kfold-ubmsFit-method function

K-fold Cross-validation of a ubmsFit Model

K-fold Cross-validation of a ubmsFit Model

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 signature 'ubmsFit' kfold(x, K = 10, folds = NULL, quiet = FALSE, ...)

Arguments

  • x: A ubmsFit model
  • K: Number of folds into which the data will be partitioned
  • folds: 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
  • quiet: If TRUE, suppress progress bar
  • ...: Currently ignored

Returns

An object of class elpd_generic that is compatible with loo::loo_compare

  • Maintainer: Ken Kellner
  • License: GPL (>= 3)
  • Last published: 2024-10-01