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Related papers: Random derangements and the Ewens Sampling Formula

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We explore the cycle types of a class of biased random derangements, described as a random game played by some children labeled $1,\cdots,n$. Children join the game one by one, in a random order, and randomly form some circles of size at…

Probability · Mathematics 2022-11-28 Poly H. da Silva , Arash Jamshidpey , Simon Tavaré

This paper studies Markov chains on the symmetric group $S_n$ where the transition probabilities are given by the Ewens distribution with parameter $\theta>1$. The eigenvalues are identified to be proportional to the content polynomials of…

Probability · Mathematics 2022-09-21 Alperen Y. Özdemir

Feller (1945) provided a coupling between the counts of cycles of various sizes in a uniform random permutation of $[n]$ and the spacings between successes in a sequence of $n$ independent Bernoulli trials with success probability $1/n$ at…

Probability · Mathematics 2020-11-16 Joseph Najnudel , Jim Pitman

The general relationship between an arbitrary frequency distribution and the expectation value of the frequency distributions of its samples is discussed. A wide set of measurable quantities ("invariant moments") whose expectation value…

Data Analysis, Statistics and Probability · Physics 2015-06-15 Paolo Rossi

This paper develops an analogy between the cycle structure of, on the one hand, random permutations with cycle lengths restricted to lie in an infinite set $S$ with asymptotic density $\sigma$ and, on the other hand, permutations selected…

Combinatorics · Mathematics 2009-08-07 Michael Lugo

We show that the number of cycles in a random permutation chosen according to generalized Ewens measure is normally distributed and compute asymptotic estimates for the mean and variance.

Probability · Mathematics 2013-08-16 Kenneth Maples , Ashkan Nikeghbali , Dirk Zeindler

The Ewens sampling formula with parameter $\alpha$ is the distribution on $S_n$ which gives each $\pi\in S_n$ weight proportional to $\alpha^{C(\pi)}$, where $C(\pi)$ is the number of cycles of $\pi$. We show that, for any fixed $\alpha$,…

Group Theory · Mathematics 2019-01-23 Sean Eberhard

The Ewens sampling formula is a distribution related to the random partition of a positive integer. In this study, we investigate the issue of non-existence solutions in parameter estimation under the distribution. As a result, the first…

Statistics Theory · Mathematics 2021-05-25 Masayo Y. Hirose , Shuhei Mano

We consider Ewens random permutations of length $n$ conditioned to have no cycle longer than $n^\beta$ with $0<\beta<1$ and to study the asymptotic behaviour as $n\to\infty$. We obtain very precise information on the joint distribution of…

Probability · Mathematics 2020-04-22 Volker Betz , Julian Mühlbauer , Helge Schäfer , Dirk Zeindler

We study the number of random permutations needed to invariably generate the symmetric group, $S_n$, when the distribution of cycle counts has the strong $\alpha$-logarithmic property. The canonical example is the Ewens sampling formula,…

Probability · Mathematics 2016-10-18 Gerandy Brito , Christopher Fowler , Matthew Junge , Avi Levy

We show how to generate random derangements efficiently by two different techniques: random restricted transpositions and sequential importance sampling. The algorithm employing restricted transpositions can also be used to generate random…

Computation · Statistics 2020-08-17 J. R. G. Mendonça

Consider a random permutation of $\{1, \ldots, \lfloor n^{t_2}\rfloor\}$ drawn according to the Ewens measure with parameter $t_1$ and let $K(n, t)$ denote the number of its cycles, where $t\equiv (t_1, t_2)\in\mathbb [0, 1]^2$. Next,…

Probability · Mathematics 2021-06-21 Helmut Pitters

The purpose of this article is to present a general method to find limiting laws for some renormalized statistics on random permutations. The model considered here is Ewens sampling model, which generalizes uniform random permutations. We…

Probability · Mathematics 2013-10-28 Valentin Féray

Given n observations, we study the consistency of a batch of k new observations, in terms of their distribution function. We propose a non-parametric, non-likelihood test based on Edgeworth expansion of the distribution function. The…

Statistics Theory · Mathematics 2009-06-08 Mahendra Mariadassou , Avner Bar-Hen

Consider n unit intervals, say [1,2], [3,4], ..., [2n-1,2n]. Identify their endpoints in pairs at random, with all (2n-1)!! = (2n-1) (2n-3) ... 3 1 pairings being equally likely. The result is a collection of cycles of various lengths, and…

Combinatorics · Mathematics 2007-05-23 Nicholas Pippenger

In this article we study in detail a family of random matrix ensembles which are obtained from random permutations matrices (chosen at random according to the Ewens measure of parameter $\theta>0$) by replacing the entries equal to one by…

Probability · Mathematics 2010-05-05 Joseph Najnudel , Ashkan Nikeghbali

We consider an independently identically distributed random dynamical system generated by finitely many, non-uniformly expanding Markov interval maps with a finite number of branches. Assuming a topologically mixing condition and the…

Dynamical Systems · Mathematics 2022-03-23 Shintaro Suzuki , Hiroki Takahasi

We study a one-dimensional model of disordered electrons (also relevant for random spin chains), which exhibits a delocalisation transition at half-filling. Exact probability distribution functions for the Wigner time and transmission…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Steiner , Yang Chen , M. Fabrizio , Alexander O. Gogolin

We consider the distribution of cycle counts in a random regular graph, which is closely linked to the graph's spectral properties. We broaden the asymptotic regime in which the cycle counts are known to be approximately Poisson, and we…

Combinatorics · Mathematics 2023-07-14 Tobias Johnson

The problem of estimating an unknown discrete distribution from its samples is a fundamental tenet of statistical learning. Over the past decade, it attracted significant research effort and has been solved for a variety of divergence…

Machine Learning · Computer Science 2018-10-30 Yi Hao , Alon Orlitsky , Venkatadheeraj Pichapati
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