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  
    [aut, cre],
  Julia M. Haaf  
    [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 gmail.com> | 
| BugReports: | 
https://github.com/FBartos/RoBSA/issues | 
| License: | 
GPL-3 | 
| URL: | 
https://fbartos.github.io/RoBSA/ | 
| NeedsCompilation: | 
yes | 
| SystemRequirements: | 
JAGS >= 4.3.0 (https://mcmc-jags.sourceforge.io/) | 
| Citation: | 
RoBSA citation info  | 
| Materials: | 
README NEWS  | 
| CRAN checks: | 
RoBSA results | 
Documentation:
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