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Related papers: Random generation under the Ewens distribution

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We show that in a sample of size $n$ from a GEM$(0,\theta)$ random discrete distribution, the gaps $G_{i:n}:= X_{n-i+1:n} - X_{n-i:n}$ between order statistics $X_{1:n} \le \cdots \le X_{n:n}$ of the sample, with the convention $G_{n:n} :=…

Probability · Mathematics 2017-01-24 Jim Pitman , Yuri Yakubovich

Backwards analysis, first popularized by Seidel, is often the simplest most elegant way of analyzing a randomized algorithm. It applies to incremental algorithms where elements are added incrementally, following some random permutation,…

Data Structures and Algorithms · Computer Science 2017-04-18 Mathias Bæk Tejs Knudsen , Mikkel Thorup

This paper proposes an algorithm to generate random numbers from any member of the truncated multivariate elliptical family of distributions with a strictly decreasing density generating function. Based on Neal (2003) and Ho et al. (2012),…

Computation · Statistics 2021-12-20 Katherine A. L. Valeriano , Christian E. Galarza , Larissa A. Matos

A branching process in random environment $(Z_n, n \in \N)$ is a generalization of Galton Watson processes where at each generation the reproduction law is picked randomly. In this paper we give several results which belong to the class of…

Probability · Mathematics 2008-12-15 Vincent Bansaye , Julien Berestycki

We consider a general, neutral, dynamical model of biodiversity. Individuals have i.i.d. lifetime durations, which are not necessarily exponentially distributed, and each individual gives birth independently at constant rate \lambda. We…

Populations and Evolution · Quantitative Biology 2010-09-02 Amaury Lambert

A simple but powerful network model with $n$ nodes and $m$ partly overlapping layers is generated as an overlay of independent random graphs $G_1,\dots,G_m$ with variable sizes and densities. The model is parameterised by a joint…

Probability · Mathematics 2020-11-04 Mindaugas Bloznelis , Lasse Leskelä

We consider a class of growing random graphs obtained by creating vertices sequentially one by one: at each step, we choose uniformly the neighbours of the newly created vertex; its degree is a random variable with a fixed but arbitrary…

Combinatorics · Mathematics 2013-11-13 Svante Janson , Simone Severini

The aim of this paper is to extend Azzalini's method. This extension is done in two stages: consider two dependent and non-identically distributed random variables say $X_1$ and $X_2$; model the dependence between $X_1$ and $X_2$ by a…

Statistics Theory · Mathematics 2018-03-06 Filippo Domma , Božidar V. Popović , Saralees Nadarajah

Let $K(=K_{n,\theta})$ be a positive integer-valued random variable whose distribution is given by ${\rm P}(K = x) = \bar{s}(n,x) \theta^x/(\theta)_n$ $(x=1,\ldots,n) $, where $\theta$ is a positive number, $n$ is a positive integer,…

Statistics Theory · Mathematics 2022-03-29 Koji Tsukuda

In considering evolution of transcribed regions, regulatory modules, and other genomic loci of interest, we are often faced with a situation in which the number of allelic states greatly exceeds the population size. In this limit, the…

Populations and Evolution · Quantitative Biology 2016-07-27 Pavel Khromov , Constantin D. Malliaris , Alexandre V. Morozov

We investigate a model of evolving random network, introduced by us previously {[}{\it Phys. Rev. Lett.} {\bf 83}, 5587 (1999){]} . The model is a generalization of the Bak-Sneppen model of biological evolution, with the modification that…

Statistical Mechanics · Physics 2009-10-31 Frantisek Slanina , Miroslav Kotrla

This paper studies the eigenvalue distribution of the Watts-Strogatz random graph, which is known as the "small-world" random graph. The construction of the small-world random graph starts with a regular ring lattice of n vertices; each has…

Probability · Mathematics 2021-01-28 Poramate Nakkirt

We consider a regular $n$-ary tree of height $h$, for which every vertex except the root is labelled with an independent and identically distributed continuous random variable. Taking motivation from a question in evolutionary biology, we…

Probability · Mathematics 2013-11-14 Matthew I. Roberts , Lee Zhuo Zhao

The properties of randomly evolving special trees having defined and analyzed already in two earlier papers (arXiv:cond-mat/0205650 and arXiv:cond-mat/0211092) have been investigated in the case when the continuous time parameter converges…

Statistical Mechanics · Physics 2007-05-23 L. Pal

Starting with a set of weighted items, we want to create a generic sample of a certain size that we can later use to estimate the total weight of arbitrary subsets. For this purpose, we propose priority sampling which tested on Internet…

Data Structures and Algorithms · Computer Science 2007-05-23 Nick Duffield , Carsten Lund , Mikkel Thorup

Several representations of the exact cdf of the sum of squares of n independent gamma-distributed random variables Xi are given, in particular by a series of gamma distribution functions. Using a characterization of the gamma distribution…

Statistics Theory · Mathematics 2007-05-23 Thomas Royen

We study the length of cycles of random permutations drawn from the Mallows distribution. Under this distribution, the probability of a permutation $\pi \in \mathbb{S}_n$ is proportional to $q^{\textrm{inv}(\pi)}$ where $0<q\le 1$ and…

Probability · Mathematics 2017-09-12 Alexey Gladkich , Ron Peled

Inverse transform sampling is an exceptionally general method to generate non-uniform-distributed random numbers, but can be rather unstable when simulating extremely truncated distributions. Many famous probability models share a property…

Methodology · Statistics 2024-09-30 Lambardi di San Miniato , Michele , Kenne Pagui , Euloge Clovis

Using a self-replicating method, we generalize with a free parameter some Borwein algorithms for the number $\pi$. This generalization includes values of the Gamma function like $\Gamma(1/3)$, $\Gamma(1/4)$ and of course…

Number Theory · Mathematics 2017-02-22 Jesús Guillera

In the setting of entangled single-sample distributions, the goal is to estimate some common parameter shared by a family of distributions, given one \emph{single} sample from each distribution. We study mean estimation and linear…

Machine Learning · Computer Science 2020-07-08 Hui Yuan , Yingyu Liang