pod.bootstrap_pod_ci

bootstrap_pod_ci(
    X,
    y,
    X_eval,
    threshold,
    model_type,
    model_params,
    bandwidth,
    dist_info,
    n_boot=1000,
    nuisance_ranges=None,
    n_jobs=None,
    feature_names=None,
    poi_names=None,
    confidence_levels=None,
    nuisance_dists=None,
    progress_callback=None,
    n_mc_samples=500,
)

Estimates Confidence Bounds for the PoD curve via Bootstrapping.

This function resamples the original data with replacement n_boot times. For each resample, it refits the Mean Model (dynamically rebuilding either a Polynomial or Kriging model), recalculates residuals, and generates a new PoD curve. If Kriging is selected, the optimizer is disabled during bootstrapping to remain computationally tractable.