Comparison of model evidence for each simulated dataset and model.

This was computed with sequential Monte Carlo (SMC), using the integrated likelihood and separately using the full likelihood. This was repeated for 8 random initialisations with 2000 draws at each step in SMC, and we present the mean and standard deviation of the model evidence from each run. For each approach, the model with the strongest evidence is marked with * (this is not clear for with rounding here, but see the repository [17] for full results). For each model, we also report the time taken to complete the sampling for all initialisations, averaged across the different datasets.

此项计算采用序列蒙特卡洛（sequential Monte Carlo, SMC）方法，分别使用积分似然与完整似然两种方式完成。随后我们针对8次随机初始化重复该流程，每次SMC步骤均执行2000次抽样，并报告各次运行所得模型证据的均值与标准差。针对每种计算方案，我们将模型证据最优的模型以*标记（受限于当前的四舍五入处理，此处暂无法明确判定，完整结果可查阅参考文献[17]对应的代码仓库）。针对每类模型，我们同时报告了所有初始化下的采样总耗时，并按不同数据集求取平均值。