![]() |
Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
|
Use the Gaussian process regression surrogate from the surrogates module
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | trend | This keyword enables the use of deterministic polynomial trend function | ||
Optional | num_restarts | Number of optimization restarts for L-BFGS-B | ||
Optional (Choose One) | Nugget (Group 1) | nugget | Value for the fixed nugget parameter | |
find_nugget | Use regression to estimate the nugget. | |||
Optional | options_file | Filename for a YAML file that specifies Gaussian process options | ||
Optional | export_approx_variance_file | Output file for surrogate model variance evaluations | ||
Optional | export_model | Exports surrogate model in user-specified format(s) | ||
Optional | import_model | Import surrogate model from archive file |
This Gaussian process implementation is contained in Dakota's surrogates module and is considered experimental. It uses gradient-based optimization with restarts to determine hyperparmeters and trend coefficients. Nugget and trend estimation are optional.