This vignette briefly demonstrates multiple features of babette
, without going into much detail.
First, load the library:
This vignette shows how to:
babette
run ‘BEAST2’In all cases, this is done for a short MCMC chain length of 10K:
Also, in all cases, we use the same BEAST2 options:
babette
run ‘BEAST2’For an alignment, we’ll use a babette
example alignment.
Effective sample sizes, with 20% burn-in removed:
if (is_beast2_installed()) {
traces <- remove_burn_ins(
traces = out$estimates,
burn_in_fraction = 0.2
)
esses <- t(
calc_esses(
traces,
sample_interval = inference_model$mcmc$tracelog$log_every
)
)
colnames(esses) <- "ESS"
knitr::kable(esses)
}
For a reliable inference, use an ESS of at least 200.