.. _method-efficient_global-gaussian_process: """""""""""""""" gaussian_process """""""""""""""" Gaussian Process surrogate model .. toctree:: :hidden: :maxdepth: 1 method-efficient_global-gaussian_process-surfpack method-efficient_global-gaussian_process-dakota method-efficient_global-gaussian_process-experimental **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 | | | +--------------------+---------------------------------------------+ | | | `experimental`__ | Use the experimental Gaussian Process | | | | | surrogate | +-------------------------+--------------------+--------------------+---------------------------------------------+ .. __: method-efficient_global-gaussian_process-surfpack.html __ method-efficient_global-gaussian_process-dakota.html __ method-efficient_global-gaussian_process-experimental.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.*