Blurb::
Hessians are needed and will be approximated by secant updates (BFGS
or SR1) from a series of gradient evaluations

Description::
The \c quasi_hessians specification means that Hessian information is
needed and will be approximated using secant updates (sometimes called
"quasi-Newton updates", though any algorithm that approximates
Newton's method is a quasi-Newton method).

Compared to finite difference numerical Hessians, secant
approximations do not expend additional function evaluations in
estimating all of the second-order information for every point of
interest. Rather, they accumulate approximate curvature information
over time using the existing gradient evaluations. 

The supported secant approximations include the
Broyden-Fletcher-Goldfarb-Shanno (BFGS) update (specified with the
keyword \c bfgs) and the Symmetric Rank 1 (SR1) update (specified with
the keyword \c sr1).

Topics::	
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Theory::



Faq::
See_Also::	responses-no_hessians, responses-numerical_hessians, responses-analytic_hessians, responses-mixed_hessians
