Distributions of cherries and pitchforks for the Ford model

IF 1.2 4区 生物学 Q4 ECOLOGY
Gursharn Kaur , Kwok Pui Choi , Taoyang Wu
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引用次数: 1

Abstract

Distributional properties of tree shape statistics under random phylogenetic tree models play an important role in investigating the evolutionary forces underlying the observed phylogenies. In this paper, we study two subtree counting statistics, the number of cherries and that of pitchforks for the Ford model, the alpha model introduced by Daniel Ford. It is a one-parameter family of random phylogenetic tree models which includes the proportional to distinguishable arrangement (PDA) and the Yule models, two tree models commonly used in phylogenetics. Based on a non-uniform version of the extended Pólya urn models in which negative entries are permitted for their replacement matrices, we obtain the strong law of large numbers and the central limit theorem for the joint distribution of these two statistics for the Ford model. Furthermore, we derive a recursive formula for computing the exact joint distribution of these two statistics. This leads to exact formulas for their means and higher order asymptotic expansions of their second moments, which allows us to identify a critical parameter value for the correlation between these two statistics. That is, when the number of tree leaves is sufficiently large, they are negatively correlated for 0α1/2 and positively correlated for 1/2<α<1.

福特车型的樱桃和干草叉分布
随机系统发育树模型下树形统计的分布特性在研究所观察到的系统发育背后的进化力方面发挥着重要作用。在本文中,我们研究了Daniel Ford引入的alpha模型Ford模型的两个子树计数统计数据,即樱桃数量和干草叉数量。它是一个单参数的随机系统发育树模型家族,包括系统发育学中常用的比例可区分排列(PDA)和Yule模型。基于扩展的Pólya-urn模型的非均匀版本,其中它们的替换矩阵允许负项,我们得到了Ford模型的强数定律和这两个统计量联合分布的中心极限定理。此外,我们还导出了计算这两个统计量的精确联合分布的递归公式。这导致了它们的平均值的精确公式和二阶矩的高阶渐近展开式,这使我们能够确定这两个统计量之间相关性的关键参数值。也就是说,当树叶数量足够大时,它们在0≤α≤1/2时呈负相关,在1/2<;α<;1.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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