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>.

Implements Bayesian model averaging for settings with many
    candidate regressors relative to the available sample size, including
    cases where the number of regressors exceeds the number of observations.
    By restricting attention to models with at most M regressors, the package
    supports reduced model space inference, thereby preserving degrees of
    freedom for estimation. It provides posterior summaries, Extreme Bounds
    Analysis, model selection procedures, joint inclusion measures, and
    graphical tools for exploring model probabilities, model size
    distributions, and coefficient distributions. The methodological
    approach follows Doppelhofer and Weeks (2009) <doi:10.1002/jae.1046>.

A function for multivariate outlier detection named Modified Stahel-Donoho (MSD) estimators is contained.  The function is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. 
    The function is called the single core version in Wada & Tsubaki (2013) <doi:10.1109/CLOUDCOM-ASIA.2013.86> and evaluated with other methods in Wada, Kawano & Tsubaki (2020) <doi:10.17713/ajs.v49i2.872>.

A parallel function for multivariate outlier detection named modified Stahel-Donoho estimators is contained in this package.  The function RMSDp() is for elliptically distributed datasets and recognizes outliers based on Mahalanobis distance. This function is for higher dimensional datasets that cannot be handled by a single core function RMSD() included in 'RMSD' package.  See Wada and Tsubaki (2013) <doi:10.1109/CLOUDCOM-ASIA.2013.86> for the detail of the algorithm.