Coalescence and sampling distributions for Feller diffusions

IF 1.2 4区 生物学 Q4 ECOLOGY
Conrad J. Burden , Robert C. Griffiths
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引用次数: 0

Abstract

Consider the diffusion process defined by the forward equation ut(t,x)=12{xu(t,x)}xxα{xu(t,x)}x for t,x0 and <α<, with an initial condition u(0,x)=δ(xx0). This equation was introduced and solved by Feller to model the growth of a population of independently reproducing individuals. We explore important coalescent processes related to Feller’s solution. For any α and x0>0 we calculate the distribution of the random variable An(s;t), defined as the finite number of ancestors at a time s in the past of a sample of size n taken from the infinite population of a Feller diffusion at a time t since its initiation. In a subcritical diffusion we find the distribution of population and sample coalescent trees from time t back, conditional on non-extinction as t. In a supercritical diffusion we construct a coalescent tree which has a single founder and derive the distribution of coalescent times.

费勒扩散的凝聚和采样分布
考虑由正向方程 ut(t,x)=12{xu(t,x)}xx-α{xu(t,x)}x 定义的扩散过程,当 t,x≥0 和 -∞<α<∞ 时,初始条件为 u(0,x)=δ(x-x0)。该方程由费勒提出并求解,用于模拟由独立繁殖个体组成的种群的增长。我们将探讨与费勒求解相关的重要凝聚过程。对于任意 α 和 x0>0,我们计算随机变量 An(s;t)的分布,An(s;t)的定义是:在费勒扩散的无限种群中,自扩散开始以来,在 t 时刻从大小为 n 的样本中抽取的祖先在过去 s 时刻的有限数量。在亚临界扩散中,我们可以找到从时间 t 开始的种群和样本凝聚树的分布,条件是 t→∞ 时没有灭绝。在超临界扩散中,我们构建了一棵具有单一创始者的凝聚树,并推导出凝聚时间的分布。
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来源期刊
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
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