Parameter Identifiability of a Multitype Pure-Birth Model of Speciation
Parameter Identifiability of a Multitype Pure-Birth Model of Speciation
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DOI：
10.1089/cmb.2022.0330
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发表时间：
2023-02-06
影响因子：
1.7
通讯作者：
Rhodes, John A.
中科院分区：
文献类型：
--
作者：
Dragomir, Dakota;Allman, Elizabeth S.;Rhodes, John A.
多样性模型描述了进化树的随机生长，通过物种形成和灭绝事件来模拟物种的历史关系。一类这样的模型允许独立改变树内物种的特征或类型，物种形成和灭绝率取决于此。尽管参数的可识别性对于证明模型参数估计的合理性是必要的，但尽管这些模型用于推理，但尚未正式建立这些模型的可识别性。这项工作建立了通用的可识别性标签交换的参数的一个简单的形式，这样一个模型，一个多类型的纯出生模型的物种形成，从一个渐近分布来自一个单一的树观察，因为它的深度去到无穷大。对于可用数据的应用来说，至关重要的是，在树的任何内部点都不需要观察类型，甚至在叶子上也不需要。
Diversification models describe the random growth of evolutionary trees, modeling the historical relationships of species through speciation and extinction events. One class of such models allows for independently changing traits, or types, of the species within the tree, upon which speciation and extinction rates depend. Although identifiability of parameters is necessary to justify parameter estimation with a model, it has not been formally established for these models, despite their adoption for inference. This work establishes generic identifiability up to label swapping for the parameters of one of the simpler forms of such a model, a multitype pure birth model of speciation, from an asymptotic distribution derived from a single tree observation as its depth goes to infinity. Crucially for applications to available data, no observation of types is needed at any internal points in the tree, nor even at the leaves.