Widely Application Information Criteria (WAIC) for model comparison
waic(fit, pointwise = FALSE, digits = 2)
Watanabe, S. (2010). Asymptotic equivalence of Bayes cross validation and widely application information criterion in singular learning theory. Journal of Machine Learning Research 11, 3571-3594.
geostan_fit object or any Stan model with a parameter named "log_lik", the pointwise log likelihood of the observations.
Logical (defaults to
FALSE), should a vector of values for each observation be returned?
Round results to this many digits.
A vector of length 3 with
WAIC, a rough measure of the effective number of parameters estimated by the model
Eff_pars, and log predictive density
pointwise = TRUE, results are returned in a