resampling: Resampling specifications for evaluate(), tune() and...

In survalis: Interpretable Survival Machine Learning Framework

Resampling specifications for evaluate(), tune() and compare()

Description

These constructors return a lightweight survalis_resampling description that the verb-level functions turn into concrete train/test splits. They do not touch the data themselves, so the same specification can be reused across models to obtain paired comparisons (identical folds via a shared seed).

Usage

cv(v = 5, repeats = 1, strata = "status", seed = NULL)

holdout(prop = 0.75, strata = "status", seed = NULL)

groupcv(group, v = 5, seed = NULL)

bootstrap(times = 25, seed = NULL)

Arguments

v	Integer number of folds (default 5).
repeats	Integer number of times the whole v-fold scheme is repeated with fresh random folds (default 1).
strata	Column name to stratify on, or NA to disable stratification. The default sentinel "status" means "use the event-indicator column of the model formula", whatever its name (for example cens in Surv(time, cens) ~ .). Any other name must be a column of the data; otherwise a warning is given and the resampling is not stratified.
seed	Optional integer seed. Set it (and keep it equal across models) for paired resampling.
prop	Proportion of rows assigned to the training set in holdout() (default 0.75).
group	Column name whose distinct values define the groups held out together in groupcv().
times	Integer number of bootstrap resamples (default 25).

Details

• cv() – k-fold cross-validation, optionally repeated, stratified on the event indicator by default.

• holdout() – a single stratified train/test split.

• groupcv() – k-fold cross-validation where whole groups (e.g. centres, subjects with repeated rows) are held out together.

• bootstrap() – resampling with replacement; the out-of-bag rows form the assessment set (Efron-Tibshirani style, suitable for .632 reporting).

Value

An object of class survalis_resampling.

Examples

cv(5)
cv(v = 10, repeats = 3, seed = 1)
holdout(prop = 0.8)
bootstrap(times = 50)

survalis documentation built on Nov. 14, 2026, 5:10 p.m.