Package: randomForestRHF 1.0.2

randomForestRHF: Random Hazard Forests

Random Hazard Forests (RHF) extend Random Survival Forests (RSF) by directly estimating the hazard function and by accommodating time-dependent covariates through counting-process style inputs. The package fits tree ensembles for dynamic survival prediction, returning hazard, cumulative hazard, integrated hazard, and related performance summaries for training and test data. The methods build on Random Survival Forests described by Ishwaran et al. (2008) <doi:10.1214/08-AOAS169> and on nonparametric hazard modeling with time-dependent covariates described by Lee et al. (2021) <doi:10.1214/20-AOS2028>.

Authors:Hemant Ishwaran [aut], Udaya B. Kogalur [aut, cre]

randomForestRHF_1.0.2.tar.gz
randomForestRHF_1.0.2.zip(r-4.7)randomForestRHF_1.0.2.zip(r-4.6)randomForestRHF_1.0.2.zip(r-4.5)
randomForestRHF_1.0.2.tgz(r-4.6-x86_64)randomForestRHF_1.0.2.tgz(r-4.6-arm64)randomForestRHF_1.0.2.tgz(r-4.5-x86_64)randomForestRHF_1.0.2.tgz(r-4.5-arm64)
randomForestRHF_1.0.2.tar.gz(r-4.7-arm64)randomForestRHF_1.0.2.tar.gz(r-4.7-x86_64)randomForestRHF_1.0.2.tar.gz(r-4.6-arm64)randomForestRHF_1.0.2.tar.gz(r-4.6-x86_64)
randomForestRHF_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
randomForestRHF/json (API)
NEWS

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

Bug tracker:https://github.com/kogalur/randomforestrhf/issues

Pkgdown/docs site:https://www.randomforestsrc.org

Uses libs:
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openmp

2.60 score 2 stars 444 downloads 28 exports 77 dependencies

Last updated from:42347c04a7. Checks:11 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE162
linux-devel-x86_64NOTE179
source / vignettesOK186
linux-release-arm64NOTE168
linux-release-x86_64NOTE219
macos-release-arm64NOTE93
macos-release-x86_64NOTE241
macos-oldrel-arm64NOTE126
macos-oldrel-x86_64NOTE227
windows-develNOTE147
windows-releaseNOTE142
windows-oldrelNOTE167
wasm-releaseOK135

Exports:as.data.frame.importance.rhfauctauct.rhfconvert.countingconvert.standard.countingdotmatrix.importancedotmatrix.importance.rhfhazard.simulationimportance.rhfplot.auct.rhfplot.importance.rhfplot.rhfplot.tune.treesize.rhfpredict.rhfprint.auct.rhfprint.importance.rhfprint.rhfrhfrhf.newssmoothed.hazardsmoothed.hazard.rhftune.iAUCtune.iAUC.rhftune.rhftune.treesize.rhfvarpro.cachevarpro.cache.rhfxvar.wt.rhf

Dependencies:BARTbase64encbitbit64bslibcachemclicliprcodetoolscpp11crayondata.treeDiagrammeRdigestdplyrevaluatefarverfastmapfontawesomeforeachfsgbmgenericsglmnetgluehighrhmshtmltoolshtmlwidgetsigraphiteratorsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimenlmepillarpkgconfigprettyunitsprogresspurrrR6randomForestSRCrappdirsRColorBrewerRcppRcppEigenreadrrlangrmarkdownrstudioapisassscalesshapestringistringrsurvivaltibbletidyrtidyselecttinytextzdbutf8varProvctrsviridisLitevisNetworkvroomwithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Time-varying AUC(t) and iAUC for Random Hazard Forests (TDC)auct auct.rhf plot.auct.rhf print.auct.rhf
Time-localized VarPro importance for random hazard forestsas.data.frame.importance.rhf barplot.importance barplot.importance.rhf dotmatrix.importance dotmatrix.importance.rhf importance.rhf plot.importance.rhf print.importance.rhf varpro.cache varpro.cache.rhf
Plot smoothed hazard and cumulative hazard plots from RHF analysisplot.rhf
Prediction on Test Data for Random Hazard Forestspredict.rhf
Print Output from a Random Hazard Forest Analysisprint.rhf print.vimp.rhf
Random Hazard Forestsrhf
Show the NEWS filerhf.news
Smoothed hazard and cumulative hazard estimates from a random hazard forestsmoothed.hazard smoothed.hazard.rhf
Tune tree size for Random Hazard Forestsplot.tune.treesize.rhf tune.iAUC tune.iAUC.rhf tune.rhf tune.treesize.rhf