Log-likelihood is not directly exposed for ame() / lame() fits

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.

Usage

# S3 method for class 'ame'
logLik(object, ...)

# S3 method for class 'lame'
logLik(object, ...)

Arguments

object

an ame or lame fit.

...

ignored.

Value

Never returns; raises an error.

Details

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).