rmsb
Bayesian Regression Modeling Strategies
A Bayesian companion to the 'rms' package, 'rmsb' provides Bayesian model fitting, post-fit estimation, and graphics. It implements Bayesian regression models whose fit objects can be processed by 'rms' functions such as 'contrast()', 'summary()', 'Predict()', 'nomogram()', and 'latex()'. The fitting function currently implemented in the package is 'blrm()' for Bayesian logistic binary and ordinal regression with optional clustering, censoring, and departures from the proportional odds assumption using the partial proportional odds model of Peterson and Harrell (1990) <https://www.jstor.org/stable/2347760>.
- Version1.1-1
- R version≥ 3.4.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release07/08/2024
Documentation
Team
Frank Harrell
Ben Bolker
Ben Goodrich
Show author detailsRolesContributorDoug Bates
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- Depends1 package
- Imports10 packages
- Suggests2 packages
- Linking To6 packages
- Reverse Suggests1 package