Package: rocTree 1.1.1
rocTree: Receiver Operating Characteristic (ROC)-Guided Classification and Survival Tree
Receiver Operating Characteristic (ROC)-guided survival trees and ensemble algorithms are implemented, providing a unified framework for tree-structured analysis with censored survival outcomes. A time-invariant partition scheme on the survivor population was considered to incorporate time-dependent covariates. Motivated by ideas of randomized tests, generalized time-dependent ROC curves were used to evaluate the performance of survival trees and establish the optimality of the target hazard/survival function. The optimality of the target hazard function motivates us to use a weighted average of the time-dependent area under the curve (AUC) on a set of time points to evaluate the prediction performance of survival trees and to guide splitting and pruning. A detailed description of the implemented methods can be found in Sun et al. (2019) <arxiv:1809.05627>.
Authors:
rocTree_1.1.1.tar.gz
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rocTree_1.1.1.tgz(r-4.4-x86_64)rocTree_1.1.1.tgz(r-4.4-arm64)rocTree_1.1.1.tgz(r-4.3-x86_64)rocTree_1.1.1.tgz(r-4.3-arm64)
rocTree_1.1.1.tar.gz(r-4.5-noble)rocTree_1.1.1.tar.gz(r-4.4-noble)
rocTree_1.1.1.tgz(r-4.4-emscripten)rocTree_1.1.1.tgz(r-4.3-emscripten)
rocTree.pdf |rocTree.html✨
rocTree/json (API)
NEWS
# Install 'rocTree' in R: |
install.packages('rocTree', repos = c('https://stc04003.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/stc04003/roctree/issues
- simDat - Simulated dataset for demonstration
Last updated 4 years agofrom:56c9818858. Checks:OK: 1 NOTE: 5 WARNING: 3. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 22 2024 |
R-4.5-win-x86_64 | WARNING | Oct 22 2024 |
R-4.5-linux-x86_64 | NOTE | Oct 22 2024 |
R-4.4-win-x86_64 | WARNING | Oct 22 2024 |
R-4.4-mac-x86_64 | NOTE | Oct 22 2024 |
R-4.4-mac-aarch64 | NOTE | Oct 22 2024 |
R-4.3-win-x86_64 | WARNING | Oct 22 2024 |
R-4.3-mac-x86_64 | NOTE | Oct 22 2024 |
R-4.3-mac-aarch64 | NOTE | Oct 22 2024 |
Exports:rocTreesimuSurvtrueHaztrueSurv
Dependencies:assertthatbase64encbbmlebdsmatrixBHbitbit64bslibcachemclicliprcolorspacecpp11crayondata.tabledata.treedeSolveDiagrammeRdigestdplyrevaluatefansifarverfastGHQuadfastmapflexsurvfontawesomefsgenericsggplot2gluegtablehighrhmshtmltoolshtmlwidgetsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemstatemuhazmunsellmvtnormnlmenumDerivpillarpkgconfigprettyunitsprogresspurrrquadprogR6rappdirsRColorBrewerRcppRcppArmadilloreadrrlangrmarkdownrstpm2rstudioapisassscalesstatmodstringistringrsurvivaltibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
rocTree:Receiver Operating Characteristic (ROC)-Guided Classification Survival Tree and Ensemble. | rocTree-package _PACKAGE |
'Surv' function imported from 'survival' | export_Surv Surv |
Plotting an 'rocTree' object | plot.rocTree |
Predicting based on a 'rocTree' model. | predict.rocTree |
Printing an 'rocTree' object | print.rocTree |
Roc-guided survival trees | rocTree |
Simulated dataset for demonstration | simDat |
Function to generate simulated data used in the manuscript. | simu trueHaz trueSurv |