randomForestSRC survival backend

Wrappers for random survival forests fitted with randomForestSRC.

Usage

fit.rfsrc(response, x, cplx, ...)
complexity.oob.rfsrc(response, x, full.data,
    mtry = unique(pmax(1L, c(floor(sqrt(ncol(x))), floor(ncol(x)/3), ncol(x)))),
    nodesize = c(5L, 15L), ntree = 200L, ...)
# S3 method for class 'rfsrc'
predictProb(object, response, x, times, complexity = NULL, ...)

Arguments

response

survival response as a Surv object or a two-column time/status matrix.

x

covariate matrix.

cplx

either a selected mtry value or a named list such as list(mtry = ..., nodesize = ...).

full.data

full data frame, accepted for the peperr complexity-function contract.

mtry

candidate mtry values for OOB tuning.

nodesize

candidate terminal-node sizes for OOB tuning.

ntree

number of trees used during OOB tuning.

object

a fitted rfsrc object.

times

evaluation times for survival probabilities.

complexity

unused for fitted forests; included for interface compatibility.

...

additional arguments passed to rfsrc or predict.rfsrc.

Value

Fitted rfsrc objects, tuning lists containing mtry and nodesize, and survival-probability matrices.

Details

No PLL.rfsrc method is provided, because random survival forests do not naturally expose a Cox-style partial likelihood. They can still be used with pmpec through predictProb.rfsrc.

See also

peperr, rfsrc, predict.rfsrc