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, 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.
| Version: |
1.0.2 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
BayesTools (≥ 0.2.14), survival, rjags, runjags, scales, coda, stats, graphics, rlang, Rdpack |
| Suggests: |
parallel, ggplot2, flexsurv, testthat, vdiffr, knitr, rmarkdown, covr |
| Published: |
2023-05-30 |
| DOI: |
10.32614/CRAN.package.RoBSA |
| 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 >= 4.3.1 (https://mcmc-jags.sourceforge.io/) |
| Citation: |
RoBSA citation info |
| Materials: |
README NEWS |
| CRAN checks: |
RoBSA results |
Documentation:
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