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Based on random forest principle, 'DynForest' is able to include multiple longitudinal predictors to provide individual predictions. Longitudinal predictors are modeled through the random forest. The methodology is fully described for a survival outcome in: Devaux, Helmer, Genuer & Proust-Lima (2023) <doi:10.1177/09622802231206477>.
Version: | 1.2.0 |
Depends: | R (≥ 4.4.0) |
Imports: | DescTools, cli, cmprsk, doParallel, doRNG, foreach, ggplot2, lcmm, methods, pbapply, pec, prodlim, stringr, survival, zoo |
Suggests: | knitr, rmarkdown |
Published: | 2024-10-23 |
DOI: | 10.32614/CRAN.package.DynForest |
Author: | Anthony Devaux [aut, cre], Robin Genuer [aut], Cécile Proust-Lima [aut], Louis Capitaine [aut] |
Maintainer: | Anthony Devaux <anthony.devauxbarault at gmail.com> |
BugReports: | https://github.com/anthonydevaux/DynForest/issues |
License: | LGPL (≥ 3) |
URL: | https://github.com/anthonydevaux/DynForest |
NeedsCompilation: | no |
Citation: | DynForest citation info |
Materials: | README NEWS |
CRAN checks: | DynForest results |
Package source: | DynForest_1.2.0.tar.gz |
Windows binaries: | r-devel: DynForest_1.2.0.zip, r-release: DynForest_1.2.0.zip, r-oldrel: DynForest_1.1.3.zip |
macOS binaries: | r-release (arm64): DynForest_1.2.0.tgz, r-oldrel (arm64): DynForest_1.1.3.tgz, r-release (x86_64): DynForest_1.2.0.tgz, r-oldrel (x86_64): DynForest_1.1.3.tgz |
Old sources: | DynForest archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.