Griffiths Robert C, Jenkins Paul A, Song Yun S
University of Oxford.
Adv Appl Probab. 2008 Jun 1;40(2):473-500. doi: 10.1239/aap/1214950213.
The diffusion-generator approximation technique developed by De Iorio and Griffiths (2004a) is a very useful method of constructing importance sampling proposal distributions. Being based on general mathematical principles, the method can be applied to various models in population genetics. In this paper we extend the technique to the neutral coalescent model with recombination, thus obtaining novel sampling distributions for the two-locus model. We consider the case with subdivided population structure, as well as the classic case with only a single population. In the latter case we also consider the importance sampling proposal distributions suggested by Fearnhead and Donnelly (2001), and show that their two-locus distributions generally differ from ours. In the case of the infinitely-many-alleles model, our approximate sampling distributions are shown to be generally closer to the true distributions than are Fearnhead and Donnelly's.
由德约里奥和格里菲思(2004a)开发的扩散 - 生成器近似技术是构建重要性抽样提议分布的一种非常有用的方法。基于一般数学原理,该方法可应用于群体遗传学中的各种模型。在本文中,我们将该技术扩展到具有重组的中性合并模型,从而获得双位点模型的新型抽样分布。我们考虑了具有细分群体结构的情况,以及只有单个群体的经典情况。在后一种情况下,我们还考虑了费恩黑德和唐纳利(2001)提出的重要性抽样提议分布,并表明他们的双位点分布通常与我们的不同。在无限等位基因模型的情况下,我们的近似抽样分布通常比费恩黑德和唐纳利的更接近真实分布。