mathbb{P}\{Y\ge n\}$ and the point…

Probability · Mathematics 2026-02-10 Alexander Iksanov , Valeriya Kotelnikova

Experiments involving the two-dimensional passive diffusion of colloidal boomerangs tracked off their centre of mobility have shown striking non-Gaussian tails in their probability distribution function [Chakrabarty et al., Soft Matter 12,…

Soft Condensed Matter · Physics 2018-04-18 Lyndon Koens , Maciej Lisicki , Eric Lauga

The geometric mean is shown to be an appropriate statistic for the scale of a heavy-tailed coupled Gaussian distribution or equivalently the Student's t distribution. The coupled Gaussian is a member of a family of distributions…

Methodology · Statistics 2018-11-14 Kenric P. Nelson , Mark A. Kon , Sabir R. Umarov
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