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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) <doi:10.2307/2347760>.

Functions (29)

ExProb.blrm

Function Generator for Exceedance Probabilities for blrm()

HPDint

Highest Posterior Density Interval

Mean.blrm

Function Generator for Mean Y for blrm()

Ocens

Censored Ordinal Variable

PostF

Function Generator for Posterior Probabilities of Assertions

Quantile.blrm

Function Generator for Quantiles of Y for blrm()

as.data.frame.Ocens

Convert Ocens Object to Data Frame to Facilitate Subset

blrm

Bayesian Binary and Ordinal Logistic Regression

blrmStats

Compute Indexes of Predictive Accuracy and Their Uncertainties

coef.rmsb

Extract Bayesian Summary of Coefficients

compareBmods

Compare Bayesian Model Fits

distSym

Distribution Symmetry Measure

getParamCoef

Get a Bayesian Parameter Vector Summary

pdensityContour

Bivariate Posterior Contour

plot.PostF

Plot Posterior Density of PostF

plot.rmsb

Plot Posterior Densities and Summaries

predict.blrm

Make predictions from a blrm() fit

print.blrm

Print blrm() Results

print.blrmStats

Print Details for blrmStats Predictive Accuracy Measures

print.predict.blrm

Print Predictions for blrm()

print.rmsb

Basic Print for Bayesian Parameter Summary

rmsb-package

The 'rmsb' package.

selectedQr

QR Decomposition Preserving Selected Columns

stackMI

Bayesian Model Fitting and Stacking for Multiple Imputation

stanDx

Print Stan Diagnostics

stanDxplot

Diagnostic Trace Plots

stanGet

Get Stan Output

tauFetch

Fetch Partial Proportional Odds Parameters

vcov.rmsb

Variance-Covariance Matrix

rmsb

Bayesian Regression Modeling Strategies

v0.0.2

GPL (>= 3)

Authors

Frank Harrell [aut, cre] (<https://orcid.org/0000-0002-8271-5493>), 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)

Initial release

2021-02-27

rmsb

Functions (29)

rmsb

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