SAS.DCM.FORMAT_
function(input)
{
# input consists of scenario Price points and associated frequencies
# this produces the a format for data to be transformed into 
# for the PHREG procedure used for DCM models
# see Kuhfield (1995) pages 14-15
# no. of prices
	input <- input[, -1]	
	# this gets rid of the design columns for data
	d <- ncol(input)/2	
	# no. of scenarios
	ns <- nrow(input)
	imat <- diag(1, d)
	out <- NULL
	temp <- NULL
	freq <- rep(0, 2 * d)
	for(i in 1:ns) {
		x <- unlist(input[i,  ])
		p <- x[1:d]
		f <- x[(1:d) + d]
		n <- sum(f)	#print(i,p)
#print(i,f)
		temp2 <- NULL
		for(j in 1:d) {
			freq[2 * j - 1] <- 
				f[j]
			freq[2 * j] <- n - 
				f[j]
			temp <- p[j] * imat[
				,  - j]	
	#print(temp)
			temp2 <- cbind(
				temp2, temp
				)
		}
		temp <- cbind(freq, cbind(
			imat, p * imat, 
			temp2)[rep(1:d, rep(
			2, d)),  ])	
	#print(p*imat) 
		out <- rbind(out, temp)
	}
	out <- cbind(1:(2 * d), rep(1:nrow(
		input), rep(2 * d, nrow(
		input))), 1:2, out)	
	#labeling
#lp_paste("Price",1:d,sep="")
#lb_paste("Br",1:d,sep="")
	lb <- dimnames(input)[[2]][1:d]
	lp <- paste("PR", lb, sep = "_")	
	# obtaining labels for 
	cb1 <- outer(lb, lb, paste, sep = 
		"_")
	sub1.cb <- cbind(rep(1:d, rep(d, d)
		), rep(1:d, d))
	sub2.cb <-  - (1:d + d * (0:(d - 1)
		))
	cb2 <- cb1[sub1.cb[sub2.cb,  ]]
	dimnames(out) <- list(NULL, c("OBS",
		"SET", "T", "FREQ", lb, lp, 
		cb2))
	out
}
 


HeinekenData2008<-SAS.DCM.FORMAT(Heineken2008)