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DynForest

Random Forest with Multivariate Longitudinal Predictors

v1.2.0 · Oct 23, 2024 · LGPL (>= 3)

Description

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>.

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14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies DescTools cli cmprsk doParallel doRNG foreach ggplot2 lcmm pbapply pec prodlim stringr survival zoo DynForest

Version History

new 1.2.0 Mar 10, 2026
updated 1.2.0 ← 1.1.3 diff Oct 22, 2024
updated 1.1.3 ← 1.1.2 diff Mar 21, 2024
updated 1.1.2 ← 1.1.1 diff Dec 10, 2023
updated 1.1.1 ← 1.1.0 diff Feb 10, 2023
updated 1.1.0 ← 1.0.0 diff Nov 18, 2022
new 1.0.0 Sep 19, 2022