attentionrct            Payday cognitive attention experiment
average_treatment_effect
                        Get doubly robust estimates of average
                        treatment effects.
best_linear_projection
                        Estimate the best linear projection of a
                        conditional average treatment effect.
boosted_regression_forest
                        Boosted regression forest
causal_forest           Causal forest
causal_survival_forest
                        Causal survival forest
generate_causal_data    Generate causal forest data
generate_causal_survival_data
                        Simulate causal survival data
get_forest_weights      Given a trained forest and test data, compute
                        the kernel weights for each test point.
get_leaf_node           Find the leaf node for a test sample.
get_scores              Compute doubly robust scores for a GRF forest
                        object
get_scores.causal_forest
                        Compute doubly robust scores for a causal
                        forest.
get_scores.causal_survival_forest
                        Compute doubly robust scores for a causal
                        survival forest.
get_scores.instrumental_forest
                        Doubly robust scores for estimating the average
                        conditional local average treatment effect.
get_scores.multi_arm_causal_forest
                        Compute doubly robust scores for a multi arm
                        causal forest.
get_tree                Retrieve a single tree from a trained forest
                        object.
grf_options             grf package options
instrumental_forest     Intrumental forest
ll_regression_forest    Local linear forest
lm_forest               LM Forest
merge_forests           Merges a list of forests that were grown using
                        the same data into one large forest.
multi_arm_causal_forest
                        Multi-arm/multi-outcome causal forest
multi_regression_forest
                        Multi-task regression forest
plot.grf_tree           Plot a GRF tree object.
plot.rank_average_treatment_effect
                        Plot the Targeting Operator Characteristic
                        curve.
predict.boosted_regression_forest
                        Predict with a boosted regression forest.
predict.causal_forest   Predict with a causal forest
predict.causal_survival_forest
                        Predict with a causal survival forest forest
predict.instrumental_forest
                        Predict with an instrumental forest
predict.ll_regression_forest
                        Predict with a local linear forest
predict.lm_forest       Predict with a lm forest
predict.multi_arm_causal_forest
                        Predict with a multi arm causal forest
predict.multi_regression_forest
                        Predict with a multi regression forest
predict.probability_forest
                        Predict with a probability forest
predict.quantile_forest
                        Predict with a quantile forest
predict.regression_forest
                        Predict with a regression forest
predict.survival_forest
                        Predict with a survival forest
print.boosted_regression_forest
                        Print a boosted regression forest
print.grf               Print a GRF forest object.
print.grf_tree          Print a GRF tree object.
print.rank_average_treatment_effect
                        Print the Rank-Weighted Average Treatment
                        Effect (RATE).
print.tuning_output     Print tuning output. Displays average error for
                        q-quantiles of tuned parameters.
probability_forest      Probability forest
quantile_forest         Quantile forest
rank_average_treatment_effect
                        Estimate a Rank-Weighted Average Treatment
                        Effect (RATE).
rank_average_treatment_effect.fit
                        Fitter function for Rank-Weighted Average
                        Treatment Effect (RATE).
regression_forest       Regression forest
schoolrct               Brazilian high school financial education RCT
split_frequencies       Calculate which features the forest split on at
                        each depth.
survival_forest         Survival forest
test_calibration        Omnibus evaluation of the quality of the random
                        forest estimates via calibration.
variable_importance     Calculate a simple measure of 'importance' for
                        each feature.
