Felsenstein Joseph
Department of Genome Sciences, University of Washington, Box 357730, Seattle, WA 98195-7730, USA.
Philos Trans R Soc Lond B Biol Sci. 2005 Jul 29;360(1459):1427-34. doi: 10.1098/rstb.2005.1669.
Sewall Wright's threshold model has been used in modelling discrete traits that may have a continuous trait underlying them, but it has proven difficult to make efficient statistical inferences with it. The availability of Markov chain Monte Carlo (MCMC) methods makes possible likelihood and Bayesian inference using this model. This paper discusses prospects for the use of the threshold model in morphological systematics to model the evolution of discrete all-or-none traits. There the threshold model has the advantage over 0/1 Markov process models in that it not only accommodates polymorphism within species, but can also allow for correlated evolution of traits with far fewer parameters that need to be inferred. The MCMC importance sampling methods needed to evaluate likelihood ratios for the threshold model are introduced and described in some detail.
休厄尔·赖特的阈值模型已被用于对离散性状进行建模,这些离散性状可能有一个连续性状作为其基础,但事实证明,用该模型进行有效的统计推断很困难。马尔可夫链蒙特卡罗(MCMC)方法的出现使得使用该模型进行似然推断和贝叶斯推断成为可能。本文讨论了在形态系统学中使用阈值模型来模拟离散的全有或全无性状进化的前景。在那里,阈值模型相对于0/1马尔可夫过程模型具有优势,因为它不仅能够处理物种内的多态性,而且还可以用少得多的需要推断的参数来考虑性状的相关进化。本文详细介绍并描述了评估阈值模型似然比所需的MCMC重要性抽样方法。