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This article introduces an algorithm to draw random discrete uniform variables within a given range of size n from a source of random bits. The algorithm aims to be simple to implement and optimal both with regards to the amount of random…

Data Structures and Algorithms · Computer Science 2013-04-09 Jérémie Lumbroso

This article presents an efficient algorithm to generate a discrete uniform distribution on a set of $p$ elements using a biased random source for $p$ prime. The algorithm generalizes Von Neumann's method and improves computational…

Probability · Mathematics 2023-01-18 Xiaoyu Lei

Unbiased random vectors i.e. distributed uniformly in n-dimensional space, are widely applied and the computational cost of generating a vector increases only linearly with n. On the other hand, generating uniformly distributed random…

Numerical Analysis · Mathematics 2021-04-05 Arun I. , Murugesan Venkatapathi

A general method to produce uniformly distributed pseudorandom numbers with extended precision by combining two pseudorandom numbers with lower precision is proposed. In particular, this method can be used for pseudorandom number generation…

Mathematical Software · Computer Science 2014-05-13 Vadim Demchik , Alexey Gulov

A method for generating random $U(1)$ variables with Boltzmann distribution is presented. It is based on the rejection method with transformation of variables. High efficiency is achieved for all range of temparatures or coupling…

High Energy Physics - Lattice · Physics 2009-10-22 Tetsuya Hattori , Hideo Nakajima

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

The distribution of the sum of independent identically distributed uniform random variables is well-known. However, it is sometimes necessary to analyze data which have been drawn from different uniform distributions. By inverting the…

Statistics Theory · Mathematics 2010-05-25 David M. Bradley , Ramesh C. Gupta

The problem of computing functions of values at the nodes in a network in a totally distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peer-to-peer,…

Networking and Internet Architecture · Computer Science 2007-05-23 Damon Mosk-Aoyama , Devavrat Shah

We describe a uniformly fast algorithm for generating points \vec{x} uniformly in a hypercube with the restriction that the difference between each pair of coordinates is bounded. We discuss the quality of the algorithm in the sense of its…

Computational Physics · Physics 2009-11-06 A. van Hameren , R. Kleiss

This paper studies the distributed optimization problem with possibly nonidentical local constraints, where its global objective function is composed of $N$ convex functions. The aim is to solve the considered optimization problem in a…

Optimization and Control · Mathematics 2022-08-26 Hongzhe Liu , Wenwu Yu , Guanghui Wen , Wei Xing Zheng

For a variant of the algorithm in [Pit19] (arXiv:1903.10816) to compute the approximate density or distribution function of a linear mixture of independent random variables known by a finite sample, it is presented a proof of the functional…

Statistics Theory · Mathematics 2019-06-19 Thomas Pitschel

We propose efficient techniques for generating independent identically distributed uniform random samples inside semialgebraic sets. The proposed algorithm leverages recent results on the approximation of indicator functions by polynomials…

Optimization and Control · Mathematics 2014-03-20 Fabrizio Dabbene , Didier Henrion , Constantino Lagoa

We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials over a sufficiently large finite field, produces a common…

Data Structures and Algorithms · Computer Science 2009-02-10 Mahdi Cheraghchi , Amin Shokrollahi

In this paper we provide an algorithm that generates a graph with given degree sequence uniformly at random. Provided that $\Delta^4=O(m)$, where $\Delta$ is the maximal degree and $m$ is the number of edges,the algorithm runs in expected…

Combinatorics · Mathematics 2021-01-25 Andrii Arman , Pu Gao , Nicholas Wormald

A universal generator for integer-valued square-integrable random variables is introduced. The generator relies on a rejection technique based on a generalization of the inversion formula for integer-valued random variables. The proposal…

Computation · Statistics 2012-11-06 Lucio Barabesi , Luca Pratelli

In a recent article a generalization of the binomial distribution associated with a sequence of positive numbers was examined. The analysis of the nonnegativeness of the formal expressions was a key-point to allow to give them a statistical…

Mathematical Physics · Physics 2015-06-04 H. Bergeron , E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

We establish the unimodality and the asymptotic strong unimodality of the ordinary multinomials and give their smallest mode leading to the expression of the maximal probability of convolution powers of the discrete uniform distribution. We…

Probability · Mathematics 2007-08-20 Hacene Belbachir

A systematic study of the probability distribution of superimposed random codes is presented through the use of generating functions. Special attention is paid to the cases of either uniformly distributed but not necessarily independent or…

Databases · Computer Science 2008-06-19 Bernd Günther

We develop a new approach for uniform generation of combinatorial objects, and apply it to derive a uniform sampler REG for d-regular graphs. REG can be implemented such that each graph is generated in expected time O(nd^3), provided that…

Combinatorics · Mathematics 2021-01-14 Pu Gao , Nicholas Wormald

We develop uniformly fast random variate generators for the Pearson IV distribution that can be used over the entire range of both shape parameters and highlight some applications in a Bayesian setting.

Computation · Statistics 2026-05-05 Luc Devroye , Joe R. Hill
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