Provides fast implementations of Honest Random Forests,
Gradient Boosting, and Linear Random Forests, with an emphasis on inference
and interpretability. Additionally contains methods for variable
importance, out-of-bag prediction, regression monotonicity, and
several methods for missing data imputation. Soren R. Kunzel,
Theo F. Saarinen, Edward W. Liu, Jasjeet S. Sekhon (2019)