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orf  

Ordered Random Forests
View on CRAN: Click here


Download and install orf package within the R console
Install from CRAN:
install.packages("orf")

Install from Github:
library("remotes")
install_github("cran/orf")

Install by package version:
library("remotes")
install_version("orf", "0.1.4")



Attach the package and use:
library("orf")
Maintained by
Gabriel Okasa
[Scholar Profile | Author Map]
First Published: 2019-11-30
Latest Update: 2022-07-23
Description:
An implementation of the Ordered Forest estimator as developed in Lechner & Okasa (2019) . 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) .
How to cite:
Gabriel Okasa (2019). orf: Ordered Random Forests. R package version 0.1.4, https://cran.r-project.org/web/packages/orf. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.2 (2019-11-30 11:00), 0.1.3 (2020-01-31 12:40)
Other packages that cited orf R package
View orf citation profile
Other R packages that orf depends, imports, suggests or enhances
Complete documentation for orf
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