Package: survivalSL 1.0

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]

survivalSL_1.0.tar.gz
survivalSL_1.0.zip(r-4.7)survivalSL_1.0.zip(r-4.6)survivalSL_1.0.zip(r-4.5)
survivalSL_1.0.tgz(r-4.6-any)survivalSL_1.0.tgz(r-4.5-any)
survivalSL_1.0.tar.gz(r-4.7-any)survivalSL_1.0.tar.gz(r-4.6-any)
survivalSL_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
survivalSL/json (API)

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

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:

Conda:

3.70 score 1 stars 9 scripts 183 downloads 28 exports 210 dependencies

Last updated from:94db0015e1. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK279
source / vignettesOK278
linux-release-x86_64OK273
macos-release-arm64OK188
macos-oldrel-arm64OK186
windows-develOK214
windows-releaseOK209
windows-oldrelOK194
wasm-releaseOK184

Exports:LIB_AFTgammaLIB_AFTggammaLIB_AFTllogisLIB_AFTweibullLIB_COXaicLIB_COXallLIB_COXenLIB_COXlassoLIB_COXridgeLIB_PHexponentialLIB_PHgompertzLIB_PHsplineLIB_PLANNLIB_RSFmetricsplot.libslplot.sltimepredict.libslpredict.sltimesummary.libslsummary.sltimesurvivalSLtuneCOXentuneCOXlassotuneCOXridgetunePHsplinetunePLANNtuneRSF

Dependencies:assertthatbackportsbase64encbbmlebdsmatrixbitbit64bitopsbslibcachemcaretcaToolscheckmateclassclicliprclockclustercmprskcodetoolscolorspacecpp11crayoncubaturecvAUCdata.tabledata.treedatedeSolvediagramDiagrammeRdialsDiceDesigndigestdoParalleldplyre1071evaluatefarverfastGHQuadfastmapflexsurvfontawesomefontBitstreamVerafontLiberationfontquiverforcatsforeachforeignFormulafsfurrrfuturefuture.applygamGauProgdtoolsgenericsggformulaggiraphggplot2ggridgesglmnetglobalsgluegowergplotsgridExtragtablegtoolshardhathavenhdnomherehighrHmischmshtmlTablehtmltoolshtmlwidgetsigraphipredisobanditeratorsjquerylibjsonlitekernlabKernSmoothknitrlabelinglabelledlatticelavalazyevallbfgslifecyclelistenvlsodalubridatemagrittrMASSMatrixMatrixModelsmemoisemetsmgcvmimemixoptmodelenvModelMetricsmosaicmosaicCoremosaicDatamstatemuhazmultcompmvtnormncvregnlmennetnnlsnumDerivpammtoolsparallellyparsnippecpenalizedpillarpkgconfigplotrixplyrpngpolsplineprettyunitspROCprodlimprogressprogressrproxyPublishpurrrquadprogquantregR6randomForestSRCrangerrappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppTOMLreadrrecipesrelsurvreshape2reticulateRISCAriskRegressionrlangrmarkdownrmsROCRrpartrprojrootrsamplerstpm2rstudioapiS7sandwichsassscalesscamsfdshapesliderSparseMsparsevctrssplitfngrSQUAREMstatmodstringistringrSuperLearnersurvivalsurvivalPLANNsystemfontstailorTH.datatibbletidyrtidyselecttimechangetimeDatetimeregtinytextunetzdbutf8vctrsviridisLitevisNetworkvroomwarpwithrworkflowsxfunyamlyardstickzoo

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
Metrics to Evaluate the Prognostic Capacitiesmetrics
Calibration Plotplot.libsl
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
Summaries of a Learnersummary.libsl
Summaries of a Super Learnersummary.sltime
Super Learner for Censored OutcomessurvivalSL
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