Man pages for CRE
Interpretable Discovery and Inference of Heterogeneous Treatment Effects

autoplot.creA helper function for cre object
check_hyper_paramsCheck input parameters
check_input_dataCheck input data
check_method_paramsCheck method-related parameters
creCausal rule ensemble
CRE-packageThe CRE package
discover_rulesDiscover rules
estimate_cateEstimate the Conditional Average Treatment Effect
estimate_iteEstimate the Individual Treatment Effect (ITE)
estimate_ite_aipwEstimate the Individual Treatment Effect (ITE) using...
estimate_ite_bartEstimate the Individual Treatment Effect (ITE) using Bayesian...
estimate_ite_cfEstimate the Individual Treatment Effect (ITE) using Causal...
estimate_ite_slearnerEstimate the Individual Treatment Effect (ITE) using...
estimate_ite_tlearnerEstimate the Individual Treatment Effect (ITE) using...
estimate_ite_tpoissonEstimate the Individual Treatment Effect (ITE) using...
estimate_ite_xlearnerEstimate the Individual Treatment Effect (ITE) using...
estimate_psEstimate the propensity score
evaluateDiscovery (performance) evaluation
extract_effect_modifiersExtract effect modifiers
extract_rulesExtract (causal) decision rules
filter_correlated_rulesFilter correlated rules
filter_extreme_rulesFilter extreme decision rules
filter_irrelevant_rulesFilter irrelevant decision rules using leave-one-out pruning
generate_cre_datasetGenerate CRE synthetic data
generate_rulesGenerate rules
generate_rules_matrixGenerate rules matrix
get_loggerGet Logger settings
honest_splittingHonest splitting
interpret_rulesInterpret rules
plot.creExtend generic plot functions for cre class
predict.crePredict individual treatment effect via causal rule ensemble
print.creExtend print function for the CRE object
select_rulesSelect rules
set_loggerSet Logger settings
standardize_rules_matrixStandardize Rules Matrix
summary.crePrint summary of CRE object
CRE documentation built on Oct. 19, 2024, 5:07 p.m.