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icRSF
View on CRAN: Click
here
Download and install icRSF package within the R console
Install from CRAN:
install.packages("icRSF")
Install from Github:
library("remotes")
install_github("cran/icRSF")
Install by package version:
library("remotes")
install_version("icRSF", "1.2")
Attach the package and use:
library("icRSF")
Maintained by
Hui Xu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-01-20
Latest Update: 2018-02-27
Description:
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.
How to cite:
Hui Xu (2016). icRSF: A Modified Random Survival Forest Algorithm. R package version 1.2, https://cran.r-project.org/web/packages/icRSF. Accessed 22 Dec. 2024.
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imports, suggests or enhances
Complete documentation for icRSF
Functions, R codes and Examples using
the icRSF R package
Some associated functions: icrsf . simout . treebuilder .
Some associated R codes: RcppExports.R . Full icRSF package functions and examples
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