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The contribution of this paper is to introduce change of measure based techniques for the rare-event analysis of heavy-tailed stochastic processes. Our changes-of-measure are parameterized by a family of distributions admitting a mixture…

Probability · Mathematics 2010-06-15 Jose Blanchet , Jingchen Liu

We derive in this article the {\it lower} bound for tail of distribution for the random variables (r.v.) through a lower estimate for its moment generating functions (MGF).

Probability · Mathematics 2017-11-21 E. Ostrovsky , L. Sirota

In this paper, we give estimates of the minimal ${\mathbb{L}}^1$ distance between the distribution of the normalized partial sum and the limiting Gaussian distribution for stationary sequences satisfying projective criteria in the style of…

Probability · Mathematics 2008-08-25 Jérôme Dedecker , Emmanuel Rio

Here we suppose that the observed random variable has cumulative distribution function $F$ with regularly varying tail, i.e. $1-F \in RV_{-\alpha}$, $\alpha > 0$. Using the results about exponential order statistics we investigate…

Statistics Theory · Mathematics 2020-01-08 Pavlina K. Jordanova , Milan Stehlík

In this paper we show that the limiting distribution of the real and the imaginary part of the double Fourier transform of a stationary random field is almost surely an independent vector with Gaussian marginal distributions, whose variance…

Probability · Mathematics 2017-08-29 Magda Peligrad , Na Zhang

Standard statistical analysis is unable to provide reliable confidence intervals on expectation values of probability distributions that do not satisfy the conditions of the central limit theorem. We present a regression-based estimator of…

Data Analysis, Statistics and Probability · Physics 2019-06-24 Pablo Lopez Rios , Gareth J. Conduit

This paper describes the construction of a lower bound for the tails of general random variables, using solely knowledge of their moment generating function. The tilting procedure used allows for the construction of lower bounds that are…

Probability · Mathematics 2007-06-13 Ted Theodosopoulos

The approach of Kleitman (1970) and Kanter (1976) to multivariate concentration function inequalities is generalized in order to obtain for deviation probabilities of sums of independent symmetric random variables a lower bound depending…

Probability · Mathematics 2007-05-23 Lutz Mattner

The (general) hypoexponential distribution is the distribution of a sum of independent exponential random variables. We consider the particular case when the involved exponential variables have distinct rate parameters. We prove that the…

Probability · Mathematics 2020-12-16 George P. Yanev

We study the tails of the density of states of fermions subject to a random magnetic field with non-zero mean with the Optimum Fluctuation Method (OFM). Closer to the centres of the Landau levels, the density of states is found to be…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Riccardo Mazzarello , Stefan Kettemann , Bernhard Kramer

The study of loss function distributions is critical to characterize a model's behaviour on a given machine learning problem. For example, while the quality of a model is commonly determined by the average loss assessed on a testing set,…

Machine Learning · Computer Science 2023-06-06 Etrit Haxholli , Marco Lorenzi

We study the influence of the multipliers $\xi (n)$ on the angular distribution of zeroes of the Taylor series \[ F_\xi (z) = \sum_{n\ge 0} \xi (n) \frac{z^n}{n!}\,. \] We show that the distribution of zeroes of $ F_\xi $ is governed by…

Probability · Mathematics 2016-01-11 Alexander Borichev , Alon Nishry , Mikhail Sodin

This paper proves several weak limit theorems for the joint version of extreme order statistics and partial sums of independently and identically distributed random variables. The results are also extended to almost sure limit version.

Probability · Mathematics 2023-12-18 Gaoyu Li , Zhongquan Tan

In many areas of interest, modern risk assessment requires estimation of the extremal behaviour of sums of random variables. We derive the first order upper-tail behaviour of the weighted sum of bivariate random variables under weak…

Statistics Theory · Mathematics 2022-08-17 Jordan Richards , Jonathan A. Tawn

We consider moderately trimmed sums of non-negative i.i.d. random variables. We show that for every distribution function there exists a proper moderate trimming such that for the trimmed sum a non-trivial strong law of large numbers holds.…

Probability · Mathematics 2019-05-23 Marc Kesseböhmer , Tanja Schindler

We study the behavior of the tail probabilities $P(V^2<r)$ as $r\to 0$, where $V^2$ is defined by the following double sum $$ V^2 =\pi^{-4}\,\sum\limits_{i,j\ge 1} \Big((i+b)\,(j + \delta)\Big)^{-2}\,\xi_{ij}^2,$$ where $ \{\xi_{ij}\} $ are…

Probability · Mathematics 2017-05-16 L. Rozovsky

This paper studies the limits of a spatial random field generated by uniformly scattered random sets, as the density $\lambda$ of the sets grows to infinity and the mean volume $\rho$ of the sets tends to zero. Assuming that the volume…

Probability · Mathematics 2011-11-10 Ingemar Kaj , Lasse Leskelä , Ilkka Norros , Volker Schmidt

Let $\{S_n=(X_n,W_n)\}_{n\ge0}$ be a random walk with $X_n\in \mathbb{R}$ and $W_n\in \mathbb{R}^m$. Let $\tau=\tau_a=\inf\{n:X_n>a\}$. The main results presented are two term asymptotic expansions for the joint distribution of $S_{\tau}$…

Statistics Theory · Mathematics 2007-06-13 Robert Keener

The sum of Log-normal variates is encountered in many challenging applications such as in performance analysis of wireless communication systems and in financial engineering. Several approximation methods have been developed in the…

Statistics Theory · Mathematics 2017-05-29 Mohamed-Slim Alouini , Nadhir Ben Rached , Abla Kammoun , Raul Tempone

We establish the one-to one bilateral interrelations between an asymptotic behavior for the tail of distributions for random variables and its great moments evaluation. Our results generalize the famous Richter's ones.

Probability · Mathematics 2022-06-02 M. R. Formica , E. Ostrovsky , L. Sirota
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