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) .


Reference manual

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0.0.2 by Frank Harrell, a year ago

Browse source code at

Authors: Frank Harrell [aut, cre] , Ben Goodrich [ctb] (contributed Stan code) , Ben Bolker [ctb] (wrote original code that is folded into the pdensityContour function) , Doug Bates [ctb] (write original code for highest posterior density interval that is folded into the HPDint function)

Documentation:   PDF Manual  

GPL (>= 3) license

Imports methods, Rcpp, RcppParallel, rstan, rstantools, Hmisc, survival, ggplot2, MASS, cluster, digest, knitr, loo

Depends on rms

Suggests mice

Linking to BH, Rcpp, RcppEigen, RcppParallel, rstan, StanHeaders

System requirements: GNU make

Suggested by rms.

See at CRAN