Compute the covariance matrix.
c = moc_cov (x) c = moc_cov (x,opt) c = moc_cov (x,y) c = moc_cov (x,y,opt)
If each row of xand y is an observation, and each column is
a variable, then the (i, j)-th entry of
moc_cov (x, y)} is the covariance between the i-th
variable in x and the j-th variable in y.
If called with one argument, compute moc_cov (x, x)}, the
covariance between the columns of x.
The argument opt determines the type of normalization to use. Valid values are
normalize with N-1, provides the best unbiased estimator of the covariance [default]
normalize with N, this provides the second moment around the mean