RoBSA: Robust Bayesian Survival Analysis

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, 2021, <doi:10.48550/arXiv.2112.08311>). 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.

Version: 1.0.0
Depends: R (≥ 4.0.0)
Imports: BayesTools (≥ 0.2.10), survival, rjags, runjags, bridgesampling, scales, coda, stats, graphics, Rdpack
Suggests: parallel, ggplot2, flexsurv, testthat, vdiffr, knitr, rmarkdown
Published: 2022-05-27
Author: František Bartoš ORCID iD [aut, cre], Julia M. Haaf ORCID iD [ths], Matthew Denwood [cph] (Original copyright holder of some modified code where indicated.), Martyn Plummer [cph] (Original copyright holder of some modified code where indicated.)
Maintainer: František Bartoš <f.bartos96 at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: JAGS >= 4.3.0 (
Citation: RoBSA citation info
Materials: README NEWS
CRAN checks: RoBSA results


Reference manual: RoBSA.pdf


Package source: RoBSA_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): RoBSA_1.0.0.tgz, r-oldrel (arm64): RoBSA_1.0.0.tgz, r-release (x86_64): RoBSA_1.0.0.tgz, r-oldrel (x86_64): RoBSA_1.0.0.tgz


Please use the canonical form to link to this page.