Package: survivalSL 0.97

survivalSL: Super Learner for Survival Prediction from Censored Data

Several functions and S3 methods to construct a super learner in the presence of censored times-to-event and to evaluate its prognostic capacities.

Authors:Yohann Foucher [aut, cre], Camille Sabathe [aut]

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survivalSL.pdf |survivalSL.html✨
survivalSL/json (API)

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

Peer review:

Bug tracker:https://github.com/foucher-y/survivalsl/issues

Datasets:
  • dataDIVAT2 - A Sample from the DIVAT Data Bank.
  • dataDIVAT3 - A Sample from the DIVAT Data Bank.
  • dataOFSEP - A Simulated Sample from the OFSEP Cohort.

On CRAN:

3.90 score 2 stars 220 downloads 27 exports 134 dependencies

Last updated 1 days agofrom:d675106f9e. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 30 2025
R-4.5-winOKJan 30 2025
R-4.5-macOKJan 30 2025
R-4.5-linuxOKJan 30 2025
R-4.4-winOKJan 30 2025
R-4.4-macOKJan 30 2025
R-4.3-winOKJan 30 2025
R-4.3-macOKJan 30 2025

Exports:LIB_AFTgammaLIB_AFTggammaLIB_AFTllogisLIB_AFTweibullLIB_COXaicLIB_COXallLIB_COXenLIB_COXlassoLIB_COXridgeLIB_PHexponentialLIB_PHgompertzLIB_PHsplineLIB_PLANNLIB_RSFLIB_SNNmetricsplot.libslrocsurvivalSLtuneCOXaictuneCOXentuneCOXlassotuneCOXridgetunePHsplinetunePLANNtuneRSFtuneSNN

Dependencies:assertthatbase64encbbmlebdsmatrixBHbitbit64bslibcachemcaretclassclicliprclockcodetoolscolorspacecpp11crayondata.tabledata.treedatedeSolvediagramDiagrammeRdigestdplyre1071evaluatefansifarverfastGHQuadfastmapflexsurvfontawesomeforeachfsfuturefuture.applygenericsggplot2glmnetglmnetUtilsglobalsgluegowergridExtragtablehardhathdnomhighrhmshtmltoolshtmlwidgetsigraphipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmemoisemgcvmimeModelMetricsmstatemuhazmunsellmvtnormncvregnlmennetnumDerivparallellypenalizedpillarpkgconfigplyrprettyunitspROCprodlimprogressprogressrproxypurrrquadprogR6randomForestSRCrappdirsRColorBrewerRcppRcppArmadilloRcppEigenreadrrecipesreshape2rlangrmarkdownrpartrstpm2rstudioapisassscalesshapeSQUAREMstatmodstringistringrsurvivalsurvivalPLANNtibbletidyrtidyselecttimechangetimeDatetinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
A Sample from the DIVAT Data Bank.dataDIVAT2
A Sample from the DIVAT Data Bank.dataDIVAT3
A Simulated Sample from the OFSEP Cohort.dataOFSEP
Library of the Super Learner for an Accelerated Failure Time (AFT) Model with a Gamma DistributionLIB_AFTgamma
Library of the Super Learner for an Accelerated Failure Time (AFT) Model with a Generalized Gamma DistributionLIB_AFTggamma
Library of the Super Learner for an Accelerated Failure Time (AFT) Model with a Log Logistic DistributionLIB_AFTllogis
Library of the Super Learner for an Accelerated Failure Time (AFT) Model with a Weibull DistributionLIB_AFTweibull
Library of the Super Learner for a Cox Model with Selected CovariatesLIB_COXaic
Library of the Super Learner for Cox RegressionLIB_COXall
Library of the Super Learner for Elastic Net Cox RegressionLIB_COXen
Library of the Super Learner for Lasso Cox RegressionLIB_COXlasso
Library of the Super Learner for Ridge Cox RegressionLIB_COXridge
Library of the Super Learner for a Proportional Hazards (PH) Model with an Exponential DistributionLIB_PHexponential
Library of the Super Learner for an Proportional Hazards (PH) Model with a Gompertz DistributionLIB_PHgompertz
Library of the Super Learner for an Survival Regression using the Royston/Parmar Spline ModelLIB_PHspline
Library of the Super Learner for Survival Neural Network Based on the PLANN MethodLIB_PLANN
Library of the Super Learner for Survival Random Survival ForestLIB_RSF
Library of the Super Learner for Survival Neural NetworkLIB_SNN
Metrics to Evaluate the Prognostic Capacitiesmetrics
Calibration Plot for a Cox-like Modelplot.libsl
Plot Method for 'rocrisca' Objectsplot.rocrisca
Calibration Plot for Super Learnerplot.sltime
Prediction from an Flexible Parametric Modelpredict.libsl
Prediction from a Super Learner for Censored Outcomespredict.sltime
S3 Method for Printing an 'libsl' Objectprint.libsl
S3 Method for Printing an 'sltime' Objectprint.sltime
Time-Dependent ROC Curves With Right Censored Dataroc
Summaries of a Learnersummary.libsl
Summaries of a Super Learnersummary.sltime
Super Learner for Censored OutcomessurvivalSL
Tune a Cox Model with a Forward Selection Based on the AICtuneCOXaic
Tune Elastic Net Cox RegressiontuneCOXen
Tune Lasso Cox RegressiontuneCOXlasso
Tune Ridge Cox RegressiontuneCOXridge
Tune a Survival Regression using the Royston/Parmar Spline ModeltunePHspline
Tune a Survival Neural Network Based on the PLANN MethodtunePLANN
Tune a Survival Random ForesttuneRSF
Tune a 1-Layer Survival Neural NetworktuneSNN