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The Robinson-Foulds (RF) distance is by far the most widely used measure of dissimilarity between trees. Although the distribution of these distances has been investigated for twenty years, an algorithm that is explicitly polynomial time…

Populations and Evolution · Quantitative Biology 2008-10-07 David Bryant , Mike Steel

Stochastic partial differential equations driven by Poisson random measures (PRM) have been proposed as models for many different physical systems, where they are viewed as a refinement of a corresponding noiseless partial differential…

Probability · Mathematics 2012-09-25 Amarjit Budhiraja , Jiang Chen , Paul Dupuis

We want to approximate general multivariate probability density functions by deterministic sample sets. For optimal sampling, the closeness to the given continuous density has to be assessed. This is a difficult challenge in multivariate…

Systems and Control · Electrical Eng. & Systems 2020-01-01 Uwe D. Hanebeck

Motivated by the fundamental problem of measuring species diversity, this paper introduces the concept of a cluster structure to define an exchangeable cluster probability function that governs the joint distribution of a random count and…

Methodology · Statistics 2014-10-14 Mingyuan Zhou , Stephen G Walker

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

Probabilistic machine learning techniques can learn both complex relations between input features and output quantities of interest as well as take into account stochasticity or uncertainty within a data set. In this initial work, we…

Nuclear Theory · Physics 2020-10-28 A. E. Lovell , A. T. Mohan , P. Talou

Compound Poisson distributions have been employed by many authors to fit experimental data, typically via the method of moments or maximum likelihood estimation. We propose a new technique and apply it to several sets of published data. It…

Methodology · Statistics 2025-04-01 S. R. Mane

We study the distribution of entries of a random permutation matrix under a "randomized basis," i.e., we conjugate the random permutation matrix by an independent random orthogonal matrix drawn from Haar measure. It is shown that under…

Probability · Mathematics 2019-05-08 Benjamin Tsou

Inherent stochasticity in gene expression leads to distributions of mRNA copy numbers in a population of identical cells. These distributions are determined primarily by the multitude of states of a gene promoter, each driving transcription…

Molecular Networks · Quantitative Biology 2020-06-16 Jaroslav Albert

We introduce Poisson-response tensor-on-tensor regression (PToTR), a novel regression framework designed to handle tensor responses composed element-wise of random Poisson-distributed counts. Tensors, or multi-dimensional arrays, composed…

Methodology · Statistics 2026-04-10 Carlos Llosa-Vite , Daniel M. Dunlavy

We analyze various data of multiplicity distributions by means of the Modified Negative Binomial Distribution (MNBD) and its KNO scaling function, since this MNBD explains the oscillating behavior of the cumulant moment observed in e^+e^-…

High Energy Physics - Phenomenology · Physics 2009-10-31 T. Osada , N. Nakajima , M. Biyajima , N. Suzuki

In this article, a Probability Mass Function (PMF) estimation method which tames the curse of dimensionality is proposed. This method, called Partial Coupled Tensor Factorization of 3D marginals or PCTF3D, has for principle to partially…

Signal Processing · Electrical Eng. & Systems 2025-09-08 Philippe Flores , Konstantin Usevich , David Brie

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

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 a random variable expressed as the Euclidean distance between an arbitrary point and a random variable uniformly distributed in a closed and bounded set of a three-dimensional Euclidean space. Four cases are considered for this…

Probability · Mathematics 2019-06-05 Vincent Guigues

The concepts of Generalized Parton Distributions (GPD) are reviewed in an introductory and phenomenological fashion. These distributions provide a rich and unifying picture of the nucleon structure. Their physical meaning is discussed. The…

High Energy Physics - Phenomenology · Physics 2009-11-07 Michel Garcon

The ensemble average of physical properties of molecules is closely related to the distribution of molecular conformations, and sampling such distributions is a fundamental challenge in physics and chemistry. Traditional methods like…

Machine Learning · Computer Science 2025-08-06 Liya Guo , Zun Wang , Chang Liu , Junzhe Li , Pipi Hu , Yi Zhu

Matrix-form Poisson probability distributions were recently introduced as one matrix generalization of Panjer distributions. We show in this paper that under the constraint that their representation is to be nonnegative, they have a…

Probability · Mathematics 2012-11-15 Sophie Hautphenne , Guy Latouche , Giang Nguyen

In many areas of applied statistics and machine learning, generating an arbitrary number of independent and identically distributed (i.i.d.) samples from a given distribution is a key task. When the distribution is known only through…

Artificial Intelligence · Computer Science 2021-10-29 Ulysse Marteau-Ferey , Francis Bach , Alessandro Rudi

In this paper, we advocate a novel measure for the purpose of checking the quality of a cluster partition for a sample into several distinct classes, and thus, determine the unknown value for the true number of clusters prevailing the…

Applications · Statistics 2024-04-12 Soumita Modak
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