Generates realizations from a multivariate normal distribution
Generates realizations from a multivariate normal distribution.
rmvnorm(nsim = 1, mu, V, method = "eigen")
nsim |
An integer indicating the number of realizations from the distribution. |
mu |
A vector of length n containing the mean values of the multivariate normal distribution. |
V |
The covariance matrix of the multivariate normal distribution. The matrix should be symmetric and positive definite. The size must be n times n. |
method |
The method for performing a decomposition of the covariance matrix. Possible values are "eigen", "chol", and "svd", Eigen value decomposition, Cholesky decomposition, or Singular Value Decomposoition, respectively. |
An n \times nsim matrix containing the nsim realizations of the multivariate normal distribution. Each column of the matrix represents a realization of the multivariate normal distribution.
Joshua French
rmvnorm
n <- 20 mu <- 1:n V <- exp(-dist1(matrix(rnorm(n)))) rmvnorm(nsim = 100, mu = mu, V = V, method = "eigen")
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