Dakota Reference Manual  Version 6.16
Explore and Predict with Confidence
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Gaussian Process surrogate model


Alias: kriging

Argument(s): none

Child Keywords:

Required/Optional Description of Group Dakota Keyword Dakota Keyword Description
(Choose One)
GP Implementation (Group 1) dakota Select the built in Gaussian Process surrogate
surfpack Use the Surfpack version of Gaussian Process surrogates
Optional export_approx_variance_file

Output file for surrogate model variance evaluations


Use the Gaussian process (GP) surrogate from Surfpack, which is specified using the 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.