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When modeling the distribution of a set of data by a mixture of Gaussians, there are two possibilities: i) the classical one is using a set of parameters which are the proportions, the means and the variances; ii) the second is to consider…

Data Analysis, Statistics and Probability · Physics 2009-11-13 Ali Mohammad-Djafari

A family of consistent tests, derived from a characterization of the probability generating function, is proposed for assessing Poissonity against a wide class of count distributions, which includes some of the most frequently adopted…

Statistics Theory · Mathematics 2024-06-11 Antonio Di Noia , Marzia Marcheselli , Caterina Pisani , Luca Pratelli

We consider a system of $N$ identical server pools and a single dispatcher where tasks arrive as a Poisson process of rate $\lambda(N)$. Arriving tasks cannot be queued, and must immediately be assigned to one of the server pools to start…

We propose a new method, probabilistic divide-and-conquer, for improving the success probability in rejection sampling. For the example of integer partitions, there is an ideal recursive scheme which improves the rejection cost from…

Probability · Mathematics 2015-11-25 Richard Arratia , Stephen DeSalvo

The two parameter Poisson-Dirichlet Process (PDP), a generalisation of the Dirichlet Process, is increasingly being used for probabilistic modelling in discrete areas such as language technology, bioinformatics, and image analysis. There is…

Statistics Theory · Mathematics 2012-02-17 Wray Buntine , Marcus Hutter

We overview results on the topic of Poisson approximation that are missed in existing surveys. The topic of Poisson approximation to the distribution of a sum of integer-valued random variables is presented as well. We do not restrict…

Probability · Mathematics 2019-04-12 S. Y. Novak

We consider the problem of approximating two, possibly unrelated probability distributions from a single complex-valued function $\psi$ and its Fourier transform. We show that this problem always has a solution within a specified degree of…

Mathematical Physics · Physics 2011-01-12 W. D. Flanders , G. Japaridze

Diffusion of a two component fluid is studied in the framework of differential equations, but where these equations are systematically derived from a well-defined microscopic model. The model has a finite carrying capacity imposed upon it…

Statistical Mechanics · Physics 2015-06-04 D. Fanelli , A. J. McKane , G. Pompili , B. Tiribilli , M. Vassalli , T. Biancalani

In the present paper new insights into the study of the Non-central Dirichlet distribution are provided. This latter is the analogue of the Dirichlet distribution obtained by replacing the Chi-Squared random variables involved in its…

Statistics Theory · Mathematics 2021-08-23 Carlo Orsi

Mutually uncorrelated random discrete events, manifesting a common basic process, are examined often in terms of their occurrence rate as a function of one or more of their distinguishing attributes, such as measurements of photon spectrum…

Instrumentation and Methods for Astrophysics · Physics 2012-07-26 Avinash A. Deshpande , Harsha Raichur

The one-dimensional Dickman distribution arises in various stochastic models across number theory, combinatorics, physics, and biology. Recently, a definition of the multidimensional Dickman distribution has appeared in the literature,…

Probability · Mathematics 2026-04-30 Anastasiia S. Kovtun , Nikolai N. Leonenko , Andrey Pepelyshev

Computer-based tests with randomly generated questions allow a large number of different tests to be generated. Given a fixed number of alternatives for each question, the number of tests that need to be generated before all possible…

Probability · Mathematics 2010-03-04 Charles M. Goldie , Rosie Cornish , Carol L. Robinson

Motivated by real-world machine learning applications, we analyze approximations to the non-asymptotic fundamental limits of statistical classification. In the binary version of this problem, given two training sequences generated according…

Information Theory · Computer Science 2018-12-07 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit…

Information Theory · Computer Science 2010-08-24 Yuriy A. Reznik

Diffusion models have emerged as powerful tools for solving inverse problems, yet prior work has primarily focused on observations with Gaussian measurement noise, restricting their use in real-world scenarios. This limitation persists due…

Machine Learning · Statistics 2025-02-11 Alessandro Micheli , Mélodie Monod , Samir Bhatt

The Zipf distribution is a probability distribution widely used by scientists from various disciplines due to its ubiquity. Some of these areas include linguistics, physics, genetics, and sociology, among others. In this paper, it is proved…

Statistics Theory · Mathematics 2025-11-17 Marta Pérez-Casany , Ariel Duarte-López , Jordi Valero

The computation of two Bayesian predictive distributions which are discrete mixtures of incomplete beta functions is considered. The number of iterations can easily become large for these distributions and thus, the accuracy of the result…

Statistics Theory · Mathematics 2007-06-13 Jacques Poitevineau , Bruno Lecoutre

A compound Poisson process whose randomized time is an independent Poisson process is called compound Poisson process with Poisson subordinator. We provide its probability distribution, which is expressed in terms of the Bell polynomials,…

Probability · Mathematics 2015-11-18 Antonio Di Crescenzo , Barbara Martinucci , Shelemyahu Zacks

This note is motivated by connections between the online and offline problems of selecting a possibly long subsequence from a Poisson-paced sequence of uniform marks under either a monotonicity or a sum constraint. The offline problem with…

Probability · Mathematics 2020-07-16 Alexander Gnedin

The Bayesian approach to inference stands out for naturally allowing borrowing information across heterogeneous populations, with different samples possibly sharing the same distribution. A popular Bayesian nonparametric model for…

Methodology · Statistics 2022-01-25 Antonio Lijoi , Igor Prünster , Giovanni Rebaudo