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: 1.0
Imports: Rcpp (≥ 0.11.3), icensmis, parallel
LinkingTo: Rcpp
Published: 2016-01-20
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

Downloads:

Reference manual: icRSF.pdf
Package source: icRSF_1.0.tar.gz
Windows binaries: r-devel: icRSF_1.0.zip, r-release: icRSF_1.0.zip, r-oldrel: icRSF_1.0.zip
OS X El Capitan binaries: r-release: icRSF_1.0.tgz
OS X Mavericks binaries: r-oldrel: icRSF_1.0.tgz

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