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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("icRSF")

1.2 by Hui Xu, a year ago


Browse source code at https://github.com/cran/icRSF


Authors: Hui Xu and Raji Balasubramanian


Documentation:   PDF Manual  


Task views: Survival Analysis


GPL (>= 2) license


Imports Rcpp, icensmis, parallel, stats

Linking to Rcpp


See at CRAN