Diversification rates vary across species as a response to various factors, including environmental conditions and species-specific features. Phylogenetic models that allow accounting for and quantifying this heterogeneity in diversification rates have proven particularly useful for understanding clades diversification. Recently, we introduced the cladogenetic diversification rate shift model, which allows inferring multiple rate changes of small magnitude across lineages. Here, we present a new inference technique for this model that considerably reduces computation time through the use of data augmentation and provide an implementation of this method in Julia. In addition to drastically reducing computation time, this new inference approach provides a posterior distribution of the augmented data, that is the tree with extinct and unsampled lineages as well as associated diversification rates. In particular, this allows extracting the distribution through time of both the mean rate and the number of lineages. We assess the statistical performances of our approach using simulations and illustrate its application on the entire bird radiation.[Birth–death model; data augmentation; diversification; macroevolution.]

中文翻译：

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使用数据增强快速准确地估计特定物种的多样化率

作为对各种因素的反应，包括环境条件和物种特异性特征，物种的多样化率会有所不同。允许解释和量化多样化率的这种异质性的系统发育模型已被证明对于理解进化枝多样化特别有用。最近，我们引入了进化枝多样化速率变化模型，该模型允许推断跨谱系的多个小幅度的速率变化。在这里，我们为该模型提出了一种新的推理技术，该技术通过使用数据增强显着减少了计算时间，并在 Julia 中提供了该方法的实现。除了大大减少计算时间外，这种新的推理方法还提供了增强数据的后验分布，那是具有灭绝和未采样血统以及相关多样化率的树。特别是，这允许提取平均速率和谱系数量随时间的分布。我们使用模拟评估我们方法的统计性能，并说明其在整个鸟类辐射中的应用。数据增强；多样化; 宏观进化。]