Repeated cross-validation for predictive assessment — evaluate_prediction

Repeats V-fold cross-validation for a fixed SDR and covariance-estimator combination. Failed folds are retained with diagnostic messages.

Usage

evaluate_prediction_cv(
  X,
  y,
  sdr_method = c("dr", "sir", "save", "phd"),
  cov_method = c("sample", "ridge", "oas", "lw", "mec"),
  d,
  v = 5,
  repeats = 10,
  nslices = 6,
  standardize = TRUE,
  stabilize = TRUE,
  stabilization = c("eigenfloor", "ridge", "nearest_pd"),
  seed = NULL,
  cov_args = list(),
  stabilization_args = list(),
  sdr_args = list(),
  ...
)

Arguments

X: Numeric predictor matrix or data frame.
y: Numeric continuous response vector.
sdr_method: SDR method.
cov_method: Covariance estimator.
d: Fixed structural dimension.
v: Number of folds.
repeats: Number of cross-validation repetitions.
nslices: Number of response slices.
standardize: Logical. Standardise within each training fold.
stabilize: Logical. Stabilise the estimated covariance matrix.
stabilization: Covariance stabilisation method.
seed: Optional random seed.
cov_args: Named list of covariance-estimator arguments.
stabilization_args: Named list of stabilisation arguments.
sdr_args: Named list of SDR-kernel arguments.
...: Backward-compatible component arguments.

Value

A list containing a one-row summary and fold-level results.