Optimal_Rule_Q_learning: Learns the Optimal Rule given a tmle_task and likelihood,...

In tlverse/tmle3mopttx: Targeted Maximum Likelihood Estimation of the Mean under Optimal Individualized Treatment

Learns the Optimal Rule given a tmle_task and likelihood, using Q learning.

Description

Learns the Optimal Rule given a tmle_task and likelihood, using Q learning.

Learns the Optimal Rule given a tmle_task and likelihood, using Q learning.

Super class

tmle3::tmle3_Spec -> Optimal_Rule_Q_learning

Methods

Public methods

• Optimal_Rule_Q_learning$new()

• Optimal_Rule_Q_learning$fit_blip()

• Optimal_Rule_Q_learning$rule()

• Optimal_Rule_Q_learning$clone()

Inherited methods

• tmle3::tmle3_Spec$make_initial_likelihood()
• tmle3::tmle3_Spec$make_params()
• tmle3::tmle3_Spec$make_targeted_likelihood()
• tmle3::tmle3_Spec$make_tmle_task()
• tmle3::tmle3_Spec$make_updater()

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Method new()

Usage

Optimal_Rule_Q_learning$new(tmle_task, likelihood, maximize = TRUE)

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Method fit_blip()

Usage

Optimal_Rule_Q_learning$fit_blip()

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Method rule()

Usage

Optimal_Rule_Q_learning$rule(tmle_task, fold_number = "full")

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Method clone()

The objects of this class are cloneable with this method.

Usage

Optimal_Rule_Q_learning$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

tlverse/tmle3mopttx documentation built on Aug. 9, 2022, 3:31 p.m.