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A $d$-dimensional random array on a nonempty set $I$ is a stochastic process $\boldsymbol{X}=\langle X_s:s\in \binom{I}{d}\rangle$ indexed by the set $\binom{I}{d}$ of all $d$-element subsets of $I$. We obtain structural decompositions of…

Probability · Mathematics 2025-02-18 Pandelis Dodos , Konstantinos Tyros , Petros Valettas

The Conway-Maxwell-Poisson distribution is a two-parameter generalisation of the Poisson distribution that can be used to model data that is under- or over-dispersed relative to the Poisson distribution. The normalizing constant…

Statistics Theory · Mathematics 2019-04-05 Robert E. Gaunt , Satish Iyengar , Adri B. Olde Daalhuis , Burcin Simsek

To a higher Landau Level corresponds a generalization of the Poisson distribution arising from generalized coherent states. In this paper, we write down the atomic decomposition of this probability measure and expressed its weights through…

Probability · Mathematics 2015-02-18 Nizar Demni , Zouhair Mouayn

There is given a characterization of the geometric distribution by the independence of linear forms with random coefficients. The result is a discrete analog of the corresponding theorem on exponential distribution. The property of linear…

Probability · Mathematics 2022-10-05 Lev Klebanov

An $(n,k)$-Poisson Multinomial Distribution (PMD) is the distribution of the sum of $n$ independent random vectors supported on the set ${\cal B}_k=\{e_1,\ldots,e_k\}$ of standard basis vectors in $\mathbb{R}^k$. We prove a structural…

Data Structures and Algorithms · Computer Science 2015-11-24 Constantinos Daskalakis , Gautam Kamath , Christos Tzamos

A Poisson Binomial distribution over $n$ variables is the distribution of the sum of $n$ independent Bernoullis. We provide a sample near-optimal algorithm for testing whether a distribution $P$ supported on $\{0,...,n\}$ to which we have…

Data Structures and Algorithms · Computer Science 2014-10-15 Jayadev Acharya , Constantinos Daskalakis

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

In this paper, we introduce a new approach to generate flexible parametric families of distributions. These models arise on competitive and complementary risks scenario, in which the lifetime associated with a particular risk is not…

Applications · Statistics 2018-05-22 Pedro L. Ramos , Dipak K. Dey , Francisco Louzada , Victor H. Lachos

In this paper, an alternative mixed Poisson distribution is proposed by amalgamating Poisson distribution and a modification of the Quasi Lindley distribution. Some fundamental structural properties of the new distribution, namely the shape…

Methodology · Statistics 2021-10-26 Ramajeyam Tharshan , Pushpakanthie Wijekoon

Let $\sigma$ be a non-atomic, infinite Radon measure on $\mathbb R^d$, for example, $d\sigma(x)=z\,dx$ where $z>0$. We consider a system of freely independent particles $x_1,\dots,x_N$ in a bounded set $\Lambda\subset\mathbb R^d$, where…

Probability · Mathematics 2016-03-02 Marek Bożejko , José Luís da Silva , Tobias Kuna , Eugene Lytvynov

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

We derive some estimates for the integral modulus of continuity of probability densities of infinitely divisible distributions. The paper is splitted into two parts. The first part deals with general infinitely divisible distributions. The…

Probability · Mathematics 2018-05-07 David Berger

We consider a type of nonnormal approximation of infinitely divisible distributions that incorporates compound Poisson, Gamma, and normal distributions. The approximation relies on achieving higher orders of cumulant matching, to obtain…

Probability · Mathematics 2013-04-24 Zhiyi Chi

In this article we survey properties of mixed Poisson distributions and probabilistic aspects of the Stirling transform: given a non-negative random variable $X$ with moment sequence $(\mu_s)_{s\in\mathbb{N}}$ we determine a discrete random…

Combinatorics · Mathematics 2014-09-12 Markus Kuba , Alois Panholzer

A deterministic sequence of real numbers in the unit interval is called \emph{equidistributed} if its empirical distribution converges to the uniform distribution. Furthermore, the limit distribution of the pair correlation statistics of a…

Number Theory · Mathematics 2016-12-19 Christoph Aistleitner , Thomas Lachmann , Florian Pausinger

A theoretical framework is developed to describe the transformation that distributes probability density functions uniformly over space. In one dimension, the cumulative distribution can be used, but does not generalize to higher…

Neural and Evolutionary Computing · Computer Science 2016-09-08 Eric Kee

We prove that the classical normal distribution is infinitely divisible with respect to the free additive convolution. We study the Voiculescu transform first by giving a survey of its combinatorial implications and then analytically,…

Operator Algebras · Mathematics 2012-12-06 Serban T. Belinschi , Marek Bozejko , Franz Lehner , Roland Speicher

We consider the infinite divisibility of distributions of some well-known inverse subordinators. Using a tail probability bound, we establish that distributions of many of the inverse subordinators used in the literature are not infinitely…

Probability · Mathematics 2019-02-11 Arun Kumar , Erkan Nane

Consider the random quadratic form $T_n=\sum_{1 \leq u < v \leq n} a_{uv} X_u X_v$, where $((a_{uv}))_{1 \leq u, v \leq n}$ is a $\{0, 1\}$-valued symmetric matrix with zeros on the diagonal, and $X_1,$ $X_2, \ldots, X_n$ are i.i.d.…

Probability · Mathematics 2019-12-30 Bhaswar B. Bhattacharya , Somabha Mukherjee , Sumit Mukherjee

We derive an asymptotic expansion for the distribution of a compound sum of independent random variables, all having the same light-tailed subexponential distribution. The examples of a Poisson and geometric number of summands serve as an…

Probability · Mathematics 2007-05-23 Ph . Barbe , W. P. McCormick , C. Zhang