Figure 5.

Power to avoid spurious estimation of small temporal variance in divergences when divergence times are random. The power of models (A–D)M_msBayes, (E–H)M_Ushaped, (I–L)M_Uniform, and (M–P)M_DPP to detect random variation in divergence times as simulated under the ${\mathcal{ℳ}}_{\mathit{\text{msBayes}}}$ series of models. The plots illustrate the estimated dispersion index of divergence times ($\left|\widehat{\tau }\right|$) from analyses of 1000 datasets simulated under each of the ${\mathcal{ℳ}}_{\mathit{\text{msBayes}}}$ models, with the the estimated probability of the model inferring one divergence event, $p\left(\right|\widehat{\tau }|<0.01)$, given for each combination. The 22 divergence times were randomly drawn as indicated above each column of plots, where time is respresented as millions of generations ago (MGA) according to a per-site rate of 1 × 10⁻⁸ mutations per generation. Four of the six data-generating models of the ${\mathcal{ℳ}}_{\mathit{\text{msBayes}}}$ series are shown; please see Additional file 1: Figure S20 for all results.