conditional_means |
Estimate mean rewards mu for each treatment a |
conditional_means.causal_forest |
Estimate mean rewards mu for each treatment a |
conditional_means.causal_survival_forest |
Estimate mean rewards mu for each treatment a |
conditional_means.instrumental_forest |
Estimate mean rewards mu for each treatment a |
conditional_means.multi_arm_causal_forest |
Estimate mean rewards mu for each treatment a |
double_robust_scores |
Matrix Gamma of scores for each treatment a |
double_robust_scores.causal_forest |
Matrix Gamma of scores for each treatment a |
double_robust_scores.causal_survival_forest |
Matrix Gamma of scores for each treatment a |
double_robust_scores.instrumental_forest |
Matrix Gamma of scores for each treatment a |
double_robust_scores.multi_arm_causal_forest |
Matrix Gamma of scores for each treatment a |
gen_data_epl |
Example data generating process from Policy Learning With Observational Data |
gen_data_mapl |
Example data generating process from Offline Multi-Action Policy Learning: Generalization and Optimization |
hybrid_policy_tree |
Hybrid tree search |
multi_causal_forest |
(deprecated) One vs. all causal forest for multiple treatment effect estimation |
plot.policy_tree |
Plot a policy_tree tree object. |
policy_tree |
Fit a policy with exact tree search |
predict.policy_tree |
Predict method for policy_tree |
print.policy_tree |
Print a policy_tree object. |