R = mvnrnd(MU,SIGMA) returns an n-by-d matrix R of random vectors chosen from the multivariate normal distribution with mean MU, and covariance SIGMA. MU is an n-by-d matrix, and mvnrnd generates each row of R using the corresponding row of mu. SIGMA is a d-by-d symmetric positive semi-definite matrix, or a d-by-d-by-n array. If SIGMA is an array, mvnrnd generates each row of R using the corresponding page of SIGMA, i.e., mvnrnd computes R(i,:) using MU(i,:) and SIGMA(:,:,i). If the covariance matrix is diagonal, containing variances along the diagonal and zero covariances off the diagonal, SIGMA may also be specified as a 1-by-d vector or a 1-by-d-by-n array, containing just the diagonal. If MU is a 1-by-d vector, mvnrnd replicates it to match the trailing dimension of SIGMA.

r = mvnrnd(MU,SIGMA,cases) returns a cases-by-d matrix R of random vectors chosen from the multivariate normal distribution with a common 1-by-d mean vector MU, and a common d-by-d covariance matrix SIGMA.

Examples

mu = [2 3];
SIGMA = [1 1.5; 1.5 3];
r = mvnrnd(mu,SIGMA,100);
plot(r(:,1),r(:,2),'+')

mvnrnd - Multivariate normal random numbers

Syntax

Description

Examples

See Also

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