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Gradients have been exploited in proposal distributions to accelerate the convergence of Markov chain Monte Carlo algorithms on discrete distributions. However, these methods require a natural differentiable extension of the target discrete…

Machine Learning · Computer Science 2023-02-28 Yue Xiang , Dongyao Zhu , Bowen Lei , Dongkuan Xu , Ruqi Zhang

We investigate a way of comparing and classifying tails of random variables. Our approach extends the notion of classical indices, such as exponential and moment indices, which are widely used measuring heaviness of tail functions. A…

Probability · Mathematics 2013-10-07 Jaakko Lehtomaa

We establish upper and lower bounds with matching leading terms for tails of weighted sums of two-sided exponential random variables. This extends Janson's recent results for one-sided exponentials.

Probability · Mathematics 2025-01-28 Jiawei Li , Tomasz Tkocz

A random variable $\xi$ has a {\it light-tailed} distribution (for short: is light-tailed) if it possesses a finite exponential moment, $\E \exp (\lambda \xi) <\infty$ for some $\lambda >0$, and has a {\it heavy-tailed} distribution (is…

Probability · Mathematics 2026-03-09 Sergey Foss , Michael Scheutzow , Anton Tarasenko

Two old conjectures from problem sections, one of which from SIAM Review, concern the question of finding distributions that maximize P(Sn <= t), where Sn is the sum of i.i.d. random variables X1, ..., Xn on the interval [0,1], satisfying…

Probability · Mathematics 2008-08-13 Ludolf E. Meester

We study the entropy $S$ of longest increasing subsequences (LIS), i.e., the logarithm of the number of distinct LIS. We consider two ensembles of sequences, namely random permutations of integers and sequences drawn i.i.d.\ from a limited…

Disordered Systems and Neural Networks · Physics 2020-06-09 Phil Krabbe , Hendrik Schawe , Alexander K. Hartmann

We investigate the behavior of the length of the longest weakly increasing subsequences (weak LIS) of $n$-step random walks with nonzero integer increments $k = \pm 1, \pm 2, \dots$ given by a zero-mean, symmetric heavy tailed mass…

Statistical Mechanics · Physics 2026-04-01 José Ricardo G. Mendonça , Marcelo V. Freire

We provide Monte Carlo estimates of the scaling of the length $L_{n}$ of the longest increasing subsequences of $n$-steps random walks for several different distributions of step lengths, short and heavy-tailed. Our simulations indicate…

Statistical Mechanics · Physics 2017-01-19 J. Ricardo G. Mendonça

We consider the sample average of a centered random walk in $\mathbb{R}^d$ with regularly varying step size distribution. For the first exit time from a compact convex set $A$ not containing the origin, we show that its tail is of lognormal…

Probability · Mathematics 2022-03-30 Ayan Bhattacharya , Zbigniew Palmowski , Bert Zwart

Using the framework of factor models, we establish the general expression of the coefficient of tail dependence between the market and a stock (i.e., the probability that the stock incurs a large loss, assuming that the market has also…

Statistical Mechanics · Physics 2008-12-10 Y. Malevergne , D. Sornette

We obtain in this paper a non-asymptotic non-improvable up to multiplicative constant moment and exponential tail estimates for distribution for U-statistics by means of martingale representation. We show also the exactness of obtained…

Statistics Theory · Mathematics 2016-02-02 E. Ostrovsky , L. Sirota

We consider a random interval splitting process, in which the splitting rule depends on the empirical distribution of interval lengths. We show that this empirical distribution converges to a limit almost surely as the number of intervals…

Probability · Mathematics 2018-06-20 Pascal Maillard , Elliot Paquette

We study branching processes of independently splitting particles in the continuous time setting. If time is calibrated such that particles live on average one unit of time, the corresponding transition rates are fully determined by the…

Probability · Mathematics 2015-12-01 Serik Sagitov

We offer in this paper the non-asymptotical bilateral sharp exponential estimates for tail of maximum distribution of {\it discontinuous} random fields. Our consideration based on the theory of Prokhorov-Skorokhod spaces of random fields…

Probability · Mathematics 2015-11-02 E. Ostrovsky , L. Sirota

We present sharp tail asymptotics for the density and the distribution function of linear combinations of correlated log-normal random variables, that is, exponentials of components of a correlated Gaussian vector. The asymptotic behavior…

Probability · Mathematics 2016-01-07 Archil Gulisashvili , Peter Tankov

In this paper, we study estimates on tail probabilities $\mathbb{P}(S_r \ge t)$ of several classes of subordinators under mild assumptions on the tail of its L\'evy measure. As an application of that result, we obtain two-sided estimates…

Probability · Mathematics 2019-05-02 Soobin Cho , Panki Kim

We derive in this article the asymptotic behavior as well as non-asymptotical estimates of tail of distribution for self-normalized sums of random variables (r.v.) under natural classical norming. We investigate also the case of…

Probability · Mathematics 2017-10-10 E. Ostrovsky , L. Sirota

The upper tail of a claim size distribution of a property line of business is frequently modelled by Pareto distribution. However, the upper tail does not need to be Pareto distributed, extraordinary shapes are possible. Here, the…

Methodology · Statistics 2020-02-19 Mathias Raschke

We obtain an uniform tail estimates for natural normed sums of independent random variables (r.v.) with regular varying tails of distributions. We give also many examples on order to show the exactness of offered estimates and discuss some…

Probability · Mathematics 2012-06-22 E. Ostrovsky , L. Sirota

In numerous instances, the generalized exponential distribution can be used as an alternative to the most widely used non-regular family of distributions: Weibull, gamma, lognormal with three-parameters when analyzing lifetime or any skewed…

Methodology · Statistics 2026-03-03 Kiran Prajapat , Sharmishtha Mitra , Debasis Kundu
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