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系统发育推断:线性不变量与最大似然法。

Phylogenetic inference: linear invariants and maximum likelihood.

作者信息

Navidi W C, Churchill G A, von Haeseler A

机构信息

Department of Mathematics, University of Southern California, Los Angeles 90089-1113.

出版信息

Biometrics. 1993 Jun;49(2):543-55.

PMID:7690255
Abstract

We develop a new statistical method for inferring phylogenies, based on a likelihood ratio test. This method does not require parameter constraints but does require identical evolutionary processes in the sites considered. Another method of phylogenetic inference is the method of linear invariants, described by Cavender (1989, Molecular Biology and Evolution 6, 301-316), based on a notion of Lake (1987, Molecular Biology and Evolution 4, 167-191). We describe a sound mathematical basis for the use of linear invariants. We show that the validity of the method requires parameter constraints, but does not require that the evolutionary processes in differing sites be identical. We show that the method of linear invariants is asymptotically equivalent to a less powerful version of our likelihood ratio test, and is thus essentially a maximum likelihood technique.

摘要

我们基于似然比检验开发了一种用于推断系统发育的新统计方法。该方法不需要参数约束,但要求所考虑的位点具有相同的进化过程。系统发育推断的另一种方法是线性不变量法,由卡文德(1989年,《分子生物学与进化》6卷,301 - 316页)基于莱克(1987年,《分子生物学与进化》4卷,167 - 191页)的概念描述。我们描述了使用线性不变量的合理数学基础。我们表明该方法的有效性需要参数约束,但不要求不同位点的进化过程相同。我们表明线性不变量法渐近等同于我们似然比检验的一个效力较低的版本,因此本质上是一种最大似然技术。

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