.. _method-multifidelity_stoch_collocation-p_refinement-dimension_adaptive:

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dimension_adaptive
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Perform anisotropic expansion refinement by preferentially adapting in dimensions that are detected to have higher "importance".


.. toctree::
   :hidden:
   :maxdepth: 1

   method-multifidelity_stoch_collocation-p_refinement-dimension_adaptive-sobol
   method-multifidelity_stoch_collocation-p_refinement-dimension_adaptive-generalized


**Specification**

- *Alias:* None

- *Arguments:* None


**Child Keywords:**

+-------------------------+--------------------+--------------------+-----------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword     | Dakota Keyword Description                    |
|                         | Group              |                    |                                               |
+=========================+====================+====================+===============================================+
| Required (Choose One)   | Dimension          | `sobol`__          | Estimate dimension preference for automated   |
|                         | Adaptivity         |                    | refinement of stochastic expansion using      |
|                         | Estimation         |                    | total Sobol' sensitivity indices.             |
|                         | Approach           +--------------------+-----------------------------------------------+
|                         |                    | `generalized`__    | Use the generalized sparse grid dimension     |
|                         |                    |                    | adaptive algorithm to refine a sparse grid    |
|                         |                    |                    | approximation of stochastic expansion.        |
+-------------------------+--------------------+--------------------+-----------------------------------------------+

.. __: method-multifidelity_stoch_collocation-p_refinement-dimension_adaptive-sobol.html
__ method-multifidelity_stoch_collocation-p_refinement-dimension_adaptive-generalized.html



**Description**


Perform anisotropic expansion refinement by preferentially adapting in dimensions that are detected to hold higher "importance" in resolving statistical quantities of interest.

Dimension importance must be estimated as part of the refinement process.  Techniques include either sobol or generalized for stochastic collocation and either sobol, decay, or generalized for polynomial chaos. Each of these automated refinement approaches makes use of the max_iterations and convergence_tolerance iteration controls.


