Re: calculating the jacobian for a least-squares problem

> 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.

_______________________________________________
SciPy-User mailing list
[email protected]
https://mail.python.org/mailman/listinfo/scipy-user