Package: ocf
Type: Package
Title: Ordered Correlation Forest
Version: 1.0.1
Authors@R: person("Riccardo", "Di Francesco", email = "difrancesco.riccardo96@gmail.com", role = c("aut", "cre", "cph"))
Description: Machine learning estimator specifically optimized for predictive modeling of ordered non-numeric outcomes. 'ocf' provides forest-based estimation of the 
    conditional choice probabilities and the covariates’ marginal effects. Under an "honesty" condition, the estimates are consistent and asymptotically normal 
    and standard errors can be obtained by leveraging the weight-based representation of the random forest predictions. Please reference the use as Di Francesco (2023)
    <doi:10.48550/arXiv.2309.08755>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.4.0)
Imports: Rcpp, Matrix, stats, utils, stringr, orf, glmnet, ranger
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.2.3
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://riccardo-df.github.io/ocf/,
        https://github.com/riccardo-df/ocf
BugReports: https://github.com/riccardo-df/ocf/issues
Biarch: TRUE
NeedsCompilation: yes
Packaged: 2024-09-25 13:41:42 UTC; riccardo-df
Author: Riccardo Di Francesco [aut, cre, cph]
Maintainer: Riccardo Di Francesco <difrancesco.riccardo96@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-25 23:20:09 UTC
Built: R 4.5.0; x86_64-apple-darwin20; 2025-01-30 21:37:29 UTC; unix
Archs: ocf.so.dSYM
