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We study extremal statistics and return intervals in stationary long-range correlated sequences for which the underlying probability density function is bounded and uniform. The extremal statistics we consider e.g., maximum relative to…

Statistical Mechanics · Physics 2015-05-13 N. R. Moloney , J. Davidsen

We prove that the tail probabilities of sums of independent uniform random variables, up to a multiplicative constant, are dominated by the Gaussian tail with matching variance and find the sharp constant for such stochastic domination.

Probability · Mathematics 2026-03-05 Xinjie He , Tomasz Tkocz , Katarzyna Wyczesany

We study in this article large deviations for the empirical mean of iid random vectors with some deterministic weights, whose empirical measure weakly converges to some compactly support probability distribution. The scope of this paper is…

Probability · Mathematics 2016-08-16 Mylène Maïda , Jamal Najim , Sandrine Péché

This work prepares new probability bounds for sums of random, independent, Hermitian tensors. These probability bounds characterize large-deviation behavior of the extreme eigenvalue of the sums of random tensors. We extend Lapalace…

Probability · Mathematics 2021-01-01 Shih Yu Chang

We construct a new tail bound for the sum of independent random variables for situations in which the expected value of the sum is known and each random variable lies within a specified interval, which may be different for each variable.…

Probability · Mathematics 2025-03-25 Jackson Loper , Jeffrey Regier

We consider the problem of bounding large deviations for non-i.i.d. random variables that are allowed to have arbitrary dependencies. Previous works typically assumed a specific dependence structure, namely the existence of independent…

Probability · Mathematics 2018-11-06 Christoph H. Lampert , Liva Ralaivola , Alexander Zimin

Asymptotics deviation probabilities of the sum S n = X 1 + $\times$ $\times$ $\times$ + X n of independent and identically distributed real-valued random variables have been extensively investigated, in particular when X 1 is not…

Probability · Mathematics 2021-01-21 Fabien Brosset , Thierry Klein , Agnès Lagnoux , Pierre Petit

We establish some asymptotic expansions for infinite weighted convolutions of distributions having light subexponential tails. Examples are presented, some showing that in order to obtain an expansion with two significant terms, one needs…

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

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 provide a generalisation of Pinelis' Rademacher-Gaussian tail comparison to complex coefficients. We also establish uniform bounds on the probability that the magnitude of weighted sums of independent random vectors uniform on Euclidean…

Probability · Mathematics 2022-03-15 Giorgos Chasapis , Ruoyuan Liu , Tomasz Tkocz

We study the full distribution $P_{N}\left(A\right)$ of sums $A = \sum_{i=1}^N$ where $x_1, \dots, x_N$ are $N \gg 1$ independent and identically distributed random variables each sampled from a given distribution $p(x)$ with a…

Statistical Mechanics · Physics 2025-07-09 Naftali R. Smith

Rare events play a crucial role in understanding complex systems. Characterizing and analyzing them in scale-invariant situations is challenging due to strong correlations. In this work, we focus on characterizing the tails of probability…

Statistical Mechanics · Physics 2025-04-03 Ivan Balog , Bertrand Delamotte , Adam Rançon

We study the random variables (r.v.) with values in the so-called mixed (anisotropic) Lebesgue-Riesz spaces: formulate the sufficient conditions for belonging of the r.v. to these spaces, estimate the tail of norms distribution, especially…

Probability · Mathematics 2021-10-08 M. R. Formica , E. Ostrovsky , L. Sirota

We use bias-reduced estimators of high quantiles, of heavy-tailed distributions, to introduce a new estimator of the mean in the case of infinite second moment. The asymptotic normality of the proposed estimator is established and checked,…

Methodology · Statistics 2014-05-09 Brahim Brahimi , Djamel Meraghni , Abdelhakim Necir , Djabrane Yahia

The theory of large deviations is concerned with the exponential decay of probabilities of large fluctuations in random systems. These probabilities are important in many fields of study, including statistics, finance, and engineering, as…

Statistical Mechanics · Physics 2009-08-20 Hugo Touchette

We consider a class of stationary processes exhibiting both long-range dependence and heavy tails. Separate limit theorems for sums and for extremes have been established recently in literature with novel objects appearing in the limits. In…

Probability · Mathematics 2023-09-12 Shuyang Bai , He Tang

A well-known longstanding conjecture on the supremum of the tails of normalized sums of independent Rademacher random variables is disproved. A related conjecture, also recently disproved, is discussed.

Probability · Mathematics 2017-01-17 Iosif Pinelis

This is a thesis on some applications of regularly varying functions. Three problems are considered. The first problem is about the randomly weighted sums, the second is on the behavior of the product under conditional extreme value model…

Probability · Mathematics 2011-09-28 Rajat Subhra Hazra

In this note a two sided bound on the tail probability of sums of independent, and either symmetric or nonnegative, random variables is obtained. We utilize a recent result by Lata{\l}a on bounds on moments of such sums. We also give a new…

Probability · Mathematics 2007-05-23 Paweł Hitczenko , Stephen Montgomery-Smith

In 2017-2020 Jordanova and co-authors investigate probabilities for p-outside values and determine them in many particular cases. They show that these probabilities are closely related to the concept for heavy tails. Tukey's boxplots are…

Methodology · Statistics 2024-10-22 Pavlina K. Jordanova