1Blurb::
2Construct a surrogate from multiple existing training points
3Description::
4Multipoint approximations use data from previous design points to
5improve the accuracy of local approximations. The data often
6comes from the current and previous iterates of a minimization algorithm.
7
8Currently, only the
9Two-point Adaptive Nonlinearity %Approximation (TANA-3) method of
10\cite Xu98 is supported with the \c tana keyword.
11
12The
13truth model to be used to generate the value/gradient data used in the
14approximation is identified through the required \c
15actual_model_pointer specification.
16
17
18Topics::
19Examples::
20Theory::
21Faq::
22See_Also::	model-surrogate-local, model-surrogate-global, model-surrogate-hierarchical
23