Gives a Latin hypercube design matrix with an arbitrary number of
points in an arbitrary number of dimensions. The toy dataset
was generated using latin.hypercube().
Usage
latin.hypercube(n, d, normalize=FALSE)
Arguments
n
Number of points
d
Number of dimensions
normalize
Boolean variable with TRUE meaning to
normalize each column so the minimum is zero and the maximum is
one. If it takes its default FALSE, the points represent
midpoints of $n$ equispaced intervals; the points thus ha