Robust Bayesian Survival Analysis R package RoBSA version 1.0.4 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. Software Depends: R (>= 4.0.0) Imports: BayesTools (>= 0.3.0), survival, rjags, runjags, scales, coda, stats, graphics, rlang, Rdpack Suggests: parallel, ggplot2, flexsurv, testthat, vdiffr, knitr, rmarkdown, covr František Bartoš <f.bartos96@gmail.com> Comprehensive R Archive Network (CRAN) František Bartoš [aut, cre] (ORCID: <https://orcid.org/0000-0002-0018-5573>), Julia M. Haaf [ths] (ORCID: <https://orcid.org/0000-0001-5122-706X>), Matthew Denwood [cph] (Original copyright holder of some modified code where indicated.), Martyn Plummer [cph] (Original copyright holder of some modified code where indicated.) GPL-3 2026-05-07 application/tgz https://CRAN.R-project.org/package=RoBSA doi:10.32614/CRAN.package.RoBSA