Interacting particle systems undergoing repeated mutation and selection steps model genetic evolution, and also describe a broad class of sequential Monte Carlo methods. The genealogical tree embedded into the system is important in both applications. Under neutrality, when fitnesses of particles are independent from those of their parents, rescaled genealogies are known to converge to Kingman's coalescent. Recent work has established convergence under non-neutrality, but only for finite-dimensional distributions. We prove weak convergence of non-neutral genealogies on the space of c\`adl\`ag paths under standard assumptions, enabling analysis of the whole genealogical tree.
翻译:相互作用的粒子系统进行重复的突变和选择步骤来模拟遗传进化,并描述了广泛的顺序蒙特卡洛方法。嵌入系统中的谱系树在这两种应用中都很重要。在中立性下,当粒子的适应度与其父母的适应度不相关时,经过缩放的谱系被认为会收敛于金曼并线。最近的研究已经证明了在非中立性下的收敛性,但仅限于有限维分布。我们证明了在标准假设下,非中立的基因谱逐渐收敛于整个谱系树的c\`adl\`ag路径空间。