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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.

Versions across snapshots

VersionRepositoryFileSize
1.0.3 rolling linux/jammy R-4.5 RoBSA_1.0.3.tar.gz 359.9 KiB
1.0.3 rolling linux/noble R-4.5 RoBSA_1.0.3.tar.gz 359.7 KiB
1.0.3 rolling source/ R- RoBSA_1.0.3.tar.gz 146.1 KiB
1.0.3 latest linux/jammy R-4.5 RoBSA_1.0.3.tar.gz 359.9 KiB
1.0.3 latest linux/noble R-4.5 RoBSA_1.0.3.tar.gz 359.7 KiB
1.0.3 latest source/ R- RoBSA_1.0.3.tar.gz 146.1 KiB
1.0.3 2026-04-26 source/ R- RoBSA_1.0.3.tar.gz 146.1 KiB
1.0.3 2026-04-23 source/ R- RoBSA_1.0.3.tar.gz 146.1 KiB
1.0.3 2026-04-09 windows/windows R-4.5 RoBSA_1.0.3.zip 426.9 KiB
1.0.3 2025-04-20 source/ R- RoBSA_1.0.3.tar.gz 146.1 KiB

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