Maximum likelihood is a common method of estimating a phylogenetic tree based on a set of genetic data. However, models of evolution for certain types of genetic data are highly flawed in their specification, and this misspecification can have an adverse impact on phylogenetic inference. Our attention here is focused on extending an existing class of models for estimating phylogenetic trees from discrete morphological characters. The main advance of this work is a model that allows unequal equilibrium frequencies in the estimation of phylogenetic trees from discrete morphological character data using likelihood methods. Possible extensions of the proposed model will also be discussed.

中文翻译：

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基于离散形态特征的系统发育最大似然性扩展模型。

最大似然是基于一组遗传数据估计系统发育树的常用方法。但是，某些类型的遗传数据的演化模型的规范存在很大缺陷，这种错误指定可能会对系统发育推断产生不利影响。我们的注意力集中在扩展现有的用于从离散形态特征估计系统发育树的模型上。这项工作的主要进展是建立了一个模型，该模型允许使用似然法从离散的形态特征数据估计系统发育树时具有不相等的平衡频率。还将讨论所提议模型的可能扩展。