Figure 1.
This tree was obtained from a combined molecular–phenotypic data set analyzed by Pyron [27].
Figure 2.
A schematic representing different missing data distributions.
Columns represent characters. In the taxon-names column, an asterisk represents fossil taxa. Characters with the slowest rate of change are represented in light grey; intermediate-rate characters are represented in medium grey; characters with highest rate of change are represented in dark grey. In the top matrix, all characters are present for all taxa. The bottom matrices illustrate the missing data conditions that we simulated in this paper.
Figure 3.
Results from simulations with a single rate of character evolution.
Bayesian-Mk outperforms parsimony most strongly when the rate of character evolution (and hence homoplasy) is high.
Figure 4.
In data sets with character rate heterogeneity and with no missing data, Bayesian-Mk results in lower error compared to parsimony analyses.
Note that, unlike Figure 3, the X-axis is the average rate of change across all characters in the data set, as opposed to one single rate applied uniformly to all characters.
Figure 5.
The effects of missing data vary with the rate of character evolution.
This figure compares the effect of deleting one-third of the characters from three different rate classes. (A) Comparisons of Bayesian-Mk analyses. (B) Comparisons of parsimony analyses.
Figure 6.
Comparison of 350- and 1000-character data sets.