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We derive exponential bounds for tail of distribution for natural, i.e. under ordinary logarithm, normalized sums of arrays of random variables, not necessarily independent.

In a general class of one dimensional random differential equation the convergence of the distribution function of the solution to stationary state distribution is studied. In particular it is proved the boundedness respectively the…

Probability · Mathematics 2010-07-07 Gyorgy Steinbrecher , Xavier Garbet , Boris Weyssow

We study the asymptotic behaviour of the probability that a weighted sum of centered i.i.d. random variables X_k does not exceed a constant barrier. For regular random walks, the results follow easily from classical fluctuation theory,…

Probability · Mathematics 2011-05-24 Frank Aurzada , Christoph Baumgarten

We consider random interlacements on $ \mathbb{Z}^d$, $d \ge 3$, when their vacant set is in a strongly percolative regime. Given a large box centered at the origin, we establish an asymptotic upper bound on the exponential rate of decay of…

Probability · Mathematics 2021-11-03 Alain-Sol Sznitman

We derive upper bounds on the tail conditional expectation of binomial and Poisson random variables. Those upper bounds are subsequently employed to the problem of obtaining non-asymptotic lower bounds on the probability that the…

Probability · Mathematics 2017-12-07 Christos Pelekis

The basic random $k$-SAT problem is: Given a set of $n$ Boolean variables, and $m$ clauses of size $k$ picked uniformly at random from the set of all such clauses on our variables, is the conjunction of these clauses satisfiable? Here we…

Combinatorics · Mathematics 2019-06-13 Joel Larsson , Klas Markström

The extreme value dependence of regularly varying stationary time series can be described by the spectral tail process. Drees, Segers and Warchol [Extremes 18(3): 369--402, 2015] proposed estimators of the marginal distributions of this…

Statistics Theory · Mathematics 2019-07-23 Holger Drees , Miran Knezevic

Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with…

Discrete Mathematics · Computer Science 2009-11-13 Amin Coja-Oghlan

In this paper, we establish a sufficient condition to compare linear combinations of independent and identically distributed (iid) infinite-mean random variables under usual stochastic order. We introduce a new class of distributions that…

Probability · Mathematics 2025-05-06 Yuyu Chen , Taizhong Hu , Seva Shneer , Zhenfeng Zou

It is well-known that large deviations of random walks driven by independent and identically distributed heavy-tailed random variables are governed by the so-called principle of one large jump. We note that further subtleties hold for such…

Probability · Mathematics 2017-01-30 Harald Bernhard , Bikramjit Das

A decision must often be made between heavy-tailed and Gaussian errors for a regression or a time series model, and the t-distribution is frequently used when it is assumed that the errors are heavy-tailed distributed. The performance of…

Computation · Statistics 2015-05-11 J. Martin van Zyl

This article studies the convergence rate of the sample mean for $\varphi$-mixing dependent random variables with finite means and infinite variances. Dividing the sample mean into sum of the average of the main parts and the average of the…

Probability · Mathematics 2022-09-20 F. Q. Tang , D. Han

We prove limit theorems for sums of randomly chosen random variables conditioned on the summands. We consider several versions of the corner growth setting, including specific cases of dependence amongst the summands and summands with heavy…

Probability · Mathematics 2022-07-01 David Grzybowski

This paper studies the tail probability of weighted sums of the form $\sum_{i=1}^n c_i X_i$, where random variables $X_i$'s are either independent or pairwise quasi-asymptotical independent with heavy tails. Using $h$-insensitive function,…

Probability · Mathematics 2014-04-01 Chenhua Zhang

This article considers exponential families of truncated multivariate normal distributions with one-sided truncation for some or all coordinates. We observe that if all components are one-sided truncated then this family is not full. The…

Statistics Theory · Mathematics 2025-07-02 Michael Levine , Donald Richards , Jianxi Su

Real space condensation is known to occur in stochastic models of mass transport in the regime in which the globally conserved mass density is greater than a critical value. It has been shown within models with factorised stationary states…

Statistical Mechanics · Physics 2014-11-04 Juraj Szavits-Nossan , Martin R. Evans , Satya N. Majumdar

We consider dynamical systems on a finite measure space fulfilling a spectral gap property and Birkhoff sums of a non-negative, non-integrable observable. For such systems we generalize strong laws of large numbers for intermediately…

Dynamical Systems · Mathematics 2019-09-04 Marc Kesseböhmer , Tanja Schindler

We study the long-time behavior of the probability density associated with the decoupled continuous-time random walk which is characterized by a superheavy-tailed distribution of waiting times. It is shown that if the random walk is…

Statistical Mechanics · Physics 2011-05-02 S. I. Denisov , H. Kantz

Let $A$ be a random $m\times n$ matrix over the finite field $F_q$ with precisely $k$ non-zero entries per row and let $y\in F_q^m$ be a random vector chosen independently of $A$. We identify the threshold $m/n$ up to which the linear…

Combinatorics · Mathematics 2022-07-28 Peter Ayre , Amin Coja-Oghlan , Pu Gao , Noëla Müller

Large-deviations theory deals with tails of probability distributions and the rare events of random processes, for example spreading packets of particles. Mathematically, it concerns the exponential fall-of of the density of thin-tailed…

Statistical Mechanics · Physics 2017-07-04 Erez Aghion , David A. Kessler , Eli Barkai
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