# Bayesian Penalized Quantile Regression

## Documentation for package ‘pqrBayes’ version 1.2.2

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

pqrBayes-package | Bayesian penalized quantile regression for the sparse linear model, binary LASSO, group LASSO and varying coefficient models based on spike-and-slab priors and/or the horseshoe family of priors
coverage | 95% empirical coverage probability for a pqrBayes object
data | Simulated data under high-dimensional linear, binary, group LASSO and quantile varying coefficient models
estimation.pqrBayes | Estimation and estimation accuracy for a pqrBayes object
pqrBayes | fit Bayesian penalized quantile regression for a sparse linear model, binary LASSO, group LASSO, or varying coefficient model based on spike-and-slab priors and/or the horseshoe family of priors
pqrBayes.select | Variable selection for a pqrBayes object
predict_pqrBayes | Make predictions from a pqrBayes object
print.pqrBayes | print a pqrBayes result
print.pqrBayes.pred | print a pqrBayes.pred object
print.pqrBayes.select | print a select.pqrBayes object