think it would be useful to do (and perhaps include as SI) a small simulation that showed the method did not generate bias in the fit of trait models. Something like
library(diversitree)
## Simulate a total tree and data on it
t <- tree.bd(c(1,0), max.taxa=1000)
d <- sim.character(t, 1)
## Subsample both tree and data
t <- drop.tip(t, sample(t$tip.label, runif(500,900))
d <- d[sample(t$tip.label, runif(100,900)]
l <- make.bm(t,d)
f <- find.mle(l,1)
think it would be useful to do (and perhaps include as SI) a small simulation that showed the method did not generate bias in the fit of trait models. Something like