Dakota Reference Manual  Version 6.15
Explore and Predict with Confidence
 All Pages
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

\[ \delta_i(x_j) = d_i(x_j) - M_i(\theta^*, x_j). \]

Each $\delta_i$ 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 $x$. 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.