Function returning the Watanabe-Akaike Information Criterion (WAIC) of a fitted model object.
WAIC(object, ..., newdata = NULL)
A fitted model object which contains MCMC samples.
Optionally more fitted model objects.
Optionally, use new data for computing the WAIC.
A data frame containing the WAIC and estimated number of parameters.
Watanabe S. (2010). Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory. The Journal of Machine Learning Research, 11, 3571--3594. https://jmlr.org/papers/v11/watanabe10a.html