Several functions and S3 methods to construct a super learner in the presence of censored times-to-event and to evaluate its prognostic capacities.
Version: |
0.91 |
Depends: |
R (≥ 4.0.0), splines, survival, reticulate, tune |
Imports: |
date, graphics, MASS, nnet, kernlab, glmnet, caret, SuperLearner, flexsurv, randomForestSRC, survivalmodels, prodlim, hdnom, glmnetUtils, mosaic, mosaicCalc, cubature, timeROC, rpart, methods |
Published: |
2023-06-25 |
Author: |
Yohann Foucher
[aut, cre],
Camille Sabathe
[aut] |
Maintainer: |
Yohann Foucher <yohann.foucher at univ-poitiers.fr> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: |
no |
CRAN checks: |
survivalSL results |