Wrapper for AORSF (Oblique Random Survival Forest)

Final Production Wrapper for AORSF (Tunable & Robust).

Usage

surv.aorsf(
  time,
  event,
  X,
  newdata,
  new.times,
  obsWeights,
  id,
  n_tree = 500,
  leaf_min_events = 5,
  mtry = NULL,
  ...
)

Arguments

time: Observed follow-up time; i.e. minimum of the event and censoring times.
event: Observed event indicator; i.e, whether the follow-up time corresponds to an event or censoring.
X: Training covariate data.frame.
newdata: Test covariate data.frame to use for prediction. Should have the same variable names and structure as X.
new.times: Times at which to obtain the predicted survivals.
obsWeights: Observation weights.
id: Optional cluster/individual ID indicator.
n_tree: Number of trees to grow (default: 500).
leaf_min_events: Minimum number of events in a leaf node (default: 5).
mtry: Number of predictors evaluated at each node.
...: Additional arguments passed to orsf.

Value

A list containing:

fit: The fitted model object (e.g., the raw coxph or xgb.Booster object). If the model fails to fit, this may be an object of class try-error.
pred: A numeric matrix of cross-validated survival predictions evaluated at the specified new.times grid.

Examples

if (requireNamespace("aorsf", quietly = TRUE)) {
  data("metabric", package = "SuperSurv")
  dat <- metabric[1:30, ]
  x_cols <- grep("^x", names(dat))[1:3]
  X <- dat[, x_cols, drop = FALSE]
  newX <- X[1:5, , drop = FALSE]
  times <- seq(50, 150, by = 50)

  fit <- surv.aorsf(
    time = dat$duration,
    event = dat$event,
    X = X,
    newdata = newX,
    new.times = times,
    obsWeights = rep(1, nrow(dat)),
    id = NULL,
    n_tree = 10,
    leaf_min_events = 2
  )

  dim(fit$pred)
}
#> [1] 5 3