tune_causal_forest

Y.hat

W.hat

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

<p>To tune a causal forest, see the function `causal_forest`</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

tune_causal_forest function

Causal forest tuning (removed) — tune_causal_forest

Causal forest tuning (removed)

tune_causal_forest: Causal forest tuning (removed)

Description

Usage

Arguments

Value