icRSF: A Modified Random Survival Forest Algorithm
Implements a modification to the Random Survival Forests algorithm for obtaining variable importance in high dimensional datasets. The proposed algorithm is appropriate for settings in which a silent event is observed through sequentially administered, error-prone self-reports or laboratory based diagnostic tests. The modified algorithm incorporates a formal likelihood framework that accommodates sequentially administered, error-prone self-reports or laboratory based diagnostic tests. The original Random Survival Forests algorithm is modified by the introduction of a new splitting criterion based on a likelihood ratio test statistic.
| Version: |
1.2 |
| Imports: |
Rcpp (≥ 0.11.3), icensmis, parallel, stats |
| LinkingTo: |
Rcpp |
| Published: |
2018-02-27 |
| Author: |
Hui Xu and Raji Balasubramanian |
| Maintainer: |
Hui Xu <huix at schoolph.umass.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| In views: |
Survival |
| CRAN checks: |
icRSF results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=icRSF
to link to this page.