CRAN/E | DynForest

DynForest

Random Forest with Multivariate Longitudinal Predictors

Installation

About

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.

Citation DynForest citation info
github.com/anthonydevaux/DynForest
Bug report File report

Key Metrics

Version 1.1.3
R ≥ 4.3.0
Published 2024-03-22 26 days ago
Needs compilation? no
License LGPL (≥ 3)
CRAN checks DynForest results

Downloads

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Maintainer

Maintainer

Anthony Devaux

anthony.devauxbarault@gmail.com

Authors

Anthony Devaux

aut / cre

Robin Genuer

aut

Cécile Proust-Lima

aut

Louis Capitaine

aut

Material

README
NEWS
Reference manual
Package source

Vignettes

Introduction to 'DynForest' methodology
How to use 'DynForest' with categorical outcome?
How to use 'DynForest' with continuous outcome?
How to use 'DynForest' with survival outcome?

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

DynForest archive

Depends

R ≥ 4.3.0

Imports

DescTools
cmprsk
doParallel
doRNG
foreach
ggplot2
lcmm
methods
pbapply
pec
prodlim
stringr
survival
zoo

Suggests

knitr
rmarkdown