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survalis

0.7.1

Interpretable Survival Machine Learning Framework

0packages depend
1.3Kdownloads / year
75.5%test coverage
13/13checks pass

Overview

About
Maintained by Imad El BadisyFirst published 2026-04-241 releasesCRAN page ↗GitHub ↗

A modular toolkit for interpretable survival machine learning with a unified interface for fitting, prediction, evaluation, and interpretation. It includes semiparametric, parametric, tree-based, ensemble, boosting, kernel, and deep-learning survival learners, together with benchmarking, scoring, calibration, and model-agnostic interpretation utilities. Representative methodological anchors include Cox (1972) doi:10.1111/j.2517-6161.1972.tb00899.x, Royston and Parmar (2002) doi:10.1002/sim.1203, Ishwaran et al. (2008) doi:10.1214/08-AOAS169, Jaeger et al. (2019) doi:10.1214/19-AOAS1261, Harrell et al. (1982) doi:10.1001/jama.1982.03320430047030, Graf et al. (1999) doi:10.1002/(SICI)1097-0258(19990915/30)18:17/18%3C2529::AID-SIM274%3E3.0.CO;2-5, Friedman (2001) doi:10.1214/aos/1013203451, Apley and Zhu (2020) doi:10.1111/rssb.12377, and Lundberg and Lee (2017) https://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions, and other related methods for survival modeling, prediction, and interpretation.

Install

Health

CRAN checks
13OK
Slowest check: 6.7 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.29
75.5%
Coverage · measured lines
100%
Documentation · exports
34
Dependencies · direct
Check history
  • OK2026-08-04
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-04-24
    4 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 164 wordsVignettesNopkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
82%
Documented parameters
95%
Return-value docs
99%
References docs
9%

Downloads

1.3K
CRAN downloads in the past year
Rank #10,688 · ~4/day · ~110/mo
Daily download trend is not available in this view yet.
17330 days
92890 days
1.3K1 year
Compare downloads with other packages →
Also on29 r2u

Repository

Repository
1Stars
0Forks
0Open issues
1Open PRs
2Releases
532Commits
1Contributors
interpretable-machine-learningsurvival-analysis
532 commits · Last activity 2026-08-07

Stars over time

2026-07-07 · 02026-07-28 · 1

Repository practices

Upstream repositoryBeta

4 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/ielbadisy/survalis on 2026-08-09.

Continuous integration (1)
GitHub Actions
CRAN release process (1)
cran-comments.md
Docs source (1)
README.Rmd
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

1 release. R releases are shown for context.

  • 0.7.1Latest
    2026-04-24 · current release
  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-04-24
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.1
Bundled data
1.3 KB / 1 file
Download size
not tracked yet
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("survalis")
El Badisy, I. (2026). survalis: Interpretable Survival Machine Learning Framework (Version 0.7.1) [Computer software]. https://doi.org/10.32614/CRAN.package.survalis

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for survalis version 0.7.1 [Data set]. HJJB, LLC. Data release v2026-08-15. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-15, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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