Lrnr_crr_DR_nonconvex Class

This class defines an DR meta-learner for the conditional relative average treatment effect (crr).

Format

An R6 class with public methods to initialize the learner, create a regression task, and access the base learner.

Super classes

sl3::Lrnr_base -> hte3::Lrnr_hte -> Lrnr_crr_DR_selector

Methods

Public methods

• Lrnr_crr_DR_selector$new()

• Lrnr_crr_DR_selector$get_pseudo_data()

• Lrnr_crr_DR_selector$clone()

Inherited methods

• sl3::Lrnr_base$assert_trained()
• sl3::Lrnr_base$base_chain()
• sl3::Lrnr_base$base_predict()
• sl3::Lrnr_base$base_train()
• sl3::Lrnr_base$chain()
• sl3::Lrnr_base$custom_chain()
• sl3::Lrnr_base$get_outcome_range()
• sl3::Lrnr_base$get_outcome_type()
• sl3::Lrnr_base$predict()
• sl3::Lrnr_base$predict_fold()
• sl3::Lrnr_base$print()
• sl3::Lrnr_base$process_formula()
• sl3::Lrnr_base$reparameterize()
• sl3::Lrnr_base$retrain()
• sl3::Lrnr_base$sample()
• sl3::Lrnr_base$set_train()
• sl3::Lrnr_base$subset_covariates()
• sl3::Lrnr_base$train()
• sl3::Lrnr_base$train_sublearners()
• hte3::Lrnr_hte$check_treatment_type()
• hte3::Lrnr_hte$get_modifiers()
• hte3::Lrnr_hte$make_metalearner_task()

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Method new()

Usage

Lrnr_crr_DR_selector$new(treatment_level = NULL, control_level = NULL, ...)

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Method get_pseudo_data()

Usage

Lrnr_crr_DR_selector$get_pseudo_data(
  hte3_task,
  treatment_level = NULL,
  control_level = NULL,
  train = TRUE,
  ...
)

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Method clone()

The objects of this class are cloneable with this method.

Usage

Lrnr_crr_DR_selector$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.