ame() and lame() produce a posterior sample, not a maximum-
likelihood point. A pointwise log-likelihood is computable from the
posterior draws but is not stored on the fit object, so logLik()
(and the AIC / BIC generics that dispatch through it) error out
informatively rather than return a misleading number.
# S3 method for ame
logLik(object, ...)# S3 method for lame
logLik(object, ...)
Never returns; raises an error.
an ame or lame fit.
ignored.
For Bayesian model comparison use posterior-predictive checks via
gof / gof_plot, or compute WAIC / LOO yourself
from the per-draw log-likelihoods (e.g. via the loo package on the
BETA / VC chains).