The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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>.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.4.0) |
| Imports: | Rcpp, Matrix, stats, utils, stringr, orf, glmnet, ranger |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2024-09-25 |
| DOI: | 10.32614/CRAN.package.ocf |
| Author: | Riccardo Di Francesco [aut, cre, cph] |
| Maintainer: | Riccardo Di Francesco <difrancesco.riccardo96 at gmail.com> |
| BugReports: | https://github.com/riccardo-df/ocf/issues |
| License: | GPL-3 |
| URL: | https://riccardo-df.github.io/ocf/, https://github.com/riccardo-df/ocf |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | ocf results |
| Reference manual: | ocf.pdf |
| Vignettes: |
Short Tutorial (source, R code) |
| Package source: | ocf_1.0.1.tar.gz |
| Windows binaries: | r-devel: ocf_1.0.1.zip, r-release: ocf_1.0.1.zip, r-oldrel: ocf_1.0.1.zip |
| macOS binaries: | r-release (arm64): ocf_1.0.1.tgz, r-oldrel (arm64): ocf_1.0.1.tgz, r-release (x86_64): ocf_1.0.1.tgz, r-oldrel (x86_64): ocf_1.0.1.tgz |
| Old sources: | ocf archive |
Please use the canonical form https://CRAN.R-project.org/package=ocf to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.