add_effect_diagnostic |
Add an additional diagnostic to the effect model |
add_effect_model |
Add an additional model to the joint effect ensemble |
add_known_propensity_score |
Uses a known propensity score |
add_moderator |
Adds moderators to the configuration |
add_outcome_diagnostic |
Add an additional diagnostic to the outcome model |
add_outcome_model |
Add an additional model to the outcome ensemble |
add_propensity_diagnostic |
Add an additional diagnostic to the propensity score |
add_propensity_score_model |
Add an additional model to the propensity score ensemble |
add_vimp |
Adds variable importance information |
attach_config |
Attach an 'HTE_cfg' to a dataframe |
basic_config |
Create a basic config for HTE estimation |
Constant_cfg |
Configuration of a Constant Estimator |
construct_pseudo_outcomes |
Construct Pseudo-outcomes |
Diagnostics_cfg |
Configuration of Model Diagnostics |
estimate_QoI |
Estimate Quantities of Interest |
HTE_cfg |
Configuration of Quantities of Interest |
KernelSmooth_cfg |
Configuration for a Kernel Smoother |
Known_cfg |
Configuration of Known Model |
make_splits |
Define splits for cross-fitting |
MCATE_cfg |
Configuration of Marginal CATEs |
Model_cfg |
Base Class of Model Configurations |
Model_data |
R6 class to represent data to be used in estimating a model |
predict.SL.glmnet.interaction |
Prediction for an SL.glmnet object |
produce_plugin_estimates |
Estimate models of nuisance functions |
QoI_cfg |
Configuration of Quantities of Interest |
remove_vimp |
Removes variable importance information |
SL.glmnet.interaction |
Elastic net regression with pairwise interactions |
SLEnsemble_cfg |
Configuration for a SuperLearner Ensemble |
SLLearner_cfg |
Configuration of SuperLearner Submodel |
Stratified_cfg |
Configuration for a Stratification Estimator |
VIMP_cfg |
Configuration of Variable Importance |