1Blurb::
2Determine how the final covariance matrix is computed
3Description::
4\c covariance
5(NL2SOL's \c covreq) specifies whether and how NL2SOL computes
6a final covariance matrix.
7
8The desired covariance approximation:
9\li 0 = default = none
10\li 1 or -1 ==> \f$\sigma^2 H^{-1} J^T J H^{-1}\f$
11\li 2 or -2 ==> \f$\sigma^2 H^{-1}\f$
12\li 3 or -3 ==> \f$\sigma^2 (J^T J)^{-1}\f$
13\li Negative values ==> estimate the final Hessian H by finite
14differences of function values only (using \c fd_hessian_step_size)
15\li Positive values ==> differences of gradients (using
16\c fd_hessian_step_size)
17
18
19Topics::
20Examples::
21Theory::
22Faq::
23See_Also::
24