RoBSA
1.0.4Robust Bayesian Survival Analysis
Overview
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.
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- ERROR r-release-macos-arm64
- ERROR2026-05-0710 OK · 0 NOTE · 0 WARNING · 3 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 55%
- Documented parameters
- 93%
- Return-value docs
- 92%
- References docs
- 10%
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Package metadata
- First published
- 2022-05-27
- Total releases
- 5 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.0.0
- Download size
- 147 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet