  Random forests are a sensible non-parametric model to predict competing risk
data according to some covariates. However, there are currently no packages
that can adequately handle large datasets ($n > 100,000$). We introduce a new R
package, largeRCRF, using the random competing risks forest theory developed by
Ishwaran et al. (2014). We verify our package's validity and accuracy through
simulation studies and show that its results are similar enough to
randomForestSRC while taking less time to run. We also demonstrate the package
on a large dataset that was previously inaccessible, using hardware
requirements that are available to most researchers.
