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Related papers: Infinite Divisibility and Max-Infinite Divisibilit…

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Continuing the study reported in Satheesh (2001),(arXiv:math.PR/0304499 dated 01May2003) here we study certain aspects of randomization in infinitely divisible (ID) and max-infinitely divisible (MID) laws. They generalize ID and MID laws.…

Probability · Mathematics 2007-06-13 S. Satheesh

In this paper, we study the risk bounds for samples independently drawn from an infinitely divisible (ID) distribution. In particular, based on a martingale method, we develop two deviation inequalities for a sequence of random variables of…

Machine Learning · Statistics 2012-02-20 Chao Zhang , Dacheng Tao

The notion of geometric version of an infinitely divisible law is introduced. Concepts parallel to attraction and partial attraction are developed and studied in the setup of geometric summing of random variables.

Probability · Mathematics 2014-09-16 E. Sandhya , R. N. Pillai

The drawbacks in the formulations of random infinite divisibility in Sandhya (1991, 1996), Gnedenko and Korelev (1996), Klebanov and Rachev (1996), Bunge (1996) and Kozubowski and Panorska (1996) are pointed out. For any given Laplace…

Probability · Mathematics 2007-06-13 S. Satheesh

Here we give a necessary and sufficient condition for the convergence to a random max infinitely divisible law from that of a random maximum. We then discuss random max-stable laws, their domain of max-attraction and the associated extremal…

Probability · Mathematics 2014-05-20 S. Satheesh , E. Sandhya

The phenomenon of superconvergence is proved for all freely infinitely divisible distributions. Precisely, suppose that the partial sums of a sequence of free identically distributed, infinitesimal random variables converge in distribution…

Probability · Mathematics 2018-03-16 Hari Bercovici , Jiun-Chau Wang , Ping Zhong

In probability theory and statistics, the IID model represents a single population, and a large, potentially infinite sample from this population. Main theorems, in particular the central limit theorem and laws of large number (LLN) assure…

Statistics Theory · Mathematics 2017-10-02 Uwe Saint-Mont

Consider multiple sums $S_n$ on the $d$-dimensional integer grid,which are generated by i.i.d.\ random variables with a positive expectation. We prove the strong law of large numbers, the law of the iterated logarithm and the distributional…

Probability · Mathematics 2017-09-05 Andrii Ilienko , Ilya Molchanov

The law of large numbers for the empirical density for the pairs of uniformly distributed integers with a given greatest common divisor is a classic result in number theory. In this paper, we study the large deviations of the empirical…

Probability · Mathematics 2016-10-07 Behzad Mehrdad , Lingjiong Zhu

We study two types of probability measures on the set of integer partitions of $n$ with at most $m$ parts. The first one chooses the random partition with a chance related to its largest part only. We then obtain the limiting distributions…

Probability · Mathematics 2023-01-03 Tiefeng Jiang , Ke Wang

We present a generalization of the maximal inequalities that upper bound the expectation of the maximum of $n$ jointly distributed random variables. We control the expectation of a randomly selected random variable from $n$ jointly…

Probability · Mathematics 2017-08-31 Jiantao Jiao , Yanjun Han , Tsachy Weissman

We survey known solutions to the infinite extendibility problem for (necessarily exchangeable) probability laws on $\mathbb{R}^d$, which is: Can a given random vector $\vec{X} = (X_1,\ldots,X_d)$ be represented in distribution as the first…

Probability · Mathematics 2020-11-06 Jan-Frederik Mai

In this article we introduce associative Look-Up Tables. With their help, pseudo sums are correctly determined. The set of limit distributions in a pseudo-summation scheme of i.i.d. random variables is described. Also, two special cases…

Probability · Mathematics 2023-06-02 Ivan Alexeev , Ignat Melnikov , Artem Uglovski

This note examines the infinite divisibility of density-based transformations of normal random variables. We characterize a class of density-based transformations of normal variables which produces non-infinitely divisible distributions. We…

Statistics Theory · Mathematics 2011-08-03 A. Murillo-Salas , F. J. Rubio

Max stable laws are limit laws of linearly normalized partial maxima of indepen- dent, identically distributed (iid) random variables (rvs). These are analogous to stable laws which are limit laws of normalized partial sums of iid rvs. In…

Statistics Theory · Mathematics 2016-11-25 Sreenivasan Ravi , Ali Saeb

Laws of large numbers establish asymptotic guarantees for recovering features of a probability distribution using independent samples. We introduce a framework for proving analogous results for recovery of the $\sigma$-field of a…

Probability · Mathematics 2025-05-14 Daniel Raban

In this paper we develop tools for studying limit theorems by means of convexity. We establish bounds for the discrepancy in total variation between probability measures $\mu$ and $\nu$ such that $\nu$ is log-concave with respect to $\mu$.…

Probability · Mathematics 2022-10-24 Arturo Jaramillo , James Melbourne

Quasi-infinitely divisible (QID) distributions have been recently introduced by Lindner, Pan and Sato (\textit{Trans.~Amer.~Math.~Soc.}~\textbf{370}, 8483-8520 (2018)). A random variable $X$ is QID if and only if there exist two infinitely…

Probability · Mathematics 2020-09-23 Riccardo Passeggeri

In applied probability, the normal approximation is often used for the distribution of data with assumed additive structure. This tradition is based on the central limit theorem for sums of (independent) random variables. However, it is…

Probability · Mathematics 2020-10-27 Alexandra Dorofeeva , Victor Korolev , Alexander Zeifman

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
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