Bayesian Penalized Quantile Regression

Documentation for package ‘pqrBayes’ version 1.2.0

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 the 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