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.
<- (miceData$u == Inf)
idx_inf $u[idx_inf] <- 9999999.
miceData
## Fit an iterval-censored conditional inference forest
<- ICcforest(Surv(l, u, type = "interval2") ~ grp, data = miceData)
Cforest #> mtry = 1 OOB Brier score = 0.06497173
#> Searching left ...
#> Searching right ...
```