The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
The goal of ICcforest is to implement the conditional inference forest approach to modeling interval-censored survival data. It also provides functions to tune the parameters and evaluate the model fit.
You can install the released version of ICcforest from CRAN with:
install.packages("ICcforest")This is a basic example which shows you how to solve a common problem:
## basic example code with miceData
library(ICcforest)
library(survival)
library(icenReg)
#> Loading required package: Rcpp
#> Loading required package: coda
data(miceData)
## For ICcforest to run, Inf should be set to be a large number, for example, 9999999.
idx_inf <- (miceData$u == Inf)
miceData$u[idx_inf] <- 9999999.
## Fit an iterval-censored conditional inference forest
Cforest <- ICcforest(Surv(l, u, type = "interval2") ~ grp, data = miceData)
#> mtry = 1 OOB Brier score = 0.06497173
#> Searching left ...
#> Searching right ...These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.