library("mc2d")

Posdef <- function (n, ev = runif(n, 0, 10)) {
	Z <- matrix(ncol=n, rnorm(n^2))
	decomp <- qr(Z)
	Q <- qr.Q(decomp) 
	R <- qr.R(decomp)
	d <- diag(R)
	ph <- d / abs(d)
	O <- Q %*% diag(ph)
	Z <- t(O) %*% diag(ev) %*% O
	return(Z)
	}



N <- 1000 # number of draws

# generate random correlation matrix
sigma <- Posdef(5)
cor_mat <- cov2cor(sigma)

# independently generate 5 standard normal random variable
x1 <- rnorm(N)
x2 <- rnorm(N)
x3 <- rnorm(N)
x4 <- rnorm(N)
x5 <- rnorm(N)
 
# invoke iman-conover method
output <- cornode(cbind(x1,x2,x3,x4,x5),target=cor_mat)

# examine correlation matrices
cat("Spearman rank correlation matrix target:\n")
cor_mat
cat("Spearman rank correlation matrix of simulated data:\n")
cor(output, method="spearman")