Robust Bayesian Survival Analysis
Overview
A framework for estimating ensembles of parametric survival models with different parametric families. The RoBSA framework uses Bayesian model-averaging to combine the competing parametric survival models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual predictors or preference for a parametric family (Bartoš, Aust & Haaf, 2022, doi:10.1186/s12874-022-01676-9). The user can define a wide range of informative priors for all parameters of interest. The package provides convenient functions for summary, visualizations, fit diagnostics, and prior distribution calibration.
Install
Health
ERRORwhether package can be installedr-release-macos-arm64
Installation failed. See ‘/Volumes/Builds/packages/sonoma-arm64/results/4.6/RoBSA.Rcheck/00install.out’ for details.
- ERROR12 OK, 1 ERRORNow
- ERROR10 OK, 3 ERROR2026-05-07
- OK14 OK2026-03-10
Documentation
- Help pages
- 31includes a package overview page
- Examples that run
- 55%6 run in a plain check · 5 never run
- Exported functions with examples
- 38%
- Documented parameters
- 93%
- Return-value docs
- 92%
- Help pages citing references
- 10% with a bibliography file
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 1
Stars over time
Forks over time
Releases over time
Issues over time
PRs over time
9 development-tooling and community-health practices detected across 6 families in the upstream repository
Checks run against github.com/fbartos/robsa on 2026-10-18.
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Dependencies
Code & Tests
People & History
Package metadata
- First published
- 2022-05-27
- Total releases
- 5 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.0.0
- Download size
- 149 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("RoBSA")The package provides a citation file that builds its entry when R runs it. Run citation() to see it.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.