rGaussian {bbricks} | R Documentation |
Generate random samples from a Gaussian distribution. For a random vector x, the density function of a (multivariate) Gaussian distribution is defined as:
sqrt(2 pi^p |Sigma|)^{-1} exp(-1/2 (x-mu )^T Sigma^{-1} (x-mu))
where p is the dimension of x.
rGaussian(n, mu, Sigma = NULL, A = NULL)
n |
integer, number of samples. |
mu |
numeric, mean vector. |
Sigma |
matrix, covariance matrix, one of Sigma and A should be non-NULL. |
A |
matrix, the Cholesky decomposition of Sigma, an upper triangular matrix, one of Sigma and A should be non-NULL. |
A matrix of n rows and length(mu) columns.
x <- rGaussian(1000,mu = c(1,1),Sigma = matrix(c(1,0.5,0.5,3),2,2)) plot(x)