% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cr_components.R
\name{CR_FunctionCombiner}
\alias{CR_FunctionCombiner}
\title{Competing Risk Function Combiner}
\usage{
CR_FunctionCombiner(events, times = NULL)
}
\arguments{
\item{events}{A vector of integers specifying which competing risks event
functions should be processed. This should correspond to all of the
competing risk events that can occur, from 1 to the largest number.}

\item{times}{An optional numeric vector that forces the output functions to
only update at these time points. Pre-specifying the values can result in
faster performance when predicting, however if the times are not exhaustive
then the resulting curves will not update at that point (they'll be flat).
If left blank, the package will default to using all of the time points.}
}
\description{
Creates a CompetingRiskFunctionCombiner rJava object, which is used
internally for constructing a forest. The forest uses it when creating
predictions to average the cumulative incidence curves, cause-specific
cumulative hazard functions, and Kaplan-Meier curves generated by each tree
into individual functions.
}
\details{
The user only needs to pass this object into \code{\link{train}} as the
\code{forestResponseCombiner} parameter.
}
\examples{
T1 <- rexp(1000)
T2 <- rweibull(1000, 1, 2)
C <- rexp(1000)

u <- round(pmin(T1, T2, C))
# ...

forestCombiner <- CR_FunctionCombiner(1:2) # there are two possible events
# or, since we know that u is always an integer
forestCombiner <- CR_FunctionCombiner(1:2, 0:max(u))
}