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We study the response of a quantitative trait to exponential directional selection in a finite haploid population at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per…

Populations and Evolution · Quantitative Biology 2024-04-10 Hannah Götsch , Reinhard Bürger

Let $\eta_t$ be a Poisson point process of intensity $t\geq 1$ on some state space $\Y$ and $f$ be a non-negative symmetric function on $\Y^k$ for some $k\geq 1$. Applying $f$ to all $k$-tuples of distinct points of $\eta_t$ generates a…

Probability · Mathematics 2012-12-11 Matthias Schulte , Christoph Thaele

This paper investigates the asymptotic properties of parameter estimation for the Ewens--Pitman partition with parameters $0<\alpha<1$ and $\theta>-\alpha$. Especially, we show that the maximum likelihood estimator (MLE) of $\alpha$ is…

Statistics Theory · Mathematics 2025-05-06 Takuya Koriyama , Takeru Matsuda , Fumiyasu Komaki

Estimation of the allele frequency at genetic markers is a key ingredient in biological and biomedical research, such as studies of human genetic variation or of the genetic etiology of heritable traits. As genetic data becomes increasingly…

Applications · Statistics 2007-12-18 Marc Coram , Hua Tang

Probability proportional to size (PPS) sampling schemes with a target sample size aim to produce a sample comprising a specified number $n$ of items while ensuring that each item in the population appears in the sample with a probability…

Methodology · Statistics 2024-11-14 Brian Hentschel , Peter J. Haas , Yuanyuan Tian

The large deviation principle is established for the Poisson--Dirichlet distribution when the parameter $\theta$ approaches infinity. The result is then used to study the asymptotic behavior of the homozygosity and the Poisson--Dirichlet…

Probability · Mathematics 2007-05-23 Donald A. Dawson , Shui Feng

Consider a population of individuals belonging to an infinity number of types, and assume that type proportions follow the two-parameter Poisson-Dirichlet distribution. A sample of size n is selected from the population. The total number of…

Probability · Mathematics 2016-10-12 Stefano Favaro , Shui Feng , Fuqing Gao

Importance sampling is used to approximate Bayes' rule in many computational approaches to Bayesian inverse problems, data assimilation and machine learning. This paper reviews and further investigates the required sample size for…

Computation · Statistics 2021-02-03 Daniel Sanz-Alonso , Zijian Wang

The Ewens-Pitman model is a distribution for random partitions of the set $\{1,\ldots,n\}$, with $n\in\mathbb{N}$, indexed by parameters $\alpha \in [0,1)$ and $\theta>-\alpha$, such that $\alpha=0$ is the Ewens model in population…

Probability · Mathematics 2024-12-17 Claudia Contardi , Emanuele Dolera , Stefano Favaro

We give a general framework for approximations to combinatorial assemblies, especially suitable to the situation where the number $k$ of components is specified, in addition to the overall size $n$. This involves a Poisson process, which,…

Probability · Mathematics 2016-07-06 Richard Arratia , Stephen DeSalvo

We study the properties of variational Bayes approximations for exponential family models with missing values. It is shown that the iterative algorithm for obtaining the variational Bayesian estimator converges locally to the true value…

Statistics Theory · Mathematics 2012-07-19 Bo Wang , D. Titterington

In work on the two alleles Moran model, Ewens showed that the stationary distribution for the number of genes of one type can be approximated by a Beta distribution. In this short note, we provide a sharp error term for this approximation.…

Probability · Mathematics 2023-07-27 Jason Fulman

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

We show that the random point measures induced by vertices in the convex hull of a Poisson sample on the unit ball, when properly scaled and centered, converge to those of a mean zero Gaussian field. We establish limiting variance and…

Probability · Mathematics 2008-01-09 T. Schreiber , J. E. Yukich

The variance of a linear statistic defined on the symmetric group endowed with the Ewens probability is examined. Despite the dependence of the summands, it can be bounded from above by a constant multiple of the sum of variances. We find…

Combinatorics · Mathematics 2020-03-16 Zygimantas Baronenas , Eugenijus Manstavicius , Patricija Sapokaite

Boltzmann samplers, introduced by Duchon et al. in 2001, make it possible to uniformly draw approximate size objects from any class which can be specified through the symbolic method. This, through by evaluating the associated generating…

Discrete Mathematics · Computer Science 2014-11-14 Olivier Bodini , Jérémie Lumbroso , Nicolas Rolin

The results in this paper provide new information on asymptotic properties of classical models: the neutral Kingman coalescent under a general finite-alleles, parent-dependent mutation mechanism, and its generalisation, the ancestral…

Probability · Mathematics 2022-07-08 Martina Favero , Henrik Hult

The Ewens-Pitman model refers to a distribution for random partitions of $[n]=\{1,\ldots,n\}$, which is indexed by a pair of parameters $\alpha \in [0,1)$ and $\theta>-\alpha$, with $\alpha=0$ corresponding to the Ewens model in population…

Probability · Mathematics 2024-08-28 Bernard Bercu , Stefano Favaro

Many applications in genetic analyses utilize sampling distributions, which describe the probability of observing a sample of DNA sequences randomly drawn from a population. In the one-locus case with special models of mutation such as the…

Probability · Mathematics 2012-07-25 Anand Bhaskar , John A. Kamm , Yun S. Song

Given a large set $U$ where each item $a\in U$ has weight $w(a)$, we want to estimate the total weight $W=\sum_{a\in U} w(a)$ to within factor of $1\pm\varepsilon$ with some constant probability $>1/2$. Since $n=|U|$ is large, we want to do…

Data Structures and Algorithms · Computer Science 2021-10-29 Lorenzo Beretta , Jakub Tětek