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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.
Getting started
Browse package contents
Package details |
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| Author | František Bartoš [aut, cre] (<https://orcid.org/0000-0002-0018-5573>), Julia M. Haaf [ths] (<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.) |
| Maintainer | František Bartoš <f.bartos96@gmail.com> |
| License | GPL-3 |
| Version | 1.0.3 |
| URL | https://fbartos.github.io/RoBSA/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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