.. _method-global_evidence-ego-gaussian_process-experimental:

""""""""""""
experimental
""""""""""""


Use the experimental Gaussian Process surrogate


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

   method-global_evidence-ego-gaussian_process-experimental-export_model
   method-global_evidence-ego-gaussian_process-experimental-options_file


**Specification**

- *Alias:* None

- *Arguments:* None


**Child Keywords:**

+-------------------------+--------------------+--------------------+-----------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword     | Dakota Keyword Description                    |
|                         | Group              |                    |                                               |
+=========================+====================+====================+===============================================+
| Optional                                     | `export_model`__   | export_model not active                       |
+----------------------------------------------+--------------------+-----------------------------------------------+
| Optional                                     | `options_file`__   | ``options_file`` not active                   |
+----------------------------------------------+--------------------+-----------------------------------------------+

.. __: method-global_evidence-ego-gaussian_process-experimental-export_model.html
__ method-global_evidence-ego-gaussian_process-experimental-options_file.html



**Description**


The experimental GP surrogate is an emerging capability intended to
supersede the ``dakota`` and ``surfpack`` GP implementations by unifying
the best features of both. It also includes additional features such
as the ability to export the model and then use it from Python.


