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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Specify the type of model discrepancy
Alias: none
Argument(s): none
Default: gaussian process
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Required (Choose One) | Discrepancy Model (Group 1) | gaussian_process | Use the Surfpack version of Gaussain process as the discrepancy model | |
polynomial | Use a polynomial surrogate as the discrepancy model |
After the model parameters are calibrated, the difference between the data and the calibrated model, i.e. the model discrepancy, is calculated
Each corresponds to a different regression model. These regression models must all be either Gaussian process or polynomial models, and they are functions of the configuration variable
. The order of the trend function may be selected using the
correction_order
command by specifying constant
, linear
, or quadratic
.
Note that for Dakota 6.9 and earlier, this keyword only applies to discrepancy calculations for scalar responses. For field responses, a Gaussian process model with a quadratic function is used by default.