Random Forest with Multivariate Longitudinal Predictors R package DynForest version 1.2.0 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>. Software Depends: R (>= 4.4.0) Imports: DescTools, cli, cmprsk, doParallel, doRNG, foreach, ggplot2, lcmm, methods, pbapply, pec, prodlim, stringr, survival, zoo Suggests: knitr, rmarkdown Anthony Devaux <anthony.devauxbarault@gmail.com> Comprehensive R Archive Network (CRAN) Anthony Devaux [aut, cre] (ORCID: <https://orcid.org/0000-0002-8862-4218>), Robin Genuer [aut] (ORCID: <https://orcid.org/0000-0002-0981-3943>), Cécile Proust-Lima [aut] (ORCID: <https://orcid.org/0000-0002-9884-955X>), Louis Capitaine [aut] (ORCID: <https://orcid.org/0000-0001-6800-2342>) LGPL (>= 3) 2024-10-23 application/tgz https://CRAN.R-project.org/package=DynForest doi:10.32614/CRAN.package.DynForest