Accelerated Oblique Random Forests R package aorsf version 0.1.6 Fit, interpret, and compute predictions with oblique random forests. Includes support for partial dependence, variable importance, passing customized functions for variable importance and identification of linear combinations of features. Methods for the oblique random survival forest are described in Jaeger et al., (2023) <DOI:10.1080/10618600.2023.2231048>. Software Depends: R (>= 3.6) Imports: collapse, data.table, lifecycle, R6, Rcpp, utils LinkingTo: Rcpp, RcppArmadillo Suggests: covr, ggplot2, glmnet, knitr, rmarkdown, survival, SurvMetrics, testthat (>= 3.0.0), tibble, units Byron Jaeger <byron.jaeger@gmail.com> Comprehensive R Archive Network (CRAN) Byron Jaeger [aut, cre] (ORCID: <https://orcid.org/0000-0001-7399-2299>), Nicholas Pajewski [ctb], Sawyer Welden [ctb], Christopher Jackson [rev], Marvin Wright [rev], Lukas Burk [rev] MIT + file LICENSE (https://CRAN.R-project.org/package=aorsf/LICENSE) 2025-12-11 application/tgz https://CRAN.R-project.org/package=aorsf doi:10.32614/CRAN.package.aorsf