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DynForest
View on CRAN: Click
here
Download and install DynForest package within the R console
Install from CRAN:
install.packages("DynForest")
Install from Github:
library("remotes")
install_github("cran/DynForest")
Install by package version:
library("remotes")
install_version("DynForest", "1.2.0")
Attach the package and use:
library("DynForest")
Maintained by
Anthony Devaux
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.DynForest . https://github.com/anthonydevaux/DynForest/issues . https://github.com/anthonydevaux/DynForest . DynForest citation info . DynForest results . DynForest.pdf . How to use 'DynForest' with categorical outcome? . Introduction to 'DynForest' methodology . Overview of 'DynForest' package . How to use 'DynForest' with continuous outcome? . How to use 'DynForest' with survival outcome? . DynForest_1.2.0.tar.gz . DynForest_1.2.0.zip . DynForest_1.2.0.zip . DynForest_1.1.3.zip . DynForest_1.2.0.tgz . DynForest_1.2.0.tgz . DynForest_1.1.3.tgz . DynForest_1.2.0.tgz . DynForest_1.2.0.tgz . DynForest_1.1.3.tgz . DynForest archive . https://CRAN.R-project.org/package=DynForest .
First Published: 2022-09-20
Latest Update: 2023-12-11
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)
.
How to cite:
Anthony Devaux (2022). DynForest: Random Forest with Multivariate Longitudinal Predictors. R package version 1.2.0, https://cran.r-project.org/web/packages/DynForest. Accessed 29 Mar. 2025.
Previous versions and publish date:
Other packages that cited DynForest R package
View DynForest citation profile
Other R packages that DynForest depends,
imports, suggests or enhances
Complete documentation for DynForest
Functions, R codes and Examples using
the DynForest R package
Some associated functions: DynForest . DynTree . DynTree_surv . Fact.partitions . OOB.rfshape . OOB.tree . checking . combine_times . compute_OOBerror . compute_VIMP . compute_gVIMP . data_simu1 . data_simu2 . getParamMM . impurity . impurity_split . pbc2 . plot.DynForest . plot_CIF . pred.MMT . predRE . predict.DynForest . read.Xarg . rf_shape_para . summary.DynForest . var_depth . var_split . var_split_surv .
Some associated R codes: DynForest.R . DynTree.R . DynTree_surv.R . Fact_partitions.R . OOB_rfshape.R . OOB_tree.R . checking.R . combine_times.R . compute_OOBerror.R . compute_VIMP.R . compute_gVIMP.R . data_simu1.R . data_simu2.R . getParamMM.R . impurity.R . impurity_split.R . pbc2.R . plot.R . plot_CIF.R . predRE.R . pred_MMT.R . predict.R . read_Xarg.R . rf_shape_para.R . summary.R . var_depth.R . var_split.R . var_split_surv.R . Full DynForest package functions and examples
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