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无限等位基因莫兰模型中向尤恩斯抽样公式的收敛时间。

Convergence time to the Ewens sampling formula in the infinite alleles Moran model.

作者信息

Watkins Joseph C

机构信息

Department of Mathematics, University of Arizona, Tucson, AZ 85721, USA.

出版信息

J Math Biol. 2010 Feb;60(2):189-206. doi: 10.1007/s00285-009-0255-x. Epub 2009 Mar 15.

Abstract

In this paper, we establish an upper bound for time to convergence to stationarity for the discrete time infinite alleles Moran model. If M is the population size and mu is the mutation rate, this bound gives a cutoff time of log(Mmu)/mu generations. The stationary distribution for this process in the case of sampling without replacement is the Ewens sampling formula. We show that the bound for the total variation distance from the generation t distribution to the Ewens sampling formula is well approximated by one of the extreme value distributions, namely, a standard Gumbel distribution. Beginning with the card shuffling examples of Aldous and Diaconis and extending the ideas of Donnelly and Rodrigues for the two allele model, this model adds to the list of Markov chains that show evidence for the cutoff phenomenon. Because of the broad use of infinite alleles models, this cutoff sets the time scale of applicability for statistical tests based on the Ewens sampling formula and other tests of neutrality in a number of population genetic studies.

摘要

在本文中,我们为离散时间无限等位基因莫兰模型建立了收敛到平稳状态的时间上限。如果(M)是种群大小,(\mu)是突变率,这个上限给出了(\log(M\mu)/\mu)代的截止时间。在无放回抽样情况下,该过程的平稳分布是尤恩斯抽样公式。我们表明,从第(t)代分布到尤恩斯抽样公式的总变差距离的上限可以很好地用一种极值分布来近似,即标准耿贝尔分布。从奥尔德斯和迪亚科尼斯的洗牌例子开始,并扩展唐纳利和罗德里格斯对双等位基因模型的想法,这个模型加入了显示截止现象证据的马尔可夫链列表。由于无限等位基因模型的广泛应用,这个截止确定了基于尤恩斯抽样公式的统计检验以及许多群体遗传学研究中其他中性检验的适用时间尺度。

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