Reference

All functions
abalone	Abalone (regression practice data)
ate()	Average treatment effect of a fitted CATE model
ate_dml()	Double machine learning (DML) ATE estimator
ate_dr()	Doubly robust (AIPW) ATE estimator
ate_ipw()	Inverse propensity weighting (IPW) ATE estimator
ate_naive()	Naive ATE estimator (difference in means)
cate_ci()	Bootstrap confidence intervals for predicted CATEs
diabetes	Pima Indians diabetes (classification practice data)
dr_learner() predict(<dr_learner>)	DR-Learner for CATE estimation
eps_ate()	Absolute error of an ATE estimate
housing	Boston housing (regression practice data)
ihdp_test	IHDP semi-synthetic benchmark (test set)
ihdp_train	IHDP semi-synthetic benchmark (training set)
jobs_test	Jobs benchmark (test set)
jobs_train	Jobs benchmark (training set)
pehe()	Precision in estimation of heterogeneous effects (PEHE)
r_learner() predict(<r_learner>)	R-Learner for CATE estimation
r_loss()	R-Loss: an observable score for CATE models
rloss_nuisance()	Nuisance models for the R-Loss
s_learner() predict(<s_learner>)	S-Learner for CATE estimation
sodium	Sodium intake and blood pressure (synthetic)
spirals	Spirals (classification practice data)
synth_test	Synthetic CATE benchmark (test set)
synth_train	Synthetic CATE benchmark (training set)
t_learner() predict(<t_learner>)	T-Learner for CATE estimation
x_learner() predict(<x_learner>)	X-Learner for CATE estimation