pense (version 2.5.2)

.run_replicated_cv_ris: Run replicated K-fold CV with random splits, matching the global estimates to the CV estimates by Kendall's tau-b computed on the robustness weights.

Description

Run replicated K-fold CV with random splits, matching the global estimates to the CV estimates by Kendall's tau-b computed on the robustness weights.

Usage

.run_replicated_cv_ris(
  std_data,
  cv_k,
  cv_repl,
  cv_est_fun,
  global_ests,
  min_similarity = 0,
  par_cluster = NULL,
  rho_opts,
  handler_args = list()
)

Arguments

std_data

standardized full data set (standardized by .standardize_data)

cv_k

number of folds per CV split

cv_repl

number of CV replications.

cv_est_fun

function taking the standardized training set and the indices of the left-out observations and returns a list of estimates. The function always needs to return the same number of estimates!

global_ests

estimates computed on all observations.

min_similarity

minimum (average) similarity for CV solutions to be considered (between 0 and 1). If no CV solution satisfies this lower bound, the best CV solution will be used regardless of similarity.

par_cluster

parallel cluster to parallelize computations.

rho_opts

rho function options.

handler_args

additional arguments to the handler function.