Package: iBST 1.2

iBST: Improper Bagging Survival Tree

Fit a full or subsampling bagging survival tree on a mixture of population (susceptible and nonsusceptible) using either a pseudo R2 criterion or an adjusted Logrank criterion. The predictor is evaluated using the Out Of Bag Integrated Brier Score (IBS) and several scores of importance are computed for variable selection. The thresholds values for variable selection are computed using a nonparametric permutation test. See 'Cyprien Mbogning' and 'Philippe Broet' (2016)<doi:10.1186/s12859-016-1090-x> for an overview about the methods implemented in this package.

Authors:Cyprien Mbogning and Philippe Broet

iBST_1.2.tar.gz
iBST_1.2.zip(r-4.5)iBST_1.2.zip(r-4.4)iBST_1.2.zip(r-4.3)
iBST_1.2.tgz(r-4.4-x86_64)iBST_1.2.tgz(r-4.4-arm64)iBST_1.2.tgz(r-4.3-x86_64)iBST_1.2.tgz(r-4.3-arm64)
iBST_1.2.tar.gz(r-4.5-noble)iBST_1.2.tar.gz(r-4.4-noble)
iBST_1.2.tgz(r-4.4-emscripten)iBST_1.2.tgz(r-4.3-emscripten)
iBST.pdf |iBST.html
iBST/json (API)

# Install 'iBST' in R:
install.packages('iBST', repos = c('https://cyprien84.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

7 exports 0.36 score 5 dependencies 1 mentions 8 scripts 275 downloads

Last updated 2 years agofrom:b443d3bb10. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 24 2024
R-4.5-win-x86_64OKAug 24 2024
R-4.5-linux-x86_64OKAug 24 2024
R-4.4-win-x86_64OKAug 24 2024
R-4.4-mac-x86_64OKAug 24 2024
R-4.4-mac-aarch64OKAug 24 2024
R-4.3-win-x86_64OKAug 24 2024
R-4.3-mac-x86_64OKAug 24 2024
R-4.3-mac-aarch64OKAug 24 2024

Exports:Bagg_pred_SurvBagg_Survimproper_treepermute_select_survPseudoR2.Curercpp_hello_worldtree2indicators

Dependencies:latticeMatrixRcpprpartsurvival