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Dakota Reference Manual
Version 6.15
Explore and Predict with Confidence
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Hessians are needed and will be obtained from a mix of numerical, analytic, and "quasi" sources
Alias: none
Argument(s): none
Child Keywords:
Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description | |
---|---|---|---|---|
Optional | id_numerical_hessians | Identify which numerical-Hessian corresponds to which response | ||
Optional (Choose One) | Step Scaling (Group 1) | relative | (Default) Scale step size by the parameter value | |
absolute | Do not scale step-size | |||
bounds | Scale step-size by the domain of the parameter | |||
Optional (Choose One) | Finite Difference Type (Group 2) | forward | (Default) Use forward differences | |
central | Use central differences | |||
Optional | id_quasi_hessians | Identify which quasi-Hessian corresponds to which response | ||
Optional | id_analytic_hessians | Identify which analytical Hessian corresponds to which response |
The mixed_hessians
specification means that some Hessian information is available directly from the simulation (analytic) whereas the rest will have to be estimated by finite differences (numerical) or approximated by secant updating. As for mixed gradients, this specification allows the user to make use of as much analytic information as is available and then estimate/approximate the rest.
The id_analytic_hessians
list specifies by number the functions which have analytic Hessians, and the id_numerical_hessians
and id_quasi_hessians
lists specify by number the functions which must use numerical Hessians and secant Hessian updates, respectively. Each function identifier, from 1 through the total number of functions, must appear once and only once within the union of the id_analytic_hessians
, id_numerical_hessians
, and id_quasi_hessians
lists.
The fd_hessian_step_size
and bfgs
, damped
bfgs
, or sr1
secant update selections are as described previously in responses and pertain to those functions listed by the id_numerical_hessians
and id_quasi_hessians
lists.
These keywords may also be of interest: