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obliqueRSF: Oblique Random Forests for Right-Censored Time-to-Event Data

Oblique random survival forests incorporate linear combinations of input variables into random survival forests (Ishwaran, 2008 <doi:10.1214/08-AOAS169>). Regularized Cox proportional hazard models (Simon, 2016 <doi:10.18637/jss.v039.i05>) are used to identify optimal linear combinations of input variables.

Version: 0.1.2
Depends: R (≥ 3.5.0)
Imports: Rcpp, pec, data.table, stats, missForest, purrr, glmnet, survival, dplyr, rlang, prodlim, ggthemes, tidyr, ggplot2, scales
LinkingTo: Rcpp, RcppArmadillo
Published: 2022-08-28
DOI: 10.32614/CRAN.package.obliqueRSF
Author: Byron Jaeger [aut, cre]
Maintainer: Byron Jaeger <bjaeger at wakehealth.edu>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: obliqueRSF results

Documentation:

Reference manual: obliqueRSF.pdf

Downloads:

Package source: obliqueRSF_0.1.2.tar.gz
Windows binaries: r-devel: obliqueRSF_0.1.2.zip, r-release: obliqueRSF_0.1.2.zip, r-oldrel: obliqueRSF_0.1.2.zip
macOS binaries: r-release (arm64): obliqueRSF_0.1.2.tgz, r-oldrel (arm64): obliqueRSF_0.1.2.tgz, r-release (x86_64): obliqueRSF_0.1.2.tgz, r-oldrel (x86_64): obliqueRSF_0.1.2.tgz
Old sources: obliqueRSF archive

Linking:

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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.