Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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Construct a surrogate from multiple existing training points


Alias: none

Argument(s): none

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
Required tana Local multi-point model via two-point nonlinear approximation
Required actual_model_pointer Pointer to specify a "truth" model, from which to construct a surrogate


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 [91] is supported with the tana keyword.

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

See Also

These keywords may also be of interest: