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The size that an epidemic can reach, measured in terms of the number of fatalities, is an extremely relevant quantity. It has been recently claimed [Cirillo & Taleb, Nature Physics 2020] that the size distribution of major epidemics in…

Physics and Society · Physics 2021-03-18 Alvaro Corral

The q-Gaussians are a class of stable distributions which are present in many scientific fields, and that behave as heavy tailed distributions for an especific range of q values. The identification of these values, which are used in the…

Data Analysis, Statistics and Probability · Physics 2015-06-11 E. L de Santa Helena , C. M. Nascimento , G. J. L. Gerhardt

We consider a family of multivariate distributions with heavy-tailed margins and the type I elliptical dependence structure. This class of risks is common in finance, insurance, environmental and biostatistic applications. We obtain the…

Statistics Theory · Mathematics 2024-05-01 Kai Wang , Chengxiu Ling

Let $X$ and $Y$ be two independent random variables with corresponding distributions $F$ and $G$ supported on $[0,\infty)$. The distribution of the product $XY$, which is called the product convolution of $F$ and $G$, is denoted by $H$. In…

Probability · Mathematics 2019-01-08 Zhaolei Cui , Guancheng Jiang , Yuebao Wang

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

Stretched exponential probability density functions (pdf), having the form of the exponential of minus a fractional power of the argument, are commonly found in turbulence and other areas. They can arise because of an underlying random…

Statistical Mechanics · Physics 2009-10-30 U. Frisch , D. Sornette

Directed last passage percolation models on the plane, where one studies the weight as well as the geometry of optimizing paths (called polymers) in a field of i.i.d. weights, are paradigm examples of models in the KPZ universality class.…

Probability · Mathematics 2017-11-01 Riddhipratim Basu , Shirshendu Ganguly , Allan Sly

We propose an analytical approach to the computation of tail probabilities of compound distributions whose individual components have heavy tails. Our approach is based on the contour integration method, and gives rise to a representation…

Computational Finance · Quantitative Finance 2017-10-04 Igor Halperin

Consider first passage percolation with identical and independent weight distributions and first passage time ${\rm T}$. In this paper, we study the upper tail large deviations $\mathbb{P}({\rm T}(0,nx)>n(\mu+\xi))$, for $\xi>0$ and $x\neq…

Probability · Mathematics 2023-02-02 Clément Cosco , Shuta Nakajima

The so-called partition function is a sample moment statistic based on blocks of data and it is often used in the context of multifractal processes. It will be shown that its behaviour is strongly influenced by the tail of the distribution…

Methodology · Statistics 2013-10-02 Danijel Grahovac , Mofei Jia , Nikolai N. Leonenko , Emanuele Taufer

We establish sharp large deviation asymptotics for the maximum order statistic of independent and identically distributed heavy-tailed random variables, valid for all Borel subsets of the right tail. This result yields exact decay rates for…

Probability · Mathematics 2026-01-09 José M. Zapata

It is well known that the distribution of returns from various financial instruments are leptokurtic, meaning that the distributions have "fatter tails" than a Normal distribution, and have skew toward zero. This paper presents a graceful…

Trading and Market Microstructure · Quantitative Finance 2013-04-03 Ben Klemens

We conjecture an explicit expression for the lower tail large deviation rate function of the partition function of the log-Gamma polymer. We rigorously prove our result, except for one step for which we only provide heuristic evidence. We…

Mathematical Physics · Physics 2024-10-25 Tom Claeys , Julian Mauersberger

We establish some asymptotic expansions for infinite weighted convolution of distributions having regular varying tails. Various applications to statistics and probability are developed.

Probability · Mathematics 2007-06-13 Ph. Barbe , W. P. McCormick

We consider a model for chaotic diffusion with amplification on graphs associated with piecewise-linear maps of the interval [S. Lepri, Chaos Solitons & Fractals, 139,110003 (2020)]. We determine the conditions for having fat-tailed…

Chaotic Dynamics · Physics 2024-01-19 Stefano Lepri

Existing theory for multivariate extreme values focuses upon characterizations of the distributional tails when all components of a random vector, standardized to identical margins, grow at the same rate. In this paper, we consider the…

Statistics Theory · Mathematics 2013-12-20 J. L. Wadsworth , J. A. Tawn

We prove large deviation principles for two versions of fractional Poisson processes. Firstly we consider the main version which is a renewal process; we also present large deviation estimates for the ruin probabilities of an insurance…

Probability · Mathematics 2016-11-26 Luisa Beghin , Claudio Macci

A large deviation function mathematically characterizes the statistical property of atypical events. Recently, in non-equilibrium statistical mechanics, large deviation functions have been used to describe universal laws such as the…

Statistical Mechanics · Physics 2012-04-26 Shin-ichi Sasa

In this paper we consider the first passage percolation with identical and independent exponentially distributions, called the Eden growth model, and we study the upper tail large deviations for the first passage time ${\rm T}$. Our main…

Probability · Mathematics 2020-01-01 Shuta Nakajima

Variational inference with {\alpha}-divergences has been widely used in modern probabilistic machine learning. Compared to Kullback-Leibler (KL) divergence, a major advantage of using {\alpha}-divergences (with positive {\alpha} values) is…

Machine Learning · Computer Science 2019-09-10 Dilin Wang , Hao Liu , Qiang Liu