opl_dt_c {OPL}R Documentation

Optimal Policy Learning with Decision Tree

Description

Implementing ex-ante treatment assignment using as policy class a 2-layer fixed-depth decision-tree at specific splitting variables and threshold values.

Usage

opl_dt_c(make_cate_result, z, w, c1 = NA, c2 = NA, c3 = NA, verbose = TRUE)

Arguments

make_cate_result

A data frame resulting from the make_cate function, containing the predicted treatment effects (my_cate) and other variables for treatment assignment.

z

A character vector containing the names of the variables used for treatment assignment.

w

A string representing the treatment indicator variable name.

c1

Value of the threshold value c1 for the first splitting variable. This number must be chosen between 0 and 1.

c2

Value of the threshold value c2 for the second splitting variable. This number must be chosen between 0 and 1.

c3

Value of the threshold value c3 for the third splitting variable. This number must be chosen between 0 and 1.

verbose

Set TRUE to print the output on the console.

Value

A list containing:

References


[Package OPL version 1.0.2 Index]