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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Gradients are needed and will be approximated by finite differences
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | method_source | Specify which finite difference routine is used | ||
Optional (Choose One) | Gradient Source (Group 1) | dakota | (Default) Use internal Dakota finite differences algorithm | |
vendor | Use non-Dakota fd algorithm | |||
Optional | interval_type | Specify how to compute gradients and hessians | ||
Optional (Choose One) | Finite Difference Type (Group 2) | forward | (Default) Use forward differences | |
central | Use central differences | |||
Optional | fd_step_size | Step size used when computing gradients and Hessians |
The numerical_gradients
specification means that gradient information is needed and will be computed with finite differences using either the native or one of the vendor finite differencing routines.
These keywords may also be of interest: