Package: survivalisttoo 0.1.0

T. Moudiki

survivalisttoo: Model-Agnostic Survival Analysis

Model-agnostic survival analysis: using any Machine learning algorithm for doing survival analysis.

Authors:T. Moudiki [aut, cre]

survivalisttoo_0.1.0.tar.gz
survivalisttoo_0.1.0.zip(r-4.7)survivalisttoo_0.1.0.zip(r-4.6)survivalisttoo_0.1.0.zip(r-4.5)
survivalisttoo_0.1.0.tgz(r-4.6-x86_64)survivalisttoo_0.1.0.tgz(r-4.6-arm64)survivalisttoo_0.1.0.tgz(r-4.5-x86_64)survivalisttoo_0.1.0.tgz(r-4.5-arm64)
survivalisttoo_0.1.0.tar.gz(r-4.7-arm64)survivalisttoo_0.1.0.tar.gz(r-4.7-x86_64)survivalisttoo_0.1.0.tar.gz(r-4.6-arm64)survivalisttoo_0.1.0.tar.gz(r-4.6-x86_64)
survivalisttoo_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
survivalisttoo/json (API)

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

Bug tracker:https://github.com/techtonique/survivalisttoo/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

3.00 score 1 exports 1 dependencies

Last updated from:73c9183f8b. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK133
linux-devel-x86_64OK202
source / vignettesOK178
linux-release-arm64OK124
linux-release-x86_64OK115
macos-release-arm64OK93
macos-release-x86_64OK205
macos-oldrel-arm64OK128
macos-oldrel-x86_64OK199
windows-develOK97
windows-releaseOK99
windows-oldrelOK100
wasm-releaseOK117

Exports:cox_gradient_boost

Dependencies:Rcpp

Introduction to R package survivalisttoo

Rendered fromsurvivalisttoo.Rmdusingknitr::rmarkdownon Jun 05 2026.

Last update: 2026-05-01
Started: 2026-04-30

Introduction to R package survivalisttoo (with mlS3)

Rendered fromsurvivalisttoo_mlS3.Rmdusingknitr::rmarkdownon Jun 05 2026.

Last update: 2026-04-30
Started: 2026-04-30

Readme and manuals

Help Manual

Help pageTopics
Model-Agnostic Survival Analysissurvivalisttoo-package survivalisttoo
Cox Gradient Boosting Modelcox_gradient_boost
Predict from a CoxGradientBoost modelpredict.CoxGradientBoost
Print a CoxGradientBoost Objectprint.CoxGradientBoost