Package: recforest 1.0.2

Juliette Murris

recforest: Random Survival Forest for Recurrent Events

A tool designed to analyze recurrent events when dealing with right-censored data and the potential presence of a terminal event (that prevents further occurrences, like death). It extends the random survival forest algorithm, adapting splitting rules and node estimators to handle complexities of recurrent events. The methodology is fully described in Murris, J., Bouaziz, O., Jakubczak, M., Katsahian, S., & Lavenu, A. (2024) (<https://hal.science/hal-04612431v1/document>).

Authors:Juliette Murris [aut, cre], Guillaume Desachy [aut], Colin Fay [aut], Yohann Mansiaux [aut], Audrey Lavenu [aut], Sandrine Katsahian [aut]

recforest_1.0.2.tar.gz
recforest_1.0.2.zip(r-4.7-any)recforest_1.0.2.zip(r-4.6-any)
recforest_1.0.2.tar.gz(r-4.7-any)recforest_1.0.2.tar.gz(r-4.6-any)
recforest_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
recforest/json (API)

# Install 'recforest' in R:
install.packages('recforest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.18 score 1 stars 8 scripts 363 downloads 4 exports 37 dependencies

Last updated from:490c51709a. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK243
source / vignettesOK205
linux-releaseOK213
windows-develOK201
windows-releaseOK198
wasm-releaseOK115

Exports:%>%is_supported_variablemake_decisiontrain_forest

Dependencies:clicodetoolsdigestdplyrfuturefuture.applygenericsglobalsgluelatticelavalifecyclelistenvmagrittrMatrixmetsmvtnormnumDerivparallellypillarpkgconfigprogressrpurrrR6RcppRcppArmadilloredarlangsplines2SQUAREMsurvivaltibbletidyselecttimeregutf8vctrswithr

How I can predict events on a new dataset?
Load packages | Prepare data | Train a recforest model | Predict on new data
Rendered frompredict.Rmdusingknitr::rmarkdown

Last update: 2026-01-13
Started: 2024-12-05

How can I assess the influence of explanatory variables on the event?
Rendered fromexplain.Rmdusingknitr::rmarkdown

Last update: 2024-12-05
Started: 2024-12-05

How can I get more details about the methodology?
Introduction | Modeling framework | References
Rendered frommethod.Rmdusingknitr::rmarkdown

Last update: 2024-12-05
Started: 2024-12-05