cv.big_pls_cox: Cross-validation for big-memory PLS-Cox models

Description

Performs K-fold cross-validation for models fitted with big_pls_cox() or big_pls_cox_gd(). The routine mirrors the behaviour of the cross-validation helpers available in the original plsRcox package while operating on big.matrix inputs.

Usage

cv.big_pls_cox(
  data,
  nfold = 5L,
  nt = 5L,
  keepX = NULL,
  givefold,
  allCVcrit = FALSE,
  times.auc = NULL,
  times.prederr = NULL,
  method = c("efron", "breslow"),
  verbose = TRUE,
  ...
)
cv.big_pls_cox_gd(
  data,
  nfold = 5L,
  nt = NULL,
  keepX = NULL,
  givefold,
  allCVcrit = FALSE,
  times.auc = NULL,
  times.prederr = NULL,
  method = c("efron", "breslow"),
  verbose = TRUE,
  ...
)

Value

A list containing cross-validation summaries. When allCVcrit = FALSE, the list holds

nt: Number of components assessed.
cv.error10: Mean iAUC of survivalROC across folds for 0 to nt components.
cv.se10: Estimated standard errors for cv.error10.
folds: Fold assignments.
lambda.min10: Component minimising the cross-validated error.
lambda.1se10: Largest component within one standard error of the optimum.

When allCVcrit = TRUE, the full set of 14 criteria (log partial likelihood, iAUC variants and Brier scores) is returned together with their associated standard errors and one-standard-error selections.

Arguments

data: A list with entries x, time and status matching the arguments of big_pls_cox() or big_pls_cox_gd(). x can be either a numeric matrix/data frame or a bigmemory::big.matrix.
nfold: Integer giving the number of folds to use.
nt: Number of latent components to evaluate.
keepX: Optional integer vector passed to the modelling function to enforce naive sparsity (see big_pls_cox()).
givefold: Optional list of fold indices. When supplied, it must contain nfold integer vectors whose union is seq_len(nrow(data$x)).
allCVcrit: Logical; when FALSE (default) only the recommended integrated AUC computed with survivalROC is returned. When TRUE, the 13 additional criteria from plsRcox are also evaluated.
times.auc: Optional time grid used for time-dependent AUC computations. Defaults to an equally spaced grid between zero and the maximum observed time.
times.prederr: Optional time grid used for prediction error curves. Defaults to the same grid as times.auc without the last ten evaluation points to avoid instabilities.
method: Ties handling method passed to survival::coxph.
verbose: Logical; print progress information.
...: Additional arguments forwarded to the underlying modelling function.

Details

The function returns cross-validated estimates for each component (including the null model) using either big_pls_cox() or big_pls_cox_gd(), depending on the engine argument. The implementation reuses the internal indicators (getIndicCV, getIndicCViAUCSurvROCTest) to provide consistent metrics with the legacy plsRcox helpers.