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# Copyright (c) 2015 Santiago Barreda
# All rights reserved.
rmvtnorm = function (n = 1, k = 2, means = rep(0, k), sigma = diag(k)){
if (length(sigma) == 1) if (sigma >= -1 & sigma <= 1)
sigma = matrix(c(1, sigma, sigma, 1), 2, 2)
else stop("Correlation magnitude must be less than or equal to 1.")
if (!identical(sigma, t(sigma)))
stop("Inappropriate covariance matrix specified.")
if (nrow(sigma) != k | ncol(sigma) != k | length(means) != k)
stop("Incorrect covariance matrix dimensions.")
eig = eigen(sigma, symmetric = TRUE)
if (sum(eig$values < 0) > 0)
stop("Inappropriate covariance matrix specified.")
A = eig$vectors %*% diag(sqrt(eig$values))
x = matrix(rnorm(n * length(means), 0, 1), k, n)
output = t(means + A %*% x)
return(output)
}
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