orf - Ordered Random Forests
An implementation of the Ordered Forest estimator as
developed in Lechner & Okasa (2019) <arXiv:1907.02436>. The
Ordered Forest flexibly estimates the conditional probabilities
of models with ordered categorical outcomes (so-called ordered
choice models). Additionally to common machine learning
algorithms the 'orf' package provides functions for estimating
marginal effects as well as statistical inference thereof and
thus provides similar output as in standard econometric models
for ordered choice. The core forest algorithm relies on the
fast C++ forest implementation from the 'ranger' package
(Wright & Ziegler, 2017) <arXiv:1508.04409>.
