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.

Install the latest version of this package by entering the following in R:
install.packages("icRSF")
AuthorHui Xu and Raji Balasubramanian
Date of publication2016-01-20 17:07:02
MaintainerHui Xu <huix@schoolph.umass.edu>
LicenseGPL (>= 2)
Version1.0

View on CRAN

Files

src
src/loglikhood2.cpp
src/dataproc.cpp
src/RcppExports.cpp
NAMESPACE
data
data/Xmat.rda
data/pheno.rda
R
R/RcppExports.R R/simout.r R/icrsf.r
MD5
DESCRIPTION
man
man/icrsf.Rd man/pheno.Rd man/icRSF_1.0-package.Rd man/Xmat.Rd man/simout.Rd

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