causalTree.control: Intermediate function for 'causalTree'

In htetree: Causal Inference with Tree-Based Machine Learning Algorithms

Intermediate function for causalTree

Description

Intermediate function for causalTree

Usage

causalTree.control(
  minsplit = 20L,
  minbucket = round(minsplit/3),
  cp = 0,
  maxcompete = 4L,
  maxsurrogate = 5L,
  usesurrogate = 2L,
  xval = 10L,
  surrogatestyle = 0L,
  maxdepth = 30L,
  ...
)

Arguments

minsplit	minimum number of splits
minbucket	minimum number of bucket
cp	default is 0
maxcompete	maximum number of compete
maxsurrogate	maximum number of surrogate
usesurrogate	initial number of surrogate
xval	cross-validation
surrogatestyle	the style of surrogate
maxdepth	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.

Value

parameters used to in causalTree

htetree documentation built on April 4, 2025, 5:15 a.m.