Simulate from a Multivariate Normal Distribution

Produces one or more samples from the specified multivariate normal distribution.

mvrnorm(n = 1, mu, Sigma, tol = 1e-06, empirical = FALSE)

Arguments

n

the number of samples required.

mu

a vector giving the means of the variables.

Sigma

a positive-definite symmetric matrix specifying the covariance matrix of the variables.

tol

tolerance (relative to largest variance) for numerical lack of positive-definiteness in Sigma.

empirical

logical. If true, mu and Sigma specify the empirical not population mean and covariance matrix.

Value

If n = 1 a vector of the same length as mu, otherwise an n by length(mu) matrix with one sample in each row.

Details

The matrix decomposition is done via eigen; although a Choleski decomposition might be faster, the eigendecomposition is stabler.* Causes creation of the dataset .Random.seed if it does not already exist, otherwise its value is updated.

See also