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We study the asymptotic behavior of the marginal expected shortfall when the two random variables are asymptotic independent but positive associated, which is modeled by the so-called tail dependent coefficient. We construct an estimator of…

Statistics Theory · Mathematics 2017-09-14 Juan-Juan Cai , Eni Musta

Count data are omnipresent in many applied fields, often with overdispersion. With mixtures of Poisson distributions representing an elegant and appealing modelling strategy, we focus here on how the tail behaviour of the mixing…

Statistics Theory · Mathematics 2023-05-29 Samuel Valiquette , Gwladys Toulemonde , Jean Peyhardi , Éric Marchand , Frédéric Mortier

This paper studies the joint tail asymptotics of extrema of the multi-dimensional Gaussian process over random intervals defined as $$ P(u):=\mathbb{P}\left\{\cap_{i=1}^n \left(\sup_{t\in[0,\mathcal{T}_i]} ( X_{i}(t) +c_i t )>a_i u…

Probability · Mathematics 2020-09-28 Lanpeng Ji , Xiaofan Peng

We establish new tail estimates for order statistics and for the Euclidean norms of projections of an isotropic log-concave random vector. More generally, we prove tail estimates for the norms of projections of sums of independent…

Generalized Maxwell distribution is an extension of the classic Maxwell distribution. In this paper, we concentrate on the joint distributional asymptotics of normalized maxima and minima. Under optimal normalizing constants, asymptotic…

Probability · Mathematics 2020-03-10 Jianwen Huang

Despite the successes of probabilistic models based on passing noise through neural networks, recent work has identified that such methods often fail to capture tail behavior accurately, unless the tails of the base distribution are…

Machine Learning · Statistics 2023-06-16 Feynman Liang , Liam Hodgkinson , Michael W. Mahoney

We study the empirical version of halfspace depths with the objective of establishing a connection between the rates of convergence and the tail behaviour of the corresponding underlying distributions. The intricate interplay between the…

Statistics Theory · Mathematics 2025-06-03 Sibsankar Singha , Marie Kratz , Sreekar Vadlamani

q-Gaussian distribution appear in many science areas where we can find systems that could be described within a nonextensive framework. Usually, a way to assert that these systems belongs to nonextensive framework is by means of numerical…

Data Analysis, Statistics and Probability · Physics 2017-03-21 Wagner S. de Lima , Emerson L. de Santa Helena

We investigate what happens when an entire sample path of a smooth Gaussian process on a compact interval lies above a high level. Specifically, we determine the precise asymptotic probability of such an event, the extent to which the high…

Probability · Mathematics 2017-09-14 Arijit Chakrabarty , Gennady Samorodnitsky

At high levels, the asymptotic distribution of a stationary, regularly varying Markov chain is conveniently given by its tail process. The latter takes the form of a geometric random walk, the increment distribution depending on the sign of…

Methodology · Statistics 2014-12-11 Holger Drees , Johan Segers , Michał Warchoł

We investigate the tail behaviour of the steady state distribution of a stochastic recursion that generalises Lindley's recursion. This recursion arises in queuing systems with dependent interarrival and service times, and includes…

Probability · Mathematics 2014-04-23 Maria Vlasiou , Zbigniew Palmowski

We generalize Quasi-Linear Means by restricting to the tail of the risk distribution and show that this can be a useful quantity in risk management since it comprises in its general form the Value at Risk, the Tail Value at Risk and the…

Risk Management · Quantitative Finance 2025-10-22 Nicole Bäuerle , Tomer Shushi

Exploratory data analysis is often used to test the goodness-of-fit of sample observations to specific target distributions. A few such graphical tools have been extensively used to detect subexponential or heavy-tailed behavior in observed…

Statistics Theory · Mathematics 2013-02-04 Bikramjit Das , Souvik Ghosh

In this article we study the tail probability of the mass of critical Gaussian multiplicative chaos (GMC) associated to a general class of log-correlated Gaussian fields in any dimension, including the Gaussian free field (GFF) in dimension…

Probability · Mathematics 2019-12-06 Mo Dick Wong

This paper is a short overview of the main Abelian- and Tauberian-type results from [4, 14, 26] regarding the asymptotic analysis of different classes of generalized functions in terms of appropriate frames. The Tauberian-type results…

Functional Analysis · Mathematics 2024-04-09 Jasmina Veta Buralieva , Diana T. Stoeva , Katerina Hadzi-Velkova Saneva , Sanja Atanasova

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 estimate up to universal constants tails of symmetric and totally asymmetric 1-dimensional $\alpha$-stable distributions in terms of functions of the parameters of these distributions. In particular, for values of $\alpha$ close to $2$…

Probability · Mathematics 2020-11-30 Witold M. Bednorz , Rafał M. Łochowski , Rafał Martynek

The right tail asymptotic series consisting of attenuating exponential terms are derived for the densities of Galton-Watson processes with fractional probability generating functions. The frequencies in the exponential factors form fractal…

Probability · Mathematics 2025-02-13 Anton A. Kutsenko

The Tsallis $q$-Gaussian distribution is a powerful generalization of the standard Gaussian distribution and is commonly used in various fields, including non-extensive statistical mechanics, financial markets and image processing. It…

Computation · Statistics 2023-05-19 Viktor Witkovský

The term moderate deviations is often used in the literature to mean a class of large deviation principles that, in some sense, fills the gap between a convergence in probability of some random variables to a constant and a weak convergence…

Probability · Mathematics 2024-11-20 Rita Giuliano , Claudio Macci , Barbara Pacchiarotti
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