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 |
Author: |
Byron Jaeger [aut, cre] |
Maintainer: |
Byron Jaeger <bjaeger at wakehealth.edu> |
License: |
GPL-3 |
NeedsCompilation: |
yes |
Materials: |
README |
CRAN checks: |
obliqueRSF results |
Documentation:
Downloads:
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