Package: recforest 1.0.0

Juliette Murris

recforest: Random Survival Forest for Recurrent Events

Analyze recurrent events with right-censored data and the potential presence of a terminal event (that prevents further occurrences, like death). 'recofest' 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_1.0.0.tar.gz
recforest_1.0.0.tar.gz(r-4.5-noble)recforest_1.0.0.tar.gz(r-4.4-noble)
recforest_1.0.0.tgz(r-4.4-emscripten)recforest_1.0.0.tgz(r-4.3-emscripten)
recforest.pdf |recforest.html
recforest/json (API)
NEWS

# 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 173 downloads 4 exports 51 dependencies

Last updated 4 months agofrom:b0e640e37c. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-linuxOKMar 06 2025
R-4.4-linuxOKMar 06 2025

Exports:%>%is_supported_variablemake_decisiontrain_forest

Dependencies:clicodetoolscolorspacedigestdplyrfansifarverfuturefuture.applygenericsggplot2globalsgluegtableisobandlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixmetsmgcvmunsellmvtnormnlmenumDerivparallellypillarpkgconfigprogressrpurrrR6RColorBrewerRcppRcppArmadilloredarlangscalessplines2SQUAREMsurvivaltibbletidyselecttimeregutf8vctrsviridisLitewithr

How can I assess the influence of explanatory variables on the event?

Rendered fromexplain.Rmdusingknitr::rmarkdownon Mar 06 2025.

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

How can I get more details about the methodology?

Rendered frommethod.Rmdusingknitr::rmarkdownon Mar 06 2025.

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

How I can predict events on a new dataset?

Rendered frompredict.Rmdusingknitr::rmarkdownon Mar 06 2025.

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