R/bayesQR.r

In bayesQR: Bayesian Quantile Regression

bayesQR <- function(formula=NULL, data=NULL, quantile=0.5, alasso=FALSE, normal.approx=NULL, ndraw=NULL, keep=1, prior=NULL){

	# Create function for error message
	pandterm <- function(message) {
		stop(message, call. = FALSE)
	}

	# Check if a single or a sequence of quantile regressions is required
	nqr <- length(quantile)

	# Define an empty object (list)
	out <- NULL

	# If only one quantile is required, then call bayesQR_single
	if (nqr==1){
		out[[1]] <- bayesQR_single(formula=formula, data=data, quantile=quantile, alasso=alasso, normal.approx=normal.approx, ndraw=ndraw, keep=keep, prior=prior)

	# Else, estimate a sequence of bayesQR_single
	} else {

		# Sort required quantiles
		quantile <- sort(quantile)

		# Estimate sequence of bayesQR
		for (i in 1:nqr){
		
			# Print information to console
			cat("************************************************","\n")
			cat("* Start estimating quantile ", i," of ", nqr, "in total *", "\n")
			cat("************************************************","\n")
			
			# Set correct quantile and estimate model
			out[[i]] <- bayesQR_single(formula=formula, data=data, quantile=quantile[i], alasso=alasso, normal.approx=normal.approx, ndraw=ndraw, keep=keep, prior=prior)
		}
	}

	class(out) <- "bayesQR"
	return(out)
}