Wrapper function for Random Survival Forests (RFSRC)

Final Production Wrapper for RFSRC (Tunable & Robust). Estimates a survival random forest using rfsrc.

Usage

surv.rfsrc(
  time,
  event,
  X,
  newdata = NULL,
  new.times,
  obsWeights = NULL,
  id = NULL,
  ntree = 1000,
  nodesize = 15,
  mtry = NULL,
  ...
)

Arguments

time: Observed follow-up time.
event: Observed event indicator.
X: Training covariate data.frame.
newdata: Test covariate data.frame to use for prediction.
new.times: Times at which to obtain the predicted survivals.
obsWeights: Observation weights.
id: Currently ignored.
ntree: Number of trees to grow (default: 1000).
nodesize: Minimum number of deaths in terminal nodes (default: 15).
mtry: Number of variables randomly selected as candidates for splitting a node.
...: Additional arguments passed to rfsrc.

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("randomForestSRC", 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.rfsrc(
    time = dat$duration,
    event = dat$event,
    X = X,
    newdata = newX,
    new.times = times,
    ntree = 10,
    nodesize = 3
  )

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