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We show that a slight modification of a theorem of Ruzmaikina and Aizenman on competing particle systems on the real line leads to a characterization of Poisson-Dirichlet distributions $PD(a,0)$. Precisely, let $s$ be a proper random…

Probability · Mathematics 2010-11-09 Louis-Pierre Arguin

The paper provides a simpler method for proving a delicate inequality that was used by Achlioptis and Naor to establish asymptotic concentration for chromatic numbers of Erdos-Renyi random graphs. The simplifications come from two new…

Discrete Mathematics · Computer Science 2011-07-20 John Hartigan , David Pollard , Sekhar Tatikonda

This work is concern with testing the low-dimensional parameters of interest with divergent dimensional data and variable selection for the rest under the sparse case. A consistent test via the partial penalized likelihood approach, called…

Methodology · Statistics 2014-11-20 Shanshan Wang , Hengjian Cui

Given a Poisson process on a bounded interval, its random geometric graph is the graph whose vertices are the points of the Poisson process and edges exist between two points if and only if their distance is less than a fixed given…

Probability · Mathematics 2010-08-31 Laurent Decreusefond , Eduardo Ferraz

Let $(X_1,X_2,...)$ be a random partition of the unit interval $[0,1]$, i.e. $X_i\geq0$ and $\sum_{i\geq1} X_i=1$, and let $(\varepsilon_1,\varepsilon_2,...)$ be i.i.d. Bernoulli random variables of parameter $p \in (0,1)$. The Bernoulli…

Probability · Mathematics 2020-01-14 Jakob E. Björnberg , Cécile Mailler , Peter Mörters , Daniel Ueltschi

An important functional of Poisson random measure is the negative binomial process (NBP). We use NBP to introduce a generalized Poisson-Kingman distribution and its corresponding random discrete probability measure. This random discrete…

Statistics Theory · Mathematics 2023-07-04 Sadegh Chegini , Mahmoud Zarepour

The Poisson distribution of order $k$ is a special case of a compound Poisson distribution. Its mean and variance are known, but results for its median and mode are difficult to obtain, although a few cases have been solved and upper/lower…

Probability · Mathematics 2023-09-28 S. R. Mane

We introduce the discrete distribution of a Wiener process range. Rather than finding some basic distributional properties including hazard rate function, moments, Stress-strength parameter and order statistics of this distribution, this…

Statistics Theory · Mathematics 2017-10-24 Mohamed Abd Allah El-Hadidy

Let $X$ be a random variable that takes its values in $\frac{1}{q}\mathbb{Z}$, for some integer $q\ge2$, and consider $X$ rounded to an integer, either downwards or upwards or to the nearest integer. We give general formulas for the…

Probability · Mathematics 2025-04-10 Svante Janson

We consider the Roe-Woodroofe construction of confidence intervals for the case of a Poisson distributed variate where the mean is the sum of a known background and an unknown non-negative signal. We point out that the intervals do not have…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Mark Mandelkern , Jonas Schultz

By random complex zeroes we mean the zero set of a random entire function whose Taylor coefficients are independent complex-valued Gaussian variables, and the variance of the k-th coefficient is 1/k!. This zero set is distribution invariant…

Probability · Mathematics 2016-12-21 Fedor Nazarov , Mikhail Sodin

Random models of evolution are instrumental in extracting rates of microscopic evolutionary mechanisms from empirical observations on genetic variation in genome sequences. In this context it is necessary to know the statistical properties…

Biological Physics · Physics 2009-11-07 A. Eriksson , B. Haubold , B. Mehlig

A novel over-dispersed discrete distribution, namely the PoiTG distribution is derived by the convolution of a Poisson variate and an independently distributed transmuted geometric random variable. This distribution generalizes the…

Statistics Theory · Mathematics 2024-08-02 Anupama Nandi , Subrata Chakraborty , Aniket Biswas

Let $X$ have a Generalized Poisson distribution with mean $kb$, where $b$ is a known constant in the unit interval and $k$ is a discrete, non-negative parameter. We show that if an uninformative uniform prior for $k$ is assumed, then the…

Methodology · Statistics 2016-06-07 T. F. Khang

The generalized Poisson distribution is well known to be a compound Poisson distribution with Borel summands. As a generalization we present closed formulas for compound Bartlett and Delaporte distributions with Borel summands and a…

Probability · Mathematics 2016-03-14 Helmut Finner , Peter Kern , Marsel Scheer

In this work we apply several Poisson and zero-inflated models for software defect prediction. We apply different functions from several R packages such as pscl, MASS, R2Jags and the recent glmmTMB. We test the functions using the Equinox…

Software Engineering · Computer Science 2019-10-31 Daniel Rodriguez , Javier Dolado , Javier Tuya , Dietmar Pfahl

One of the most widely used properties of the multivariate Gaussian distribution, besides its tail behavior, is the fact that conditional means are linear and that conditional variances are constant. We here show that this property is also…

Statistics Theory · Mathematics 2018-09-24 Lukas Steinberger , Hannes Leeb

We study the value distribution of diagonal forms in k variables and degree d with random real coefficients and positive integer variables, normalized so that mean spacing is one. We show that the l-correlation of almost all such forms is…

Number Theory · Mathematics 2022-11-07 Valentin Blomer , Junxian Li

We study a one-dimensional model of disordered electrons (also relevant for random spin chains), which exhibits a delocalisation transition at half-filling. Exact probability distribution functions for the Wigner time and transmission…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Steiner , Yang Chen , M. Fabrizio , Alexander O. Gogolin

Positive and negative dependence are fundamental concepts that characterize the attractive and repulsive behavior of random subsets. Although some probabilistic models are known to exhibit positive or negative dependence, it is challenging…

Machine Learning · Statistics 2025-02-11 Takahiro Kawashima , Hideitsu Hino