.. _method-bayes_calibration-queso-emulator-gaussian_process:

""""""""""""""""
gaussian_process
""""""""""""""""


Gaussian Process surrogate model


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

   method-bayes_calibration-queso-emulator-gaussian_process-surfpack
   method-bayes_calibration-queso-emulator-gaussian_process-dakota
   method-bayes_calibration-queso-emulator-gaussian_process-build_samples
   method-bayes_calibration-queso-emulator-gaussian_process-posterior_adaptive
   method-bayes_calibration-queso-emulator-gaussian_process-import_build_points_file


**Specification**

- *Alias:* kriging 

- *Arguments:* None

- *Default:* Surfpack Gaussian process


**Child Keywords:**

+-------------------------+--------------------+------------------------------+-----------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword               | Dakota Keyword Description                    |
|                         | Group              |                              |                                               |
+=========================+====================+==============================+===============================================+
| Required (Choose One)   | GP Implementation  | `surfpack`__                 | Use the Surfpack version of Gaussian Process  |
|                         |                    |                              | surrogates                                    |
|                         |                    +------------------------------+-----------------------------------------------+
|                         |                    | `dakota`__                   | Select the built in Gaussian Process          |
|                         |                    |                              | surrogate                                     |
+-------------------------+--------------------+------------------------------+-----------------------------------------------+
| Optional                                     | `build_samples`__            | Number of initial model evaluations used in   |
|                                              |                              | build phase                                   |
+----------------------------------------------+------------------------------+-----------------------------------------------+
| Optional                                     | `posterior_adaptive`__       | Adapt emulator model to increase accuracy in  |
|                                              |                              | high posterior probability regions            |
+----------------------------------------------+------------------------------+-----------------------------------------------+
| Optional                                     | `import_build_points_file`__ | File containing points you wish to use to     |
|                                              |                              | build a surrogate                             |
+----------------------------------------------+------------------------------+-----------------------------------------------+

.. __: method-bayes_calibration-queso-emulator-gaussian_process-surfpack.html
__ method-bayes_calibration-queso-emulator-gaussian_process-dakota.html
__ method-bayes_calibration-queso-emulator-gaussian_process-build_samples.html
__ method-bayes_calibration-queso-emulator-gaussian_process-posterior_adaptive.html
__ method-bayes_calibration-queso-emulator-gaussian_process-import_build_points_file.html



**Description**


Use the Gaussian process (GP) surrogate from Surfpack, which is
specified using the
:dakkw:`model-surrogate-global-gaussian_process-surfpack` keyword.

An alternate version of GP surrogates was available in prior versions of
Dakota. *For now, both versions are supported but the ``dakota`` version is
deprecated and intended to be removed in a future release.*

*Known Issue: When using discrete variables, there have been
sometimes significant differences in surrogate behavior observed
across computing platforms in some cases.  The cause has not yet been
fully diagnosed and is currently under investigation.  In addition,
guidance on appropriate construction and use of surrogates with
discrete variables is under development.  In the meantime, users
should therefore be aware that there is a risk of inaccurate results
when using surrogates with discrete variables.*


