Dakota Reference Manual: local

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local

Build a locally accurate surrogate from data at a single point

## Specification

Alias: none

Argument(s): none

Child Keywords:

| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description
--- | --- | --- | --- | ---
| Required | taylor_series | Construct a Taylor Series expansion around a point
| Required | actual_model_pointer | Pointer to specify a "truth" model, from which to construct a surrogate

## Description

Local approximations use value, gradient, and possibly Hessian data from a single point to form a series expansion for approximating data in the vicinity of this point.

The currently available local approximation is the `taylor_series` selection.

The truth model to be used to generate the value/gradient/Hessian data used in the series expansion is identified through the required `actual_model_pointer` specification. The use of a model pointer (as opposed to an interface pointer) allows additional flexibility in defining the approximation. In particular, the derivative specification for the truth model may differ from the derivative specification for the approximation, and the truth model results being approximated may involve a model recursion (e.g., the values/gradients from a nested model).

## See Also

These keywords may also be of interest:

- global
- hierarchical
- multipoint