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
DOI:	10.32614/CRAN.package.icRSF
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:

Reference manual:

icRSF.pdf

Downloads:

Package source:	icRSF_1.2.tar.gz
Windows binaries:	r-devel: icRSF_1.2.zip, r-release: icRSF_1.2.zip, r-oldrel: icRSF_1.2.zip
macOS binaries:	r-release (arm64): icRSF_1.2.tgz, r-oldrel (arm64): icRSF_1.2.tgz, r-release (x86_64): icRSF_1.2.tgz, r-oldrel (x86_64): icRSF_1.2.tgz
Old sources:	icRSF archive

Linking:

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