English
Related papers

Related papers: Exact Asymptotic for the Tail of Maximum of Smooth…

200 papers

In this paper, we study critical and subcritical branching $\alpha$-stable processes, $\alpha \in (0, 2)$. We obtain the exact asymptotic behaviors of the tails of the maximal positions of all subcritical branching $\alpha$-stable processes…

Probability · Mathematics 2025-04-09 Haojie Hou , Yiyang Jiang , Yan-Xia Ren , Renming Song

Let $\{Z(\tau,s), (\tau,s)\in [a,b]\times[0,T]\}$ with some positive constants $a,b,T$ be a centered Gaussian random field with variance function $\sigma^{2}(\tau,s)$ satisfying $\sigma^{2}(\tau,s)=\sigma^{2}(\tau)$. We firstly derive the…

Probability · Mathematics 2019-10-10 Zhongquan Tan , Shengchao Zheng

In this paper we consider the distribution of the maximum of a Gaussian field defined on non locally convex sets. Adler and Taylor or Aza\"\i s and Wschebor give the expansions in the locally convex case. The present paper generalizes their…

Probability · Mathematics 2016-01-25 Jean-Marc Azaïs , Viet-Hung Pham

Let X be a generalised symmetrised Dirichlet random vector in R^k, and let u_n be thresholds such that P{X> u_n} tends to 0 as n goes infinity. In this paper we derive an exact asymptotic expansion of P{X> u_n} assuming that the associated…

Probability · Mathematics 2010-04-20 Enkelejd Hashorva

This paper presents a saddlepoint approximation of the random-coding union bound of Polyanskiy et al. for i.i.d. random coding over discrete memoryless channels. The approximation is single-letter, and can thus be computed efficiently.…

Information Theory · Computer Science 2014-04-28 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

We derive the first exact, rigorous but practical, globally valid remainder terms for asymptotic expansions about saddles and contour endpoints of arbitrary order degeneracy derived from the method of steepest descents. The exact remainder…

Classical Analysis and ODEs · Mathematics 2018-04-19 Thomas Bennett , Christopher J. Howls , Gergő Nemes , Adri B. Olde Daalhuis

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

We derive subexponential tail asymptotics for the distribution of the maximum of a compound renewal process with linear component and of a L\'evy process, both with negative drift, over random time horizon $\tau$ that does not depend on the…

Probability · Mathematics 2024-10-07 Sergey Foss , Dmitry Korshunov , Zbigniew Palmowski

We construct an example of a continuous centered random process with light tails of finite-dimensional distribution but with (relatively) heavy tail of maximum distribution. The apparatus for tails comparison are embedding results for…

Probability · Mathematics 2015-08-25 Eugene Ostrovsky , Leonid Sirota

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 consider a discrete-time two-dimensional quasi-birth-and-death process (2d-QBD process for short) $\{(\boldsymbol{X}_n,J_n)\}$ on $\mathbb{Z}_+^2\times S_0$, where $\boldsymbol{X}_n=(X_{1,n},X_{2,n})$ is the level state, $J_n$ the phase…

Probability · Mathematics 2022-02-23 Toshihisa Ozawa

In this paper non-asymptotic moment estimates are derived for tail of distribution for discrete time polynomial martingale by means of martingale differences as a rule in the terms of unconditional and unconditional relative moments and…

Probability · Mathematics 2014-10-06 E. Ostrovsky , L. Sirota

We consider the sums $S_n=\xi_1+\cdots+\xi_n$ of independent identically distributed random variables. We do not assume that the $\xi$'s have a finite mean. Under subexponential type conditions on distribution of the summands, we find the…

Probability · Mathematics 2013-03-20 D. Denisov , S. Foss , D. Korshunov

In this paper, we study the asymptotic behaviour of the product tail probability $ \mathbb{P}(\xi_1\cdots\xi_N \geqslant n), $ where $\{\xi_1,\ldots,\xi_N\}$ is a finite collection of independent Poisson random variables with positive…

Probability · Mathematics 2026-04-06 Džiugas Chvoinikov , Jonas Šiaulys

We deal with a discrete-time two-dimensional quasi-birth-and-death process (2d-QBD process for short) on $\mathbb{Z}_+^2\times S_0$, where $S_0$ is a finite set, and give a complete expression for the asymptotic decay function of the…

Probability · Mathematics 2023-02-28 Toshihisa Ozawa

Asymptotic expansions are derived for the tail distribution of the product of two correlated normal random variables with non-zero means and arbitrary variances, and more generally the sum of independent copies of such random variables.…

Probability · Mathematics 2025-05-27 Robert E. Gaunt , Zixin Ye

In this paper, we investigate exact tail asymptotics for the stationary distribution of a fluid model driven by the $M/M/c$ queue, which is a two-dimensional queueing system with a discrete phase and a continuous level. We extend the kernel…

Probability · Mathematics 2018-07-10 Wendi Li , Yuanyuan Liu , Yiqiang Q. Zhao

Let (X,Y) be a bivariate elliptical random vector with associated random radius in the Gumbel max-domain of attraction. In this paper we obtain a second order asymptotic expansion of the joint survival probability P(X > x, Y> y) for x,y…

Probability · Mathematics 2008-05-15 Enkelejd Hashorva

We construct an example of a continuous centered random process with light tails of finite-dimensional distribution but with heavy tail of maximum distribution.

Probability · Mathematics 2012-08-31 E. Ostrovsky , L. Sirota

We consider the asymptotic behavior of the expectation of the maximum for a special assignment process with constant or i.i.d. coefficients. We show how it depends on the coefficients' distribution.

Probability · Mathematics 2022-05-04 Mikhail Lifshits , Arman Tadevosian