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We study interacting particle systems on the real line which generalize the Hammersley process [D. Aldous and P. Diaconis, Prob. Theory Relat. Fields 103, 199-213 (1995)]. Particles jump to the right to a randomly chosen point between their…

Statistical Mechanics · Physics 2011-05-20 J. Krug , J. Garcia

Consider a list of labeled objects that are organized in a heap. At each time, object $j$ is selected with probability $p_j$ and moved to the top of the heap. This procedure defines a Markov chain on the set of permutations which is…

Methodology · Statistics 2018-01-26 Alfred Kume , Fabrizio Leisen , Antonio Lijoi

An invariant ensemble of $N\times N$ random matrices can be characterised by a joint distribution for eigenvalues $P(\lambda_1,\cdots,\lambda_N)$. The study of the distribution of linear statistics, i.e. of quantities of the form…

Statistical Mechanics · Physics 2017-09-25 Aurélien Grabsch , Christophe Texier

We establish the general equivalence between rare event process for arbitrary continuous functions whose maximal values are achieved on non-trivial sets, and the entry times distribution for arbitrary measure zero sets. We then use it to…

Dynamical Systems · Mathematics 2019-05-27 Fan Yang

In this work, we continue the line of research on the complexity of distributions (Viola, Journal of Computing 2012), and study samplers defined by low degree polynomials. An $n$-tuple $P = (P_1,\dots, P_n)$ of functions $P_i \colon…

Computational Complexity · Computer Science 2026-05-05 Mohammad Mahdi Khodabandeh , Igor Shinkar

We examine a generalization of the binomial distribution associated with a strictly increasing sequence of numbers and we prove its Poisson-like limit. Such generalizations might be found in quantum optics with imperfect detection. We…

Mathematical Physics · Physics 2015-05-28 E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

Goldman [7] proved that the distribution of a stationary determinantal point process (DPP) $\Phi$ can be coupled with its reduced Palm version $\Phi^{0,!}$ such that there exists a point process $\eta$ where $\Phi = \Phi^{0,!} \cup \eta$ in…

Probability · Mathematics 2018-07-26 François Baccelli , Eliza O'Reilly

In this paper we characterize all the $r$-parameter families of count distributions (satisfying mild conditions) that are closed under addition and under binomial subsampling. Surprisingly, few families satisfy both properties and the…

Statistics Theory · Mathematics 2011-11-10 Pedro Puig , Jordi Valero

Let $X$ be a mean zero Gaussian random vector in a separable Hilbert space ${\mathbb H}$ with covariance operator $\Sigma:={\mathbb E}(X\otimes X).$ Let $\Sigma=\sum_{r\geq 1}\mu_r P_r$ be the spectral decomposition of $\Sigma$ with…

Statistics Theory · Mathematics 2016-01-08 Vladimir Koltchinskii , Karim Lounici

This article investigates the asymptotic distribution of penalized estimators with non-differentiable penalties designed to recover low-dimensional pattern structures. Patterns play a central role in estimation, as they reveal the…

Statistics Theory · Mathematics 2025-11-18 Ivan Hejný , Jonas Wallin , Małgorzata Bogdan

The negative binomial distribution is self similar: If the spectrum over the whole rapidity range gives rise to a negative binomial, in absence of correlation and if the source is unique, also a partial range in rapidity gives rise to the…

High Energy Physics - Phenomenology · Physics 2009-10-30 Giorgio Calucci , Daniele Treleani

We study the convergence of a random iterative sequence of a family of operators on infinite dimensional Hilbert spaces, inspired by the Stochastic Gradient Descent (SGD) algorithm in the case of the noiseless regression, as studied in [1].…

Functional Analysis · Mathematics 2022-09-02 Soumyadip Ghosh , Yingdong Lu , Tomasz J. Nowicki

We introduce the problem of simultaneously learning all powers of a Poisson Binomial Distribution (PBD). A PBD of order $n$ is the distribution of a sum of $n$ mutually independent Bernoulli random variables $X_i$, where $\mathbb{E}[X_i] =…

Data Structures and Algorithms · Computer Science 2017-07-19 Dimitris Fotakis , Vasilis Kontonis , Piotr Krysta , Paul Spirakis

Within the framework of probability models for overdispersed count data, we propose the generalized fractional Poisson distribution (gfPd), which is a natural generalization of the fractional Poisson distribution (fPd), and the standard…

Probability · Mathematics 2021-01-12 Dexter Cahoy , Elvira Di Nardo , Federico Polito

Random discrete distributions, say $F,$ known as species sampling models, represent a rich class of models for classification and clustering, in Bayesian statistics and machine learning. They also arise in various areas of probability and…

Statistics Theory · Mathematics 2019-08-21 Lanelot F. James

A generalization of the Poisson distribution based on the generalized Mittag-Leffler function $E_{\alpha, \beta}(\lambda)$ is proposed and the raw moments are calculated algebraically in terms of Bell polynomials. It is demonstrated, that…

Statistics Theory · Mathematics 2018-02-23 Richard Herrmann

The generalized parton distributions, introduced nearly a decade ago, have emerged as a universal tool to describe hadrons in terms of quark and gluonic degrees of freedom. They combine the features of form factors, parton densities and…

High Energy Physics - Phenomenology · Physics 2009-09-29 A. V. Belitsky , A. V. Radyushkin

Applying arguments based on the operator product expansion for a three-point correlator and relying on quark-hadron duality, we derive an expression for the skewed (non-forward) parton distribution in the pion in the case of a…

High Energy Physics - Phenomenology · Physics 2009-08-25 Alexander P. Bakulev , Rusko Ruskov , Klaus Goeke , N. G. Stefanis

We derive large-sample and other limiting distributions of the ``frequency of frequencies'' vector, ${\bf M_n}$, together with the number of species, $K_n$, in a Poisson-Dirichlet or generalised Poisson-Dirichlet gene or species sampling…

Statistics Theory · Mathematics 2023-09-06 Ross Maller , Soudabeh Shemehsavar

We develop a Bayesian nonparametric approach to a general family of latent class problems in which individuals can belong simultaneously to multiple classes and where each class can be exhibited multiple times by an individual. We introduce…

Methodology · Statistics 2013-06-11 Tamara Broderick , Lester Mackey , John Paisley , Michael I. Jordan