Syntax

Description

X = lhsnorm(mu,sigma,n)returns ann-by-pmatrix,X, containing a latin hypercube sample of sizenfrom ap-dimensional multivariate normal distribution with mean vector,mu, and covariance matrix,sigma.

Xis similar to a random sample from the multivariate normal distribution, but the marginal distribution of each column is adjusted so that its sample marginal distribution is close to its theoretical normal distribution.

X = lhsnorm(mu,sigma,n,flag)controls the amount of smoothing in the sample. Ifflagis'off', each column has points equally spaced on the probability scale. In other words, each column is a permutation of the valuesG(0.5/n), G(1.5/n), ..., G(1-0.5/n), whereGis the inverse normal cumulative distribution for that column's marginal distribution. Ifflagis'on'(the default), each column has points uniformly distributed on the probability scale. For example, in place of0.5/nyou use a value having a uniform distribution on the interval(0/n,1/n).

[X,Z] = lhsnorm(...)also returnsZ, the original multivariate normal sample before the marginals are adjusted to obtainX.

References

See Also

lhsdesign|mvnrnd