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A tale of two tails: peakedness properties in inheritance models of evolutionary theory

机译:两条尾巴的故事:进化理论的继承模型中的峰度属性

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In this paper, we study transmission of traits through generations in multifactorial inheritance models with sex- and time-dependent heritability. We further analyze the implications of these models under heavy-tailedness of traits' distributions. Among other results, we show that in the case of a trait (for instance, a medical or behavioral disorder or a phenotype with significant heritability affecting human capital in an economy) with not very thick-tailed initial density, the trait distribution becomes increasingly more peaked, that is, increasingly more concentrated and unequally spread, with time. But these patterns are reversed for traits with sufficiently heavy-tailed initial distributions (e.g., a medical or behavioral disorder for which there is no strongly expressed risk group or a relatively equally distributed ability with significant genetic influence). Such traits' distributions become less peaked over time and increasingly more spread in the population. The proof of the results in the paper is based on the general results on majorization properties of heavy-tailed distributions obtained recently in Ibragimov (Econom Theory 23: 501-517, 2007) and also presented in the author's Ph.D. dissertation (Ibragimov, New majorization theory in economics and martingale convergence results in econometrics. Yale University, 2005) and several their extensions derived in this work.
机译:在本文中,我们研究了具有性别和时间依赖性遗传力的多因素遗传模型中各代性状的传播。我们进一步分析这些模型在特征分布的重尾性下的含义。在其他结果中,我们表明,在特征(例如,医学或行为失常或具有显着遗传力的表型会影响经济中的人力资本)的初始密度不是很高的情况下,特征分布会越来越多高峰,即随着时间的流逝越来越集中和分布不均。但是,对于具有足够大量尾巴初始分布的特征(例如,没有强烈表达风险的人群或具有显着遗传影响的相对均等分布的能力的医学或行为失调)而言,这些模式是相反的。随着时间的流逝,这些特征的分布不再达到峰值,并且在人群中的传播越来越多。本文结果的证明是基于最近在易卜拉欣莫夫(Econom Theory 23:501-517,2007)中获得的重尾分布的主要化性质的一般结果,该结果也发表在作者的博士学位论文中。论文(易卜拉欣莫夫(Ibragimov),经济学和mar理论上的新的专业化理论在计量经济学中得出。耶鲁大学,2005年)及其在本工作中得到的一些扩展。

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