Goldman N
Department of Zoology, University of Cambridge, UK.
J Mol Evol. 1993 Feb;36(2):182-98. doi: 10.1007/BF00166252.
Penny et al. have written that "The most fundamental criterion for a scientific method is that the data must, in principle, be able to reject the model. Hardly any [phylogenetic] tree-reconstruction methods meet this simple requirement." The ability to reject models is of such great importance because the results of all phylogenetic analyses depend on their underlying models--to have confidence in the inferences, it is necessary to have confidence in the models. In this paper, a test statistic suggested by Cox is employed to test the adequacy of some statistical models of DNA sequence evolution used in the phylogenetic inference method introduced by Felsenstein. Monte Carlo simulations are used to assess significance levels. The resulting statistical tests provide an objective and very general assessment of all the components of a DNA substitution model; more specific versions of the test are devised to test individual components of a model. In all cases, the new analyses have the additional advantage that values of phylogenetic parameters do not have to be assumed in order to perform the tests.
“科学方法最基本的标准是,数据在原则上必须能够否定模型。几乎没有任何[系统发育]树重建方法满足这一简单要求。”否定模型的能力至关重要,因为所有系统发育分析的结果都取决于其基础模型——要对推断有信心,就必须对模型有信心。在本文中,采用考克斯提出的一个检验统计量来检验费尔斯滕森引入的系统发育推断方法中使用的一些DNA序列进化统计模型的充分性。蒙特卡罗模拟用于评估显著性水平。由此产生的统计检验为DNA替代模型的所有组成部分提供了客观且非常通用的评估;还设计了更具体的检验版本来检验模型的各个组成部分。在所有情况下,新的分析还有一个额外的优点,即进行检验时不必假设系统发育参数的值。