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>.

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Description file content

Package
orf
Type
Package
Title
Ordered Random Forests
Version
0.1.2
Date
2019-11-22
Author
Gabriel Okasa [aut, cre], Michael Lechner [ctb]
Maintainer
Gabriel Okasa
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) .
License
GPL-3
Encoding
UTF-8
LazyData
true
Depends
R (>= 2.10)
Imports
ggplot2, ranger, Rcpp, stats, utils, xtable
RoxygenNote
6.1.1
Suggests
knitr, rmarkdown, testthat
VignetteBuilder
knitr
URL
BugReports
https://github.com/okasag/orf/issues
LinkingTo
Rcpp
NeedsCompilation
yes
Packaged
2019-11-22 20:49:26 UTC; okasag
Repository
CRAN
Date/Publication
2019-11-30 10:00:05 UTC

install.packages('orf')

0.1.2

15 days ago

https://github.com/okasag/orf

Gabriel Okasa

GPL-3

Depends on

R (>= 2.10)

Imports

ggplot2, ranger, Rcpp, stats, utils, xtable

Suggests

knitr, rmarkdown, testthat

Discussions