Package: orf
Type: Package
Title: Ordered Random Forests
Version: 0.1.3
Date: 2020-01-31
Author: Gabriel Okasa [aut, cre], Michael Lechner [ctb]
Maintainer: Gabriel Okasa <gabriel.okasa@unisg.ch>
Description: 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>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: ggplot2, ranger, Rcpp, stats, utils, xtable
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
URL: https://github.com/okasag/orf
BugReports: https://github.com/okasag/orf/issues
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-01-31 11:15:34 UTC; okasag
Repository: CRAN
Date/Publication: 2020-01-31 11:40:06 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 13:02:35 UTC; windows
Archs: i386, x64
