[SciPy-User] calculating the jacobian for a least-squares problem

[Andrew Nelson]

> You are using the cross-product of the jacobian (outer product of
gradient).

This is correct.

I discovered a bug in the way I was calculating the covariance matrix. I
was initially scaling all parameters to unity, and unwinding that scaling
after inverting the Hessian. I was multiplying by the incorrect values when
I did so. The diagonal terms in the covariance matrix were fine, but the
off diagonal terms were incorrect, leading to problems when using
np.random.multivariate_normal.
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