# \donttest{
## load the data
data(housing, package = "randomForestSRC")
## the original data contains lots of missing data, so impute it
## use missForest, can be slow so grow trees with small training sizes
housing2 <- impute(data = housing, mf.q = 1, sampsize = function(x){x * .1})
## same idea ... but directly use rfsrc.fast and multivariate missForest
housing3 <- impute(data = housing, mf.q = .5, fast = TRUE)
## even faster, but potentially less acurate
housing4 <- impute(SalePrice~., housing, splitrule = "random", nimpute = 1)
# }
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