Data from: Generalized Frequency Coding: A Method of Preparing Polymorphic Multistate Characters for Phylogenetic Analysis

A new method of coding polymorphic multistate characters for phylogenetic analysis is presented. By dividing such characters into subcharacters, their frequency distributions can be represented with discrete states. Differential weighting is employed to counter the effect of using multiple characters to represent one character. The new method, termed generalized frequency coding (GFC), is potentially superior to previously used methods in that it incorporates more information and can be applied to both qualitative and quantitative characters. The method was applied to a previously published data set that includes both types of polymorphic multistate characters, and performed well according to congruence with other studies and the g1 and nonparametric bootstrap statistics. The data set was also used to compare GFC to both gap-weighting and Manhattan distance step matrix coding. On these grounds and for philosophical reasons, GFC was found to be a better estimator of phylogeny.本研究提出一种用于系统发育分析的多态多状态性状编码新方法。通过将此类性状拆分为子性状，其频率分布可通过离散状态进行表征。本研究采用差异加权策略以抵消使用多个性状表征单个性状所带来的影响。该新方法被命名为广义频率编码（Generalized Frequency Coding, GFC），有望优于此前使用的编码方法，原因在于其可纳入更多信息，且同时适用于定性性状与定量性状。将该方法应用于一套同时包含两类多态多状态性状的已发表数据集，通过与其他研究的一致性以及g1统计量和非参数自举统计量的验证，结果表现优异。该数据集还被用于对比广义频率编码与间隙加权法、曼哈顿距离步长矩阵编码法的性能差异。基于上述依据并结合哲学层面的考量，广义频率编码被证实是更优的系统发育重建估计方法。