print.boosted_regression_forest

<p>Additional arguments (currently ignored).</p>

A pluggable package for forest-based statistical estimation and inference.
GRF currently provides methods for non-parametric least-squares regression,
quantile regression, survival regression and treatment effect estimation (optionally using instrumental
variables), with support for missing values.

Julie Tibshirani

Generalized Random Forests

Susan Athey

Rina Friedberg

Vitor Hadad

David Hirshberg

Luke Miner

Erik Sverdrup

Stefan Wager

Marvin Wright

print.boosted_regression_forest function

Print a boosted regression forest — print.boosted_regression_forest

Print a boosted regression forest

print.boosted_regression_forest: Print a boosted regression forest

Description

Usage

Arguments