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'))

Peer review:

Datasets:

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

3.18 score 6 scripts 213 downloads 4 exports 51 dependencies

Last updated 2 months agofrom:b0e640e37c. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 05 2025
R-4.5-linuxOKJan 05 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 Jan 05 2025.

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

How can I get more details about the methodology?

Rendered frommethod.Rmdusingknitr::rmarkdownon Jan 05 2025.

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

How I can predict events on a new dataset?

Rendered frompredict.Rmdusingknitr::rmarkdownon Jan 05 2025.

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