Blurb::
Construct a surrogate from multiple existing training points
Description::
Multipoint approximations use data from previous design points to
improve the accuracy of local approximations. The data often
comes from the current and previous iterates of a minimization algorithm.

Currently, only the
Two-point Adaptive Nonlinearity %Approximation (TANA-3) method of
\cite Xu98 is supported with the \c tana keyword.

The
truth model to be used to generate the value/gradient data used in the
approximation is identified through the required \c
actual_model_pointer specification.


Topics::
Examples::
Theory::
Faq::
See_Also::	model-surrogate-local, model-surrogate-global, model-surrogate-hierarchical
