causalTreeIntermediate function for causalTree
causalTree.control(
minsplit = 20L,
minbucket = round(minsplit/3),
cp = 0,
maxcompete = 4L,
maxsurrogate = 5L,
usesurrogate = 2L,
xval = 10L,
surrogatestyle = 0L,
maxdepth = 30L,
...
)parameters used to in causalTree
minimum number of splits
minimum number of bucket
default is 0
maximum number of compete
maximum number of surrogate
initial number of surrogate
cross-validation
the style of surrogate
Maximum depth
arguments to rpart.control may also be
specified in the call to causalTree. They are checked against the
list of valid arguments. An example of a commonly set parameter would
be xval, which sets the number of cross-validation samples.
The parameter minsize is implemented differently in
causalTree than in rpart; we require a minimum of minsize
treated observations and a minimum of minsize control
observations in each leaf.