predict.orsf: Compute predictions using an oblique random survival forest.

In obliqueRSF: Oblique Random Forests for Right-Censored Time-to-Event Data

Compute predictions using an oblique random survival forest.

Description

Compute predictions using an oblique random survival forest.

Usage

## S3 method for class 'orsf'
predict(object, newdata, times, ...)

Arguments

object	An object fitted using the ORSF function.
newdata	A data frame containing observations to predict.
times	A vector of times in the range of the response variable, e.g. times when the response is a survival object, at which to return the survival probabilities.
...	Other arguments passed to or from other functions.

Value

A matrix of survival probabilities containing 1 row for each observation and 1 column for each value in times.

Examples

data("pbc",package='survival')
pbc$status[pbc$status>=1]=pbc$status[pbc$status>=1]-1
pbc$id=NULL
fctrs<-c('trt','ascites','spiders','edema','hepato','stage')
for(f in fctrs)pbc[[f]]=as.factor(pbc[[f]])
pbc=na.omit(pbc)

orsf=ORSF(data=pbc,ntree=5)
times=seq(365, 365*4,length.out = 10)

predict(orsf,newdata=pbc[c(1:5),],times=times)

obliqueRSF documentation built on Aug. 29, 2022, 1:07 a.m.