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rmsb (version 1.1-0)

Bayesian Regression Modeling Strategies

Description

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) .

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Version

Install

install.packages('rmsb')

Monthly Downloads

1,652

Version

1.1-0

License

GPL (>= 3)

Maintainer

Frank Harrell Jr

Last Published

March 12th, 2024

Functions in rmsb (1.1-0)

cluster

cluster
coef.rmsb

Extract Bayesian Summary of Coefficients
distSym

Distribution Symmetry Measure
plot.rmsb

Plot Posterior Densities and Summaries
predict.blrm

Make predictions from a blrm() fit
getParamCoef

Get a Bayesian Parameter Vector Summary
print.blrm

Print blrm() Results
pdensityContour

Bivariate Posterior Contour
compareBmods

Compare Bayesian Model Fits
selectedQr

QR Decomposition Preserving Selected Columns
rmsb-package

The 'rmsb' package.
stanDxplot

Diagnostic Trace Plots
stanGet

Get Stan Output
[.Ocens

Ocens
print.blrmStats

Print Details for blrmStats Predictive Accuracy Measures
tauFetch

Fetch Partial Proportional Odds Parameters
plot.PostF

Plot Posterior Density of PostF
print.predict.blrm

Print Predictions for blrm()
print.rmsb

Basic Print for Bayesian Parameter Summary
stackMI

Bayesian Model Fitting and Stacking for Multiple Imputation
vcov.rmsb

Variance-Covariance Matrix
stanDx

Print Stan Diagnostics
Ocens

Censored Ordinal Variable
Mean.blrm

Function Generator for Mean Y for blrm()
Quantile.blrm

Function Generator for Quantiles of Y for blrm()
as.data.frame.Ocens

Convert Ocens Object to Data Frame to Facilitate Subset
ExProb.blrm

Function Generator for Exceedance Probabilities for blrm()
blrm

Bayesian Binary and Ordinal Logistic Regression
HPDint

Highest Posterior Density Interval
blrmStats

Compute Indexes of Predictive Accuracy and Their Uncertainties
PostF

Function Generator for Posterior Probabilities of Assertions