Run k-fold cross-validation — kfold.ermod • BayesERtools

This function performs k-fold cross-validation using the appropriate model development function based on the class of the ermod object. It is internally used by eval_ermod(). The output is compatible with loo ecosystem, e.g. it can be used for loo::loo_compare() function. See loo::kfold() for details.

Usage

# S3 method for class 'ermod'
kfold(x, k = 5, newdata = NULL, seed = NULL, ...)

kfold(x, ...)

extract_kfold_loo(kfold_ermod)

Arguments

x: An ermod object containing the model and data.
k: The number of folds for cross-validation. Default is 5.
newdata: Optional new dataset to use instead of the original data. Default is NULL.
seed: Random seed for reproducibility. Default is NULL.
...: Currently not used.
kfold_ermod: An object of class kfold_ermod from kfold()

Value

kfold() returns kfold_ermod class object containing the fitted models and holdout predictions for each fold.

extract_kfold_loo() returns c("kfold", "loo") class object that works well with loo ecosystem

Examples

# \donttest{
data(d_sim_binom_cov_hgly2)

ermod_bin <- dev_ermod_bin(
  data = d_sim_binom_cov_hgly2,
  var_resp = "AEFLAG",
  var_exposure = "AUCss_1000",
  var_cov = "BHBA1C_5",
  # Settings to make the example run faster
  chains = 2,
  iter = 1000
)

cv_results <- kfold(ermod_bin, k = 3, seed = 123)

print(cv_results)
#> 
#> ── k-fold Cross-Validation for ermod object ────────────────────────────────────
#> ℹ Number of folds:  3
#> 
#> ── Structure of the object ──
#> 
#> • $l_ermod: list of ermod objects
#> • $d_truth: data frame with true response values
#> • $d_sim: data frame with holdout predictions
#> 
#> ── elpd (used in `loo` package) ──
#> 
#>            Estimate   SE
#> elpd_kfold   -254.5 12.2
#> p_kfold         4.9  1.4
#> kfoldic       509.0 24.3
# }