This command computes a finite difference Hessian matrix H for the error analysis following optimization. The elements of H are given by:
The evaluation of H by means of finite differences requires 2n+n*(n-1)/2 additional TOUGH2 simulations, where n is the number of parameters. By default, the Hessian matrix, which is the inverse of the parameter covariance matrix, is approximated by
based on the linearity assumption, i.e., the second derivative term is ignored.
Evaluating the finite difference Hessian, which takes into account the
non-linearities, provides a means by which to check the linearity assumption
(for another approach see command
>> ERROR analysis should be based on
>>> finite difference approximation of the HESSIAN matrix