## Not run:
# ## Examples from RFSRC package...
# ## ------------------------------------------------------------
# ## classification example
# ## ------------------------------------------------------------
# ## -------- iris data
# ## You can build a randomForest
# # rfsrc_iris <- rfsrc(Species ~ ., data = iris)
# # varsel_iris <- var.select(rfsrc_iris)
# # ... or load a cached randomForestSRC object
# data(varsel_iris, package="ggRandomForests")
#
# # Get a data.frame containing minimaldepth measures
# gg_dta<- gg_minimal_vimp(varsel_iris)
#
# # Plot the gg_minimal_depth object
# plot(gg_dta)
#
# ## ------------------------------------------------------------
# ## Regression example
# ## ------------------------------------------------------------
# ## -------- air quality data
# rfsrc_airq <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")
# varsel_airq <- var.select(rfsrc_airq)
#
# # Get a data.frame containing error rates
# gg_dta<- gg_minimal_vimp(varsel_airq)
#
# # Plot the gg_minimal_vimp object
# plot(gg_dta)
#
# ## -------- Boston data
# data(varsel_Boston, package="ggRandomForests")
#
# # Get a data.frame containing error rates
# gg_dta<- gg_minimal_vimp(varsel_Boston)
#
# # Plot the gg_minimal_vimp object
# plot(gg_dta)
#
# ## -------- mtcars data
# data(varsel_mtcars, package="ggRandomForests")
#
# # Get a data.frame containing error rates
# gg_dta<- gg_minimal_vimp(varsel_mtcars)
#
# # Plot the gg_minimal_vimp object
# plot(gg_dta)
#
# ## ------------------------------------------------------------
# ## Survival example
# ## ------------------------------------------------------------
# ## -------- veteran data
# ## randomized trial of two treatment regimens for lung cancer
# # data(veteran, package = "randomForestSRC")
# # rfsrc_veteran <- rfsrc(Surv(time, status) ~ ., data = veteran, ntree = 100)
# # varsel_veteran <- var.select(rfsrc_veteran)
# # Load a cached randomForestSRC object
# data(varsel_veteran, package="ggRandomForests")
#
# gg_dta <- gg_minimal_vimp(varsel_veteran)
# plot(gg_dta)
#
# ## -------- pbc data
# data(varsel_pbc, package="ggRandomForests")
#
# gg_dta <- gg_minimal_vimp(varsel_pbc)
# plot(gg_dta)
# ## End(Not run)
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