Dakota Reference Manual: discrepancy_type

| Dakota Reference Manual Version 6.15 Explore and Predict with Confidence

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discrepancy_type

Specify the type of model discrepancy

## Specification

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

## Description

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.