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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=DynForest to link to this page.
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