Randomly partition data into K subsets of equal size (by site). Re-fit the model
K times, each time leaving out one of the subsets. Calculate the log-likelihood
for each of the sites that was left out. This function is an alternative
to loo (leave-one-out cross validation).
# S4 method for class 'ubmsFit'
kfold(x, K = 10, folds = NULL, quiet = FALSE, ...)A ubmsFit model
Number of folds into which the data will be partitioned
An optional vector with length equal to the number of sites in the data and containing integers from 1 to K, to manually assign sites to folds. You should use this if you plan to compare multiple models, since the folds for each model should be identical. You can use loo::kfold_split_random to generate this vector
If TRUE, suppress progress bar
Currently ignored
An object of class elpd_generic that is compatible with loo::loo_compare