# Distributional Random Forests

## Documentation for package ‘drf’ version 1.3.1

- DESCRIPTION file.

## Help Pages

drf | Distributional Random Forests
get_sample_weights | Given a trained forest and test data, compute the training sample weights for each test point.
get_tree | Retrieve a single tree from a trained forest object.
leaf_stats.default | A default leaf_stats for forests classes without a leaf_stats method that always returns NULL.
leaf_stats.drf | Calculate summary stats given a set of samples for regression forests.
medianHeuristic | Compute the median heuristic for the MMD bandwidth choice
plot.drf_tree | Plot a DRF tree object.
predict.drf | Predict from Distributional Random Forests object
print.drf | Print a DRF forest object.
print.drf_tree | Print a DRF tree object.
split_frequencies | Calculate which features the forest split on at each depth.
variableImportance | Variable importance based on MMD
variable_importance | Calculate a simple measure of 'importance' for each feature.
weighted.quantile | Weighted quantiles