Package: ICcforest 0.5.1
ICcforest: An Ensemble Method for Interval-Censored Survival Data
Implements the conditional inference forest approach to modeling interval-censored survival data. It also provides functions to tune the parameters and evaluate the model fit. See Yao et al. (2019) <arxiv:1901.04599>.
Authors:
ICcforest_0.5.1.tar.gz
ICcforest_0.5.1.zip(r-4.5)ICcforest_0.5.1.zip(r-4.4)ICcforest_0.5.1.zip(r-4.3)
ICcforest_0.5.1.tgz(r-4.4-any)ICcforest_0.5.1.tgz(r-4.3-any)
ICcforest_0.5.1.tar.gz(r-4.5-noble)ICcforest_0.5.1.tar.gz(r-4.4-noble)
ICcforest_0.5.1.tgz(r-4.4-emscripten)ICcforest_0.5.1.tgz(r-4.3-emscripten)
ICcforest.pdf |ICcforest.html✨
ICcforest/json (API)
NEWS
| # Install 'ICcforest' in R: |
| install.packages('ICcforest', repos = c('https://weichiyao.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:b33231dd25. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 21 2024 |
| R-4.5-win | OK | Nov 21 2024 |
| R-4.5-linux | OK | Nov 21 2024 |
| R-4.4-win | OK | Nov 21 2024 |
| R-4.4-mac | OK | Nov 21 2024 |
| R-4.3-win | OK | Nov 21 2024 |
| R-4.3-mac | OK | Nov 21 2024 |
Exports:ICcforestsbrier_ICtuneICRF
Dependencies:classclicodacodetoolsdata.tablediagramdigestforeachFormulafuturefuture.applyglobalsicenReginumiprediteratorsKernSmoothlatticelavalibcoinlistenvMASSMatrixMLEcensmvtnormnnetnumDerivparallellypartykitprodlimprogressrRcppRcppEigenrpartshapeSQUAREMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Construct a conditional inference forest model for interval-censored survival data | ICcforest-package |
| Extract an individual tree from an ICcforest object | gettree.ICcforest |
| Fit a conditional inference forest for interval-censored survival data | ICcforest |
| Predict from an ICcforest model | predict.ICcforest |
| Model Fit For Interval-Censored Data | sbrier_IC |
| Tune mtry to the optimal value with respect to out-of-bag error for an ICcforest model | tuneICRF |
