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The probability that the sum of independent, centered, identically distributed, heavy-tailed random variables achieves a very large value is asymptotically equal to the probability that there exists a single summand equalling that value. We…

Probability · Mathematics 2024-02-15 Quirin Vogel

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 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 give a comparison inequality that allows one to estimate the tail probabilities of sums of independent Banach space valued random variables in terms of those of independent identically distributed random variables. More precisely, let…

Probability · Mathematics 2007-05-23 Stephen Montgomery-Smith , Alexander R. Pruss

The exact expression for the probability density $p_{_N}(x)$ for sums of a finite number $N$ of random independent terms is obtained. It is shown that the very tail of $p_{_N}(x)$ has a Gaussian form if and only if all the random terms are…

Probability · Mathematics 2013-05-29 Michael I. Tribelsky

We derive the tail inequalities between two random variables starting from inequalities between its moment, or more generally between its Lebesgue-Riesz norms, which holds true on certain sets of parameters. We consider some applications…

Probability · Mathematics 2022-06-06 M. R. Formica , E. Ostrovsky , L. Sirota

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 this paper, we present a new framework to obtain tail inequalities for sums of random matrices. Compared with existing works, our tail inequalities have the following characteristics: 1) high feasibility--they can be used to study the…

Machine Learning · Computer Science 2019-10-10 Chao Zhang , Min-Hsiu Hsieh , Dacheng Tao

The extremal tail probabilities of moving sums in a marked Poisson random field is examined here. These sums are computed by adding up the weighted occurrences of events lying within a scanning set of fixed shape and size. Change of measure…

Probability · Mathematics 2007-08-22 Hock Peng Chan

The tail of the distribution of a sum of a random number of independent and identically distributed nonnegative random variables depends on the tails of the number of terms and of the terms themselves. This situation is of interest in the…

Probability · Mathematics 2008-12-10 Christian Y. Robert , Johan Segers

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

We give explicit bounds for the tail probabilities for sums of independent geometric or exponential variables, possibly with different parameters.

Probability · Mathematics 2017-09-26 Svante Janson

We study randomly stopped sums via their asymptotic scales. First, finiteness of moments is considered. To generalise this study, asymptotic scales applicable to the class of all heavy-tailed random variables are used. The stopping is…

Probability · Mathematics 2014-05-12 Jaakko Lehtomaa

We revisit the problem of condensation for independent, identically distributed random variables with a power-law tail, conditioned by the value of their sum. For large values of the sum, and for a large number of summands, a condensation…

Statistical Mechanics · Physics 2022-03-03 Claude Godrèche

A popular measure of association is the tail dependence coefficient which measures the strength of dependence in either the lower-left or upper-right tail of a bivariate distribution. In this paper, we develop the idea of quantile…

Statistics Theory · Mathematics 2024-02-09 A. Dastbaravarde , A. Dolati

We say that a random integer variable $X$ is monotone if the modulus of the characteristic function of $X$ is decreasing on $[0,\pi]$. This is the case for many commonly encountered variables, e.g., Bernoulli, Poisson and geometric random…

Probability · Mathematics 2021-04-14 Anders Aamand , Noga Alon , Jakob Bæk Tejs Knudsen , Mikkel Thorup

We suggest approximating the distribution of the sum of independent and identically distributed random variables with a Pareto-like tail by combining extreme value approximations for the largest summands with a normal approximation for the…

Probability · Mathematics 2018-02-05 Ulrich K. Mueller

In this article the relation between the tail behaviours of a free regular infinitely divisible (positively supported) probability measure and its L\'evy measure is studied. An important example of such a measure is the compound free…

Probability · Mathematics 2018-10-05 Arijit Chakrabarty , Sukrit Chakraborty , Rajat Subhra Hazra

We present an analytic method for computing the moments of a sum of independent and identically distributed random variables. The limiting behavior of these sums is very important to statistical theory, and the moment expressions that we…

Statistics Theory · Mathematics 2012-01-17 Daniel M. Packwood

We consider a new approach in the definition of two-dimensional heavy-tailed distributions. Namely, we introduce the classes of two-dimensional long-tailed, of twodimensional dominatedly varying and of two-dimensional consistently varying…

Probability · Mathematics 2025-06-25 Dimitrios G. Konstantinides , Charalampos D. Passalidis
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