负二项过程模型中的广义Dickman分布和种数

IF 0.9 4区 数学 Q3 STATISTICS & PROBABILITY
Yuguang F. Ipsen, R. Maller, S. Shemehsavar
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引用次数: 3

摘要

摘要本文推导了一个由$\alpha$稳定从属关系构造的Kingman泊松-狄利克雷模型中物种数量的大样本分布,该模型的基础是负二项过程而不是泊松过程。因此,它取决于从属参数$\alpha\in (0,1)$和负二项过程参数$r>0$。物种数量的大样本分布由样本量$n\to\infty$导出。推导中的一个重要组成部分是引入Dickman分布的双参数版本,推广现有的单参数版本。我们的分析增加了可用于建模目的的泊松-狄利克雷相关分布的范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A generalised Dickman distribution and the number of species in a negative binomial process model
Abstract We derive the large-sample distribution of the number of species in a version of Kingman’s Poisson–Dirichlet model constructed from an $\alpha$ -stable subordinator but with an underlying negative binomial process instead of a Poisson process. Thus it depends on parameters $\alpha\in (0,1)$ from the subordinator and $r>0$ from the negative binomial process. The large-sample distribution of the number of species is derived as sample size $n\to\infty$ . An important component in the derivation is the introduction of a two-parameter version of the Dickman distribution, generalising the existing one-parameter version. Our analysis adds to the range of Poisson–Dirichlet-related distributions available for modeling purposes.
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来源期刊
Advances in Applied Probability
Advances in Applied Probability 数学-统计学与概率论
CiteScore
2.00
自引率
0.00%
发文量
64
审稿时长
6-12 weeks
期刊介绍: The Advances in Applied Probability has been published by the Applied Probability Trust for over four decades, and is a companion publication to the Journal of Applied Probability. It contains mathematical and scientific papers of interest to applied probabilists, with emphasis on applications in a broad spectrum of disciplines, including the biosciences, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used. A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.
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