Package: LTRCforests 0.7.0
LTRCforests: Ensemble Methods for Survival Data with Time-Varying Covariates
Implements the conditional inference forest and relative risk forest algorithm to modeling left-truncated right-censored data with time-invariant covariates, and (left-truncated) right-censored survival data with time-varying covariates. It also provides functions to tune the parameters and evaluate the model fit. See Yao et al. (2022) <doi:10.1177/09622802221111549>.
Authors:
LTRCforests_0.7.0.tar.gz
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LTRCforests.pdf |LTRCforests.html✨
LTRCforests/json (API)
| # Install 'LTRCforests' in R: |
| install.packages('LTRCforests', repos = c('https://weichisite.r-universe.dev', 'https://cloud.r-project.org')) |
- pbcsample - Sample Mayo Clinic Primary Biliary Cirrhosis Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:79a790c28d. Checks:OK: 7 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 14 2024 |
| R-4.5-win-x86_64 | NOTE | Sep 14 2024 |
| R-4.5-linux-x86_64 | NOTE | Sep 14 2024 |
| R-4.4-win-x86_64 | OK | Sep 14 2024 |
| R-4.4-mac-x86_64 | OK | Sep 14 2024 |
| R-4.4-mac-aarch64 | OK | Sep 14 2024 |
| R-4.3-win-x86_64 | OK | Sep 14 2024 |
| R-4.3-mac-x86_64 | OK | Sep 14 2024 |
| R-4.3-mac-aarch64 | OK | Sep 14 2024 |
Exports:ltrccifltrcrrfpredictProbprintsbrier_ltrctune.ltrcciftune.ltrcrrf
Dependencies:classclicodetoolsdata.tablediagramdigestFormulafuturefuture.applyglobalsinumipredKernSmoothlatticelavalibcoinlistenvMASSMatrixmvtnormnnetnumDerivparallellypartykitprodlimprogressrRcpprpartshapeSQUAREMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Constructs forest methods for left-truncated and right-censored (LTRC) survival data | LTRCforests-package |
| Fit a LTRC conditional inference forest | ltrccif |
| Fit a LTRC relative risk forest | ltrcrrf |
| Sample Mayo Clinic Primary Biliary Cirrhosis Data | pbcsample |
| Compute a Survival Curve from a LTRCCIF model or a LTRCRRF model | predictProb predictProb.ltrccif, predictProb.ltrcrrf |
| Print Summary Output of a ltrccif object or a ltrcrrf object | print print.ltrccif, print.ltrcrrf |
| Model fit evaluation for LTRC forests. | sbrier_ltrc |
| Tune 'mtry' to the optimal value with respect to out-of-bag error for a LTRCCIF model | tune.ltrccif |
| Tune 'mtry' to the optimal value with respect to out-of-bag error for a LTRCRRF model | tune.ltrcrrf |
