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The Poisson distribution is the default choice of likelihood for probabilistic models of count data. However, due to the equidispersion contraint of the Poisson, such models may have predictive uncertainty that is artificially inflated.…

Methodology · Statistics 2025-07-15 Jimmy Lederman , Aaron Schein

A validated simulation model primarily requires performing an appropriate input analysis mainly by determining the behavior of real-world processes using probability distributions. In many practical cases, probability distributions of the…

Applications · Statistics 2014-03-05 Issac Shams , Saeede Ajorlou , Kai Yang

The Poisson distribution is the probability distribution of the number of independent events in a given period of time. Although the Poisson distribution appears ubiquitously in various stochastic dynamics of gene expression, both as…

Statistical Mechanics · Physics 2024-10-02 Julian Lee

We introduce a new class of nonparametric prior distributions on the space of continuously varying densities, induced by Dirichlet process mixtures which diffuse in time. These select time-indexed random functions without jumps, whose…

Methodology · Statistics 2016-02-10 Ramsés H. Mena , Matteo Ruggiero

In [Schuhmacher, Electron. J. Probab. 10 (2005), 165--201] estimates of the Barbour-Brown distance d_2 between the distribution of a thinned point process and the distribution of a Poisson process were derived by combining discretization…

Probability · Mathematics 2007-05-23 Dominic Schuhmacher

Pitman~(1999) describes a duality relationship between fragmentation and coagulation operators. An explicit relationship is described for the two-parameter Poisson-Dirichlet laws, with parameters {\footnotesize $(\alpha,\theta)$} and…

Probability · Mathematics 2007-05-23 Man-Wai Ho , Lancelot F. James , John W. Lau

In this article, we study a model of random permutations, which we call random standardized permutations, based on a sequence of i.i.d. random variables. This model generalizes others, such as the riffle-shuffle and the major-index-biased…

Probability · Mathematics 2026-03-26 Aurélien Guerder

The Ewens-Pitman sampling model (EP-SM) is a distribution for random partitions of the set $\{1,\ldots,n\}$, with $n\in\mathbb{N}$, which is index by real parameters $\alpha$ and $\theta$ such that either $\alpha\in[0,1)$ and…

Probability · Mathematics 2021-11-05 Emanuele Dolera , Stefano Favaro

We suggest a new hardcore Poisson-type distribution for Young diagrams with the row lengths from some finite list. A discrete variant of the time-ordered Mat\'{e}rn II process in 1D is employed. This approach is related to that based on the…

Combinatorics · Mathematics 2022-06-17 Ivan Cherednik

This paper explores large sample properties of the two-parameter $(\alpha,\theta)$ Poisson--Dirichlet Process in two contexts. In a Bayesian context of estimating an unknown probability measure, viewing this process as a natural extension…

Probability · Mathematics 2008-05-21 Lancelot F. James

Barrier crossing is a widespread phenomenon across natural and engineering systems. While an abundant cross-disciplinary literature on the topic has emerged over the years, the stochastic underpinnings of the process are yet to be linked…

Statistical Mechanics · Physics 2024-12-19 Toby Kay , Luca Giuggioli

Species sampling processes have long served as the fundamental framework for modeling random discrete distributions and exchangeable sequences. However, data arising from distinct but related sources require a broader notion of…

Statistics Theory · Mathematics 2026-02-03 Beatrice Franzolini , Antonio Lijoi , Igor Prünster , Giovanni Rebaudo

We introduce the Pitman Yor Diffusion Tree (PYDT) for hierarchical clustering, a generalization of the Dirichlet Diffusion Tree (Neal, 2001) which removes the restriction to binary branching structure. The generative process is described…

Machine Learning · Statistics 2011-06-17 David A. Knowles , Zoubin Ghahramani

A common assumption when modeling queuing systems is that arrivals behave like a Poisson process with constant parameter. In practice, however, call arrivals are often observed to be significantly overdispersed. This motivates that in this…

Probability · Mathematics 2017-03-07 Mariska Heemskerk , Julia Kuhn , Michel Mandjes

In this paper, a new mixed Poisson distribution is introduced. This new distribution is obtained by utilizing mixing process, with Poisson distribution as mixed distribution and Transmuted Exponential distribution as mixing distribution.…

Methodology · Statistics 2016-10-05 Deepesh Bhati , Pooja Kumawat , E. Gómez Déniz

We consider the distribution of the binomial probability mass function (pmf) among arithmetic progressions and obtain an average-type theorem. As applications, we consider the possible visits to a kind of sieved sets of integers or lattice…

Number Theory · Mathematics 2023-07-07 Jun Hong , Xiaosheng Wu , Shixin Zhu

We derive the class of normalized generalized Gamma processes from Poisson-Kingman models (Pitman, 2003) with tempered alfa-stable mixing distribution. Relying on this construction it can be shown that in Bayesian nonparametrics, results on…

Probability · Mathematics 2007-11-14 Annalisa Cerquetti

Consider a stationary renewal point process on the real line and divide each of the segments it defines in a proportion given by \iid realisations of a fixed distribution $G$ supported by [0,1]. We ask ourselves for which interpoint…

Probability · Mathematics 2014-08-12 Anton Muratov , Sergei Zuyev

A simple explicit construction is provided of a partition-valued fragmentation process whose distribution on partitions of $[n]=\{1,...,n\}$ at time $\theta \ge 0$ is governed by the Ewens sampling formula with parameter $\theta$. These…

Probability · Mathematics 2007-05-23 Alexander Gnedin , Jim Pitman

Hidden Markov models are versatile tools for modeling sequential observations, where it is assumed that a hidden state process selects which of finitely many distributions generates any given observation. Specifically for time series of…

Methodology · Statistics 2019-01-11 Timo Adam , Roland Langrock , Christian H. Weiß