The 'X_RF' object is X-learner combined with honest random forest used for the propensity score estimate, the first stage and the second stage.

`feature_train`

A data frame of all training features.

`tr_train`

A vector contain 0 for control and 1 for treated variables.

`yobs_train`

A vector containing the observed outcomes.

`m_0`

contains an honest random forest predictor for the control group of the first stage.

`m_1`

contains an honest random forest predictor for the treated group of the first stage.

`m_tau_0`

contains an honest random forest predictor for the control group of the second stage.

`m_tau_1`

contains an honest random forest predictor for the treated group of the second stage.

`m_prop`

contains an honest random forest predictor the propensity score.

`relevant_Variable_first`

contains the indices of variables, which are only used in the first stage.

`relevant_Variable_second`

contains the numbers of variables, which are only used in the second stage.

soerenkuenzel/hte documentation built on June 12, 2018, 4:26 p.m.

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