Data from: The estimation of tree posterior probabilities using conditional clade probability distributions

In this paper I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees, but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample.本文提出将分离子树的条件独立性作为一项原则，借此采用演化支（clade）条件概率分布而非简单样本相对频率来估算进化树的后验概率。本文详述了用于此类计算的算法，以及实现该思路的配套软件。研究证实，针对高概率进化树，该替代计算方法与简单样本相对频率的结果高度吻合；但针对低概率进化树，其准确性则显著更优。当未采样进化树仅包含其他已采样进化树中存在的演化支时，本方法可计算其对应的后验概率。此外，该方法还可用于估算已采样进化树集合的总概率，以此衡量后验采样集的完备程度。