Compute LOOIC (leave-one-out cross-validation (LOO) information criterion) and ELPD (expected log predictive density) for Bayesian regressions. For LOOIC and ELPD, smaller and larger values are respectively indicative of a better fit.
looic(model, verbose =TRUE)
Arguments
model: A Bayesian regression model.
verbose: Toggle off warnings.
Returns
A list with four elements, the ELPD, LOOIC and their standard errors.
Examples
model <- suppressWarnings(rstanarm::stan_glm( mpg ~ wt + cyl, data = mtcars, chains =1, iter =500, refresh =0))looic(model)