59 lines
2.2 KiB
R
59 lines
2.2 KiB
R
% Generated by roxygen2: do not edit by hand
|
||
% Please edit documentation in R/cr_components.R
|
||
\name{CompetingRiskSplitFinders}
|
||
\alias{CompetingRiskSplitFinders}
|
||
\alias{GrayLogRankSplitFinder}
|
||
\alias{LogRankSplitFinder}
|
||
\title{Competing Risk Split Finders}
|
||
\usage{
|
||
GrayLogRankSplitFinder(events, eventsOfFocus = NULL)
|
||
|
||
LogRankSplitFinder(events, eventsOfFocus = NULL)
|
||
}
|
||
\arguments{
|
||
\item{events}{A vector of integers specifying which competing risk events
|
||
should be focused on when determining differences. Currently, equal weights
|
||
will be assigned to all included groups.}
|
||
|
||
\item{eventsOfFocus}{The split finder will only maximize differences
|
||
between the two groups with respect to these specified events. Default is
|
||
\code{NULL}, which will cause the split finder to focus on all events
|
||
included in \code{events}.}
|
||
}
|
||
\value{
|
||
An internal rJava Java object used in \code{\link{train}}.
|
||
}
|
||
\description{
|
||
Creates a SplitFinder rJava Java object, which is then used internally when
|
||
training a competing risk random forest. The split finder is responsible for
|
||
finding the best split according to the logic of the split finder.
|
||
}
|
||
\details{
|
||
These split finders require that the response be \code{\link{CR_Response}}.
|
||
|
||
The user only needs to pass this object into \code{\link{train}} as the
|
||
\code{splitFinder} parameter.
|
||
|
||
Roughly speaking, the Gray log-rank split finder looks at
|
||
differences between the cumulative incidence functions of the two groups,
|
||
while the plain log-rank split finder look at differences between the
|
||
cause-specific hazard functions. See the references for a more detailed
|
||
discussion.
|
||
}
|
||
\note{
|
||
The Gray log-rank split finder \strong{requires} that the response
|
||
include the censoring time.
|
||
}
|
||
\examples{
|
||
splitFinder <- GrayLogRankSplitFinder(1:2)
|
||
splitFinder <- LogRankSplitFinder(1:2)
|
||
}
|
||
\references{
|
||
Kogalur, U., Ishwaran, H. Random Forests for Survival,
|
||
Regression, and Classification: A Parallel Package for a General
|
||
Implemention of Breiman's Random Forests: Theory and Specifications. URL
|
||
https://kogalur.github.io/randomForestSRC/theory.html#section8.2
|
||
|
||
Ishwaran, H., et. al. (2014) Random survival forests for competing risks,
|
||
Biostatistics (2014), 15, 4, pp. 757–773
|
||
}
|