variable_importance: Computes variable importance measures for a causal forest

In till-tietz/rcf: Heterogenous Treatment Effect Estimation Using Random Forests

Computes variable importance measures for a causal forest

Description

Computes variable importance measures for a causal forest

Usage

variable_importance(cf, covariates, n, d)

Arguments

cf	output of the rcf causal_forest function
covariates	names of predictors used in training the causal forest as character vector
n	maximum tree depth of splits to be considered for variable importance computation
d	decay parameter controlling weighting of splits at different depths for variable importance computation

Value

a data frame of variables and their importance measures

till-tietz/rcf documentation built on May 7, 2023, 10:23 p.m.