Best fit demographic model for different HIV-1 subtype BCAR clades.

Log marginal likelihood (ML) estimates for the logistic (Log), exponential (Expo) and expansion (Expa) growth demographic models obtained using the path sampling (PS) and stepping-stone sampling (SS) methods. The Log Bayes factor (BF) is the difference of the Log ML between of alternative (H1) and null (H0) models (H1/H0). Log BF >3 indicate that model H1 is more strongly supported by the data than model H0.本数据集包含采用路径抽样（Path Sampling, PS）与阶梯抽样（Stepping-Stone Sampling, SS）方法，针对逻辑增长（Logistic, 简称Log）、指数增长（Exponential, 简称Expo）及种群扩张（Expansion, 简称Expa）三类种群人口统计学模型得到的对数边际似然（Log Marginal Likelihood, ML）估计值。其中，对数贝叶斯因子（Log Bayes Factor, BF）定义为备择假设模型（H1）与原假设模型（H0）的对数边际似然值之差，其对应比值为H1/H0；当对数贝叶斯因子大于3时，表明数据对模型H1的支持强度显著高于模型H0。